What if the AI giants are building the roads, not the destinations? Chi-Hua Chien thinks he knows who wins

Speaker A: This week, our guest is Chee Hua Chen. Chee Hua has spent more than two decades inside Silicon Valley's biggest bets, beginning his career as a young associate at Excel in the mid-2000s, where he was an early champion of the firm's investment in a scrappy startup called Facebook. He went on to a partnership at Kleiner Perkins before co founding Goodwater Capital, a firm built entirely around consumer and prosumer technology, a focus that has made Goodwater an outlier in a venture landscape increasingly obsessed with AI infrastructure. In this conversation, Chihuahua, uh, argues that the real opportunity in AI won't be captured by the infrastructure giants building models and chips, but by the application layer built on top of them, just as it played out in the PC, web and mobile eras. He digs into why valuations are spiking so quickly, what's driving the new wave of hyper personalization entertainment in healthcare startups, why incumbents are now faster copycats than ever before, and why after years of digital only living, he sees a swing back toward real world in person experiences as one of the biggest opportunities in consumer tech. We really enjoyed talking to him. We hope you will enjoy the conversation and we'll see you back here next week. Well, Chiwa, so nice to talk to you. I just wanted to start off with something that's in the news. Well, two things actually. One, what do you make of the VCs going after each other on social media? Not just VCs, but founders going after VC. So I guess, you know the VC versus VC has been happening in recent years. You've got Khosla, uh, fighting with Mark Andreessen, but I haven't seen founders come out in full force against VCs, are talking about their horror stories. And I was a little bit like, oh, what's changed out there? Just curious what your thoughts were.

Speaker B: Well, I think it's part of the memeification of everything, right? You're seeing what's happening in the political realm bleeding over into the business side. And it's probably also the sign of some peakiness in the market. Back in the 90s there was a website called Efft Company where you could log on as an entrepreneur and give your feedback on specific investors by name, by firm, specific anecdotes. This type of thing happens every now and again and probably in the venture community. The reason that you're seeing some of these outspoken investors talking more publicly is because venture firms have largely vertically integrated, so the really big ones have enough capital that they're not necessarily looking for syndicate partners. They are investing in companies early and then adding more and more capital in later rounds from their own funds. So there used to be decorum or a tradition around wanting to preserve good relationships with other co investors because you got to work with them as syndicate partners at different points along the line. As the firms have gotten bigger and vertically integrated, there's less of that need.

Speaker A: Okay. Speaking of these firms that are vertically integrated, um, the other mini saga that just bubbled up over the weekend was the CEO of Mercour, Bren and Foody underscoring that firms, and he called out Sequoia Capital specifically for doing this, are becoming more comfortable with fast follow rounds, which means they invest a chunk of money at a particular valuation and a smaller amount at a higher valuation, surrounded potentially by co investors. And the higher valuation becomes sort of the headline valuation that everybody hears about, even though really the bulk of the money was raised at a much lower valuation. It's not, uh, I also don't really know how new this is or if outsiders have just sort of caught on to this a little bit more, but again, wondering what your thoughts are.

Speaker B: Yeah, I think it's been going on for quite some time. It's a maybe sharper illustration of the fact that the best companies raise successive rounds, uh, very quickly now. It used to be there's a year and a half to two years between rounds now there might only be three or six months between rounds, and the valuations change really quickly. So you go from three or six months between rounds to three or six days between rounds, and everything's getting compressed. It is also a function of the fact that valuations are being marketed very aggressively now as a way of demonstrating market leadership, attracting talent, potentially blocking out competition. All of those things are important in a highly competitive environment where these companies are growing very quickly. And so, you know, the companies that are raising capital the fastest are using their valuation as a way to signal early market leadership.

Speaker A: I understand that completely. What do you make of, uh, the valuations, though, jumping so significantly? To your point, three to six days is maybe an extreme example, but I have seen this in at least two examples that jump to mind within weeks where the valuation has doubled, which of course seems crazy to me. And while I understand the strategy, I just wonder if companies are backing themselves into a corner or you think something has fundamentally changed here that could actually rationalize these valuation bumps?

Speaker B: I think both could be true. I think something has fundamentally changed in this market. Relative to my experience set over the last couple of decades, I've been doing this job since 2002. So for 24 years. And the rate at which these companies are growing, revenue, gross profit, in many cases, actual bottom line profitability is unprecedented on any dimension. It used to be in tech. If you could get to 250 to $400,000 of revenue per customer, that would be pretty good during the stages of venture financing. And 2 million, um, sorry, of revenue per employee and 2 million of revenue per employee would be considered elite. That's like kind of Google, Facebook, Apple land. Nowadays you're getting companies doing 10, 15, $20 million of revenue per employee, which even 10 years ago or even five years ago that would have been unimaginable. So that certainly is a fundamental shift in that these companies are able to grow top line and in many cases bottom line at an unprecedented rate. That having been said, there's probably some element of frothiness here in the market with these financings happening so quickly. Because what they are most illustrative of is there's way more demand in these financings than there is supply. So an investor can come in, set a price, complete a uh, financing and then a couple of weeks later there's still excess demand in the market to invest in that company and the company can immediately price a new round at a higher price.

Speaker C: You mentioned the unprecedented revenue levels, but isn't it also true that many of these companies are giving it away and subsidizing tokens and on the back end investing so much in infrastructure that it's become uh, all out race to get to the public markets to finance these huge expenditures?

Speaker B: Yeah, I think there's two types of companies or AI companies in the market right now. One type of company is the one that you're referring to, which is fundamentally selling AI as a value proposition. Those companies are effectively repackaging compute with a specific application bundled around it. And those companies do need a huge amount of capital. The margin structures are not attractive. There's a lot of capex involved in building those companies and they need access to capital in order to grow. There's a second type of company that is not selling AI as a fundamental value proposition, but is selling an application. It might be E commerce, it might be financial services, it might be healthcare. They're selling value to customers and using AI as a way to deliver that value. And I think those two are very, very different because in that second category, what we're seