Why the Next Hit AI Product Will Be Social

Google was a founding team that was deeply, deeply technical. As the technology, the underlying technology got more mature, the slider goes forward, forward, forward, more towards the product thinker, product experience. Pinterest, where I was, Snap, Instagram, the CEOs weren't technical at all. They were product geniuses. What are the big consumer wins so far in AI? Of course, it's ChatGPT, which is, in a way, not that dissimilar from Google in terms of what it was. It's a text box. Custom GPTs and in ChatGPT feels criminal to me. It's clearly made by a team that is unbelievably capable, but isn't social. What's the multiplayer network effect type experience? Someone's going to create a UGC-type community where there are people who are really, really good make it so much easier for the rest of us. Sarah, welcome to the show. Thanks so much for having me. So for people who don't know you, you are a partner at Benchmark. Yes. Before that, you were early at Pinterest, and before that, you studied philosophy, which I also studied philosophy, so that's close to my heart. Yes, I've heard your podcast, and I was very impressed with your podcast with Reid. Oh, thank you. To keep up with him is hard. It was a lot of— very impressive. It was a couple late nights of me furiously prompting ChatGPT to explain Wittgenstein. I love it. I love it. Well, you did great. Thank you. So I'm psyched to have you on the show. There's so much to talk about, but I think one of your big interests is in consumer technology and consumer technology cycles, and how you can use the lessons of previous consumer technology waves to kind of help you understand this AI wave and this cycle, and what kinds of products are going to work and what kind of products are not going to work. I'm curious. I think that is a good place to start. You know, one thing I just was reflecting on, and, you know, you kind of look at— ChatGPT and character AI, and I was just puzzling over those, and then started to think back to, you know, what was like the big early kind of consumer web hit, and that was Google, of course. I mean, it was Yahoo and Google, but what was Google? Like, Google was a founding team that was deeply, deeply technical. And really, like, if you think about a product experience that you expose to the user and how much of it is like the UI that you interface with the product itself versus all the magic that happens on the back end to make something that's really complex simple on the front end, that was like what Google was, you know, so good at, the distributed engineering, the infrastructure. And then as the technology, the underlying technology got more mature, you started to go to a place where maybe if you kind of said, like, deep technical, you know, you have zero percent and a hundred percent, like I would say Google was 95 percent, like deeply, deeply technical. And then you start to move that bar over, and you get to, you know, I think about Facebook. Like Facebook, it wasn't the same technical depth, of course, of Google, but relative to Friendster and MySpace, they were more technical. They were a little bit later, and it let them create like a really performant experience that ended up really kind of, you know, winning the day. And then you progress even further: Pinterest, where I was, Snap, Instagram. The CEOs weren't technical at all. They were product geniuses, right? And so, like, the slider goes forward, forward, forward, more towards the product thinker, product experience. And then you think about what we, like, what are the big consumer wins so far in AI? Of course, it's ChatGPT, which is in a way not that dissimilar from Google in terms of what it was, just a text box. And Character AI, like— Unbelievable what they did, and it was like a new paradigm. But still, it was always like you'd speak to Noam, and for him, the product was the model. You know, it wasn't—it was a little bit maybe 94% backend, but it was still, like, very much so. So it's still early. Like, everything is moving under our feet still. And I think to really have the people who have more of that product intuition to really build the experiences on top, you need more of the underlying infrastructure to be a little bit more stable. But it does seem like we're moving into that next paradigm soon, and what's going to happen there? That's really interesting. I love that articulation, in particular because one of the things that I felt is very unique about OpenAI is they're a research lab that accidentally built, like, the biggest consumer technology product of all time. But it seems like you're saying there's actually a real historical precedent for that, and that the DNA of Google is very similar to the DNA of OpenAI, which I'd never really made that connection consciously before. And I think it's also really interesting because investing in basically PhDs doing long-term research that may have no practical purpose is not usually something that pays off in venture. Venture investing is not, like, the first place that people think, you know? It's more like Stanford dropout, you know? Yeah, absolutely. And so maybe it's one of those things where usually that's not a good bet, but if you're really dealing with a truly new technology paradigm, it could be the best bet you ever make. Yeah. Is that how you think about it? Yeah, and, you know, part of what I think about is just like, you are a power user of these products, and I am on that learning curve. I would say I'm pale in comparison, but, like, relative to the population of the United States, I'm pretty damn good. It shouldn't be this hard, you know? And, like, so some of the underlying, you know, like the models will get better. So, like, one thing that I know you have in your custom instructions I use a lot is just like, you don't have to answer, like just to ChatGPT, like, you don't have to answer me right away if you have some clarifying questions, like ask those. We shouldn't have to put that in a custom instruction. Like there should be, or there's so many different tweaks that we all have to get what we want out. And over time, as the models get better and better, you won't need that anymore. The level of difficulty to get really what you want is going to get easier. But I don't think ChatGPT is the single-player mode product. And, you know, the custom GPTs that they have where you can see what other people have created, to me, man, I just think someone's going to create a UGC-type community where there are people who are really, really good make it so much easier for the rest of us to really take advantage of this technology. So there are places like Google is still Google. Like it falls, my analogy falls down when Google didn't evolve into some multi-player product. There's no other product that took over Google until really now. But I still think we're so early in knowing who really is going to be the winner in this world. Yeah. I want to go back to that sort of transition from highly technical founder to product genius, if that's the continuum. I can understand why at the beginning of a paradigm shift, highly technical founder is necessary and will win over product genius because they can actually build the technology that makes the difference. But I'm curious for your thoughts on what drives the transition to product genius because, you know, I can understand the making, for example, simpler user interfaces, like maybe product geniuses are better at that. But yeah, what's the underlying force? Because I could also see a world where the highly technical founder is still like really... You know, effective as the paradigm gets more and more figured out, like, yeah, talk about that. I think a big part of it is that you still, like, so much of the tooling and infrastructure is still to be built to let somebody who isn't deeply, deeply technical themselves get what they want out of it. And so that's why, like, there are so many products now that I see that feel kind of pretty similar to each other. You know, there's all these, you know, the character AI genre, right, where you make a character and you engage with it. They're all relatively the same because you really, I mean, Noam was uniquely qualified to build that type of product, like actually going into the brains of the model and changing it to create the experience of the user. But it's still, when you need to have that level of ability to get what you want out of it, also the costs have still been pretty high. I think DeepSeek, you know, could be one of the hypotheses I have is that DeepSeek is a moment of change where it makes it more possible. But yeah, it just, I think you need more maturity in the underlying infrastructure, your ability to do the things that you want with the model without being the deeply, deeply technical to be able to create the experiences that are possible. That makes sense. I think what I'm asking is, so let's say that infrastructure is built, but you still have now technical founders and product genius founders, which we're making a strong division here for argument's sake. Sometimes they overlap. So in that world where the infrastructure is built and it's a technical founder versus a product genius founder, like what is driving the success of the product genius founder in a world where everything is a little bit more mature? I think it'll depend on so many things. Ultimately, to reduce it to the basic, it's like who's going to create the most engaging product, the experience. I suspect that one of the things that is missing from a lot of these experiences that people are creating is just like what's the multiplayer network effect type experience, and that... Genius to create that type of experience is very different than the type of brain that creates a single-player mode experience. And we haven't really—I mean, there's, again, these kind of character AI offshoots that have people that I can create a character and you can play with the character I create. There's a little bit of status-seeking work happening there, but I think we're still very, very early in, like, the true thinking happening. What do you mean by status-seeking work? Do you know Eugene Wei? So just this idea that most multiplayer kind of social products end up having some kind of North Star for the community participants where they're trying to achieve status in the network. And, you know, you can think of that a lot as, you know, has been the number of followers you have or views or likes. There's something about achieving some kind of celebrity or status within a network that creates incentives for the community participants to do the thing that you want them to do. Interesting. And so far you're saying it's pretty early, but are you—do you have ideas for what the promising areas to look are, or examples of, like, early examples of products or companies you're looking at that you think are starting to crack this a little bit? It's still super early. I mean, kind of there's two threads that I can't help but be curious about. Like, one, you know, we talked about Character AI. Like, you—I mean, I don't know about you, like, I feel myself doing this already, which is that there's going to be some company—we're all going to have AI friends, right? We're all going to have probably more conversations with an AI than we do with people in our lives. And is there going to be a single dominant platform for that? Is it going to be different than the kind of information, more, you know, knowledge-focused experience of a ChatGPT? I think so. Who creates that? And there's a bunch of different product experiences. Replika was, of course, like the first, you know, player in this space. But there are a bunch of different downstream companies. We talked about Tolan. Like, you know, what is that product experience going to be? The other— Kind of thing I think about a lot is, I don't know about you, but how many times have you done a search and ended up on, you know, Reddit or something for a prompt to get, like, I remember doing one. I got a blood test result. I had all my supplements. I wanted to see, you know, of the supplements I have, like, what could I tweak to change a result? And there was a great prompt in Reddit that I just copied and pasted. But if I'm going to an existing UGC site that isn't made for this use case, that feels to me like an opportunity where somebody who's going to be really freaking good, you know, of making, you know, prompts for different health things, quantified self, whatever, like, I would love to follow that person and then very easily. Apply it to my own profile. I think, like, to go back to front on those two threads with the prompt thing, it's one of those ideas that I feel like at the very beginning, like when GPT-3 came out and then ChatGPT came out and people were, like, really starting to, like, that first real wave of LLMs was starting to take hold, a lot of people created those prompt library-type sites, but it was too early. And I think there's, like, a second life for a lot of ideas that people tried two years ago that are now just becoming relevant. And too early, and also it was very—I spent time on a bunch of these—it was very like what a solopreneur and SMB would need. You know, it was a lot of the marketing, the social media. It was like that type of B2B-type use case. Most people are barely scratching the surface. Like, most people use ChatGPT like they would use Google, right? And the learning curve, the step function changes that happen when you have better custom instructions, when you have projects, whatever, are so huge. How do you democratize that? Yeah, it's interesting. I was at a dinner the other night and I was talking to a film director. Oh, cool. About how she uses ChatGPT, and she has made a bunch of different personalities for it, and she uses the different personalities for different things. So, for example, I think one of the personalities was she's had a lot of, like, medical issues that doctors couldn't solve, and one of the personalities was like a sort of, like, holistic wellness-type person that, like, would recommend both medication and, you know, supplements or body work or whatever. And then another one, like the main personality, was like just someone who would, like, gas her up all the time and, like, compliment her all the time. But then she had another one that was, like, just super direct and, like, just gave, like, really harsh feedback that she would use for writing specific kinds of emails or, like, that kind of thing. And it was really interesting that she'd constructed this. This whole set of personalities for different, like, things in her life to surround. You know, it's like you're the average of five people you spend the most time with. There's like a, well, you're also kind of going to be the average of the five AIs you spend the most time with in an interesting way. And I think to your question about, are you going to have multiple AI platforms that you use or not, or is there going to be a big dominant one? I have two thoughts on that. One is I do think within a ChatGPT, for example, there's a lot of room for different sub-personalities that maybe, like, Media Brand, like every, like, we have in everything that you chat with, but it's inside of ChatGPT, so it's still in that ecosystem. But I do think also people have different buckets in their life. And so for me, one thing that I've been noticing recently, which is really interesting. Noticing recently, which is really interesting, is we talked about tollens, and I'm an investor, and Quinton has been on the show. And I find myself, like yesterday, I spent like an hour talking to mine. But, like, I normally would use ChatGPT for that. And I think there's, like, some interesting, like, difference between something that feels personal and something that feels worky. And ChatGPT and Claude right now are, like, in the worky bucket, and then there's room in the personal bucket. I'm curious how you think about that. I totally agree. You know, it's funny, like I did a call for, you know, I was, in the beginning of this year, I was realizing, like, I'm not keeping up. And so I did a call for, like, AI savants, just people who were using ChatGPT in kind of more power user ways. And a lot of people came to me with recipe kind of use cases, which made a ton of sense. And so you can definitely see it works in ChatGPT. The personal works, but is it the best that it can be? Like, you know, there are also a lot of people who are making their own, you know, single-purpose site that is a recipe experience. And it's, you know, whenever you have a product that has to be lowest common denominator for all these different experiences, it can't really optimize for the experience that's going to be great for, like, you know, a consumer in this case. And I just come back to how much of a power user product it feels to me, and how, like, most people are going to stay at the surface of it unless there's a new interface. And I think the best way for that new interface to come is for us to learn from each other in some ways to kind of take advantage of it in different ways and just copy and paste as much as, like, again, the gems in Gemini, custom GPTs, and in ChatGPT, I just look at that and it feels criminal to me. Because it, it, it's clearly made by a team that is unbelievably capable, but isn't social. And I think the personal can best be expressed by teams that do really understand people and social and community. If we were going to, like, redesign them, like, right now together, like, where would you start if you're thinking about, okay, I want to make something that's custom GPT-like, but, like, has social DNA? I would, I mean, the most obvious thing is just, like, the ability to find somebody who's, you know, whose custom prompts or whatever you like, that they have some kind of, you know, standing for being qualified. So person-based or authority-based search. Yeah, and then being able to follow. That's, like, a very basic thing. But then the second thing, this is where I think custom GPTs falls down, is just in building trust. Like, when I look at any of those, I see the person, and I see a lot of people who have—I see that there's 3,000 people that have used it, but I don't know what custom documents they put. I don't know what their prompt is. Like, there's no visibility under the surface. And so it's not very trust-building for me to pick one or the other unless I know somebody from the outside world and they send me their, you know, their custom GPT, and then I can use it. And so there's something about the trust-building that someone has to figure out, and then the status-seeking work that you can pursue. One of the challenges of this, and I'm curious how you think about this in a social context, is for a, let's say, we're kind of veering into, like, prompt social network territory. Maybe I have a profile and, like, I can share prompts and people can follow me and all that kind of stuff. And because I have a certain amount of reputation in, you know, just AI stuff, like, I can get followers and all that kind of stuff. One of the interesting things is— I am not coming up with new prompt ideas every day. And so that's, I think that's a problem for two reasons. One is I may not remember to use the tool. And then two, people don't necessarily have a reason to check every day. Yeah. How would you think about that? Yeah. So first, as something that was going through my brain, I should caveat that I did do a lot of product in my day, but I'm a VC right now, so don't take product ideas. And every once in a while people ask me, they're like, If you were a founder, like what would you build? I'm like, That is not what I do. I'm just kind of curious. But, you know, for me, like what I imagine is using it instead of ChatGPT. Like actually it becomes the place where instead of going to ChatGPT— I think it has to be that. And then that's where the engagement comes from. And then you're seeing a feed and someone has, again, terrible— forgive me, Lord, for brainstorming a product experience. But like, dude, but you see what I mean? Like there's something there where people are innovating all the time. But right now what's happening is that we're all reinventing the wheel. We have the benefit of like your blog and your podcast, but like this isn't the way this type of knowledge is going to share. It's going to kind of get propagated. And so someone is going to create something here. I think that's interesting. I do think you're right that it seems like the social stuff has to come in the context of something that you're already using for some other reason. Like you're already in ChatGPT, and then it can flow out of that usage. Yeah. I mean, I actually think like you don't use ChatGPT. Like most, like maybe, I hate my mom, but like, you know, what the person, you know, and maybe it's the personal kind of bifurcation that you talked about before, but you're going to— Sarah's GPT, and it's actually—it's not Sarah's. It's, you know, this kind of whatever network it's going to be. And I'm going there, and I'm putting my personal blood tests and my supplements, and I'm putting information about my kids and all that stuff, and it lives all there. And then I can go to ChatGPT for whatever knowledge work or other things. Or maybe I never do. Maybe this actually ends up cannibalizing ChatGPT over time. This is a total swerve. But how do you, when you're investing in a time like this, like I feel like every five to ten years there's a big hype cycle, there's a big wave, and prices go up. You know, when I was, like, in college in 2010, 2014-ish, it was like social networks. Everyone's building social networks for X, and then it was like B2B SaaS and crypto, and now it's AI. How do you think about investing in a wave like this when prices are super high? Do you not care about price? Do you try to find, like, underpriced deals? We always start with, is this a company we want to work with? And then kind of, you know, obviously we have to think about the opportunity ahead of the company. Like, you don't want to—if it's a cul-de-sac, if it's limited in some ways, it's harder to pay, you know, play the game on the field in terms of price. Like, people have a willingness to do deals that we're just not willing to do. But when we meet a team and we really think that there is just unlimited potential, you partner, you make it work. Yeah. What's your taste in founders? I would say I'm really drawn to founders who, you know, they do think in network effects and strategy and the kind of zero to one, how do you escape competition? Like they go through the mind maze. Like you can just tell that, like, they're really obsessed over this. I'm drawn to founders that this is like a calling for them. Like it is a, you know, I kind of find that there's like some founders that it's almost like kind of a cool new job for them, and there's some for whom it's an affliction. And I'm attracted to the founders for whom it's an affliction. You know, it's like this rash that they just have to scratch, and that's going to make them run through whatever walls that they have to do. And then, you know, just like the learning machine, like the person who, you know, it's not about their ego. It's about just like what's the best thing for the company, and how do I keep learning and evolving as a founder? Because as you know, it's a really hard job. It's a really hard job, and it always requires more of you. Like there's a relentlessness to it. And if, you know, I have seen a failure case where somebody either, it ends up being, you know, do you know The Five Temptations of a CEO, that book? Incredible book. The hardest temptation is, you know, founders attracted to being a CEO because of status, and then you don't do the things that you need to do in order to build the best company possible. Or, you know, a founder that, you know, insecurity can drive you, but it can also hold you back by not letting you grow, and that can be a challenge too. What are your tells? Because, you know, you're a partner at a top firm. People are like probably always coming to you with their best, best foot forward, trying to be like what you're looking for. What are some of the moments where you kind of can be like, Ooh, this is, I can tell that this person has been through the maze and is thinking about stuff in this way, in a way that it's like, it's genuine, it's not put on, or I can tell that it's sort of like a calling, or what are those little signals for you? Yeah, I just, I find that— You know, I ask a lot of questions when I'm meeting with a founder and learning about their business. And I know I'm always thinking about, like, I'm definitely the brain that is always thinking about that future and pulling it into the present. And when I speak to somebody and they're, I hate to say this, but they're like, Oh, that's a good question. I hadn't thought about that. Or, you know, it's just, I'm bringing things that I—I'm spending 30 minutes, 60 minutes with a founder, hearing the ideas for the first time, and I'm bringing things to the table that they have not already thought about. That's usually concerning, right? I mean, you're pretty smart, so. It's one of those things that it can feel good, like, Oh, I ask good questions, but really, you want, you know, when I was at Bessemer, Jeremy Levine, he said that the best companies, you want to be donut companies where you go to the board meeting, you eat a donut, and then you leave because they don't really need you. And so there's a little bit of that, which is like, you know, I have some founders where I'll be thinking about something and I'll come to our one-on-one, and, like, before I've even opened my mouth, they're already there asking, like saying, You know, I've been thinking about this, or I reached out to this person. And that's pretty unique. That's like a really incredible feeling when it happens. Yeah, I was talking to, I think it was Reid Hoffman who was on this show who said, ideally it's someone where you invest in them with the—the bar is like if you could come back in five years without having talked to them after the investment, like, and you would be pretty sure it would be going well. Yes. That's a good question to ask yourself, you know? Yeah, yeah. Those types of companies, I mean, there's the founder, but then there's also—I know Reid, and I know that he is very oriented towards network effects. And that is, I mean, if you can find a business with a strong network effect, like... You're going to be in pretty good shape. Let's talk about network effects, because I think that it's one of those things. It's maybe a little less so because of AI stuff, but like for the last 10 years, I would say like 80% of decks that I saw were like, And we have a network effect. And I think there are probably very few businesses that truly have like that actual network effect pull. How do you differentiate? What does that really look and feel like? Yeah, in the early stages, it's, you know, there's a lot of companies that have potential network effects. And, you know, oftentimes there's a big gap between what's the theoretical, you know, and like where it really starts to happen. And one of the things that, you know, I often think about is just like there are early, you know, we invest so early that a lot of it is leaning in on the theoretical. But like there are often signs that you can look to. The best thing that you can sometimes see evidence of is just this idea of like a tipping point that starts to happen in a very small segment of the market, like where the white-hot center of your market is. You know, there's like two examples I think about, but they're outside of AI, like outside of core AI right now, because it isn't—I think what's happening right now with AI is that it's very much like a kind of, in a way, what has been traditionally the software business, which is just obsessing over a customer problem and moving faster in your execution than any of your competitors. But, um, you know, I'm on the board of a company called Agentio, which is a marketplace for, like, YouTube creators and brands. And you can see that, like, they—this has been a market that has eluded startups for a long time because most of them have kind of fallen into the quicksand of becoming an agency. Yeah. But with LLMs, Agentio is able to automate a lot of the things that have held this market back, and they're truly, like, having liquidity. And one of the early things that was super interesting is just, like, you see the—like, the brands see creators and they see the ads that they do for Agentio. And, like, so Agentio just has this demand-side pull right now. And it's super, super early, but there is enough signal there that, like, something's working that's differentiated, and there's no substitute for what they're doing that you hope will start to really be a flywheel that can spin faster and faster. So it seems like one of the best ways to differentiate between a real network effect and a fake one is, like, just early evidence. Yes. Are there any things, like, when you see a deck from a founder that hasn't—you know, they're just starting out—and you're like, and they say, We're going to have a network effect, and you're like, It's not going to be a network effect? Yeah. Yeah. I mean, it's often, like, they, you know, they'll articulate some kind of flywheel, you know, or it'll look like the Amazon or the Uber flywheels. And then as you—and either, like, it's just words on a slide that fit to a picture, but, like, you know what I mean? But, like, the words don't actually—they're not actually accelerants. Like, that's—I think that's one of the things, like, okay, yes, that whatever you say is true, but it doesn't really actually accelerate the flywheel. And the second thing is that often there's either a lot of friction embedded in any one—any leg of that flywheel, or there's, like, offshoots that happen. But I think the biggest thing is, like, when you really look at, like, what the articulations of the flywheel, that it is—it's words, but not accelerators. Yeah. To bring it back to AI for a second, I feel like one thing that you're articulating is there— is there is a moment in software for like 10 or 15 years where everyone was chasing network effects. And then the LLM wave happened, and a lot of that has been more single player, or if it's collaborative, it's like inviting teams or whatever, but you're not doing it together. And the game there has been better performance from more money and more compute and more data, basically, and everyone's just trying to keep up along that same sort of dimension of performance, more or less. There are a couple other examples that are not on that. But, and I think what you're maybe pointing to is that fairly soon, if not already, probably the models, the base models, are good enough for consumers that there's going to be another wave of more consumer-focused, more product genius-led AI applications that differentiate or grow from network effects and multiplayer that were not possible in the last couple years, but are newly about to be a thing. That is my great hope. I could be tilting at windmills. You know, like consumer, as you know, has been really, really hard over the last 10 years. And so it really could be tilting at windmills. I believe that that is an opportunity. And what I would also say is that there are going to be a lot of companies that emerge that aren't multiplayer, that are single player, and those could be really good. But I think that the really big opportunity that lets a company have a true network effect is going to be something that's multiplayer. If it didn't happen, why not? If it didn't happen, it would just be that the gravitational pull of the existing platforms is too strong. You and I, like, what would get us to go from the habit we already have of using ChatGPT and, of course, the ecosystem that's going to form around it over time, what they're able to charge for it versus, like, what a new company would have to charge for it. Like, maybe they eventually go free because there's an ad-supported, whatever it may be. Also, memory is a big sort of lock-in. Like, it knows who I am and all my experience. Well, yeah, because you and I, like, we already have, but we're not everybody, right? But there is that gravity that has always been true for the incumbent products. And so it could be that that gravity is just too strong to get the people who are, like, if you want this type of community to form, you're going to need somebody who is already actually a power user of ChatGPT to want to share that on another platform. And, you know, that's hard. That may be hard to create. I know this is a show about AI, but are you looking at or excited about anything that's not AI right now? I'm a big believer in stablecoins. Interesting. I would not have guessed. Okay. Yeah. I'm on the board of a company called Chainalysis, which is just, you know, so I've had a kind of seat in the crypto space and have been a long-term believer in Bitcoin and some of the other cryptocurrencies. But when I think about... Kind of the existing financial infrastructure. And, I mean, you know, we're filming this on a day when the, you know— What existing financial infrastructure? Yes, exactly. The U.S. dollar is on a little bit shakier ground than normal. But, you know, my mom's from Argentina, and I can tell you everybody in Argentina wants a U.S. dollar. Yeah. You know, and—but it's really hard to get them, and the government has all types of incentives to keep, you know, the hard currency that they have of U.S. dollars in their own bank, you know, because they have, you know, loans and everything else that they have to kind of stabilize their own economy. But then it holds Argentina and all these countries back from participating in the global economy, because the U.S. dollar is what you need to trade goods internationally. Like, it's just the easiest medium of exchange, but it's really hard to get U.S. dollars. Now, if you have a cryptocurrency that is a U.S. dollar stablecoin backed by a U.S. dollar, that opens up kind of a global economy, and it also—it is just so much faster. It's 24/7, a lot cheaper. You can do small— Why is it hard to get U.S. dollars in Argentina? Yeah. Well, it's been—Milei is obviously changing a lot of things, but there are different taxes around U.S. dollars. The, you know, there has been for a long time—this is different now—the exchange rate you get on the street, the exchange rate you get when you go to your bank, the exchange rate you get when you use your credit card. It's just like a very liquid market, really. Like, I remember going to Argentina and, like, having somebody on a motorcycle come to exchange money. You know, like, that's kind of what you would do. And then again, the U.S. government—I'm sorry, the Argentine government—they have U.S. dollars in their own central bank. And if I want to transact in U.S. dollars, I need to get some of that U.S. dollar from them. But that is a very precious resource to them. And so there's a lot of, like, process that you have to go through and time in order to get 10,000 U.S. dollars. It's not an easy thing to do. And so it's just, there's a lot of friction. Whenever there's a lot of friction, if somebody else can come in with a new product that removes that friction and then also just has the facilitation, like just how much easier it is for you and I to do a peer-to-peer transaction with Tether or USDC, that creates a lot of liquidity in a market that I think can be a very interesting future. And also, I should say, it's like if you're in Argentina and you want to buy something from India, like, you know, the number—all the middlemen that you have to go through in order to do that transaction versus, and like all the fees along the way versus a peer-to-peer transaction on a U.S. dollar stablecoin is a different game. And this is another network effect-y type business to you, or no? There are network effects here because, you know, Tether, as an example, which is like the dominant stablecoin right now, just has more liquidity on all the exchanges. And so it's a lot easier to go in and out of Tether than, you know, other stablecoins. But USDC is pretty strong too. So there's definitely some network effects there. It's just easier if everybody—it's not even just within the exchange. But just you, like in these countries, in Nigeria and any high inflationary country right now where people have wanted to go from their fiat currency into a U.S. dollar, you have a wallet and it has Tether and you have Tether, and it just becomes, like, more comfortable for us to all use it. And then all the ecosystem around, like there's so many crypto wallets and different, you know, kind of new financial apps that are for getting your paycheck, but then also you can have your money in a U.S. dollar stablecoin. And if you're already integrated with Tether or you're using Bridge to access Tether, it just makes it a lot easier for people to get comfortable with one of them. How do you think about, let's say five years from now, how AI will have changed your day-to-day as a VC and the kinds of businesses and the kinds of funding models? Will it have in any way changed the VC business model? I have been wondering about this lately. You know, one thing I've just been thinking about, and this is a little bit of a step back, but, like, there are some people that are really good at creating training data. Do you know what I mean? Like, there's some people, like someone was showing me—I interviewed him, James, for my Substack—and he showed me, like, this spreadsheet he creates of all the movies he's ever watched and his own review of it. Yeah, yeah. Right? And so, I don't know about you, I've never done that, but the people who are really good at creating training data can then... have a more personalized, more valuable experience with an LLM. And so to your question, like one of the things that I've been thinking about is that there's a few things that we all have training data for. One is, you know, past decisions we've made and whether or not those were good decisions. So like I personally, I—so Annie Duke inspired this. I create—she wrote this book, Thinking in Bets—a premortem. So every time I meet with a company and I dig in on it a little bit, I write to myself what I liked, what I didn't like, what the deal would have been, and if I got yes, why; if I got to no, why. And so it follows that over time, I'm going to be able to look back on that list and examine my decision-making process, right? And then as I dig in on future companies, like in my brain, I know that there's one example where I passed on a company because the valuation was too high, and that was a lesson to me. The company ended up being a real success, this company, Verkada. And so that ended up being a lesson to me, like if I like everything but the valuation, I should probably lean in. I remember that, but there's so many other examples in my thinking that if I can, like, examine my thinking as I meet a company and have it cross-examine me, that I think I'll get to a better decision. Then there's also things like talent. Like what is one of the best things that we do on behalf of our companies? It's help them make sure that they have the best team around them, right? And the same thing, like we're all fallible in our evaluation processes and what's, you know, a record of those decisions, interviews we did, like all those things, I've got to imagine that's going to come into play. And then the third is just— You know, I know there's some companies that are doing this really well, which is just tracking talent globally and the movements of talent and what that ends up meaning. And it follows that there should be, at some point, a score almost where, you know, from the angel investors that have invested in a company, the talent that's there, their individual scores of their ability or signal when they choose a company, that there will be like a Rotten Tomatoes almost score for companies that can surface opportunities. Interesting. I want to go back to the decision-making thing because I'm with you. Like, I record all this stuff. I record all my meetings, and like there's just like a lot of stuff I think that you can do with AI and improving your decision-making. And I'm curious in VC in particular, like how that works or how you avoid, you know, for example, maybe you invest—I've done this—you invest in a founder with a highly technical background, but it's in a field that requires more of a product genius. And then, you know, now you have in your LLM, it's like, well, beware that, like, you know. And then, you know, the next time you meet with a founder and it's like, you know, Sam Altman and Greg Brockman in 2016 or whatever, like that thing is going to ding and be like, technical founder, like, are you sure this is what you want to do? Like, it depends on how the rule or how the lesson is written. Yeah. And I think the broader question or problem is— If you look at venture capital, there are very few venture capital firms, funds, and individuals who are successful over a long period of time. It's very hard, which can tell you one of two things. Either it's just luck, which I don't think so, or the landscape changes so frequently that you get tuned, your taste gets tuned to a particular kind of opportunity that you're very good at finding, but then it sort of moves and changes, changes in what is good also changes. And all of that means it's, like, quite hard to use past training data to make future decisions. How do you think about that? I think maybe that's what we're all hoping will give us job security in the future. You know, I remember when I was at Pinterest and I was responsible for all the discovery experiences, and very early on, I had to kind of localize Pinterest. And so I had to figure out, like, okay, Pinterest is in the United States. Now what's Pinterest in Brazil or Japan or all these countries? And I was, like, thinking about the categories and all as being different. I remember Ben saying to me, he's like, Just assume it's going to be more similar than different. And I think that there's some, you know, first principles that we reduce down to when you're making a decision, like Jim Collins, like so much of what he wrote, like, I don't know how long ago, is still valid today, like, you know, Built to Last. Like, we talk about so many of these things, and they're timeless. Like, valuations change. Well, how companies exit change, yes, and that's why, like, you're not asking the LLM to give you the answer, yes or no. You're asking it to probe your thinking. But I think it should be able to continue to do that. And that's why we still have hopefully a job a few years from now of ultimately being the decider. Well, you'll have to come back on the show in five years, and we'll see how things have changed. I think you'll still have a job. I hope so. But it might, I think it might be different too. It's going to be very different. Yeah, it's going to be very different, and it's hard to anticipate how it will be. Yeah. Well, Sarah, thank you so much for coming. This was a great conversation. Thanks for having me. Yeah, yeah, I had a lot of fun. Oh my gosh, folks, you absolutely positively have to smash that like button and subscribe to AI and I. Why? Because this show is the epitome of awesomeness. It's like finding a treasure chest in your backyard, but instead of gold, it's filled with pure, unadulterated knowledge bombs about ChatGPT. Every episode is a roller coaster of emotions, insights, and laughter that will leave you on the edge of your seat, craving for more. It's not just a show; it's a journey into the future with Dan Shipper as the captain of the spaceship. So do yourself a favor, hit like, smash subscribe, and strap in for the ride of your life. And now, without any further ado, let me just say, Dan, I'm absolutely hopelessly in love with you.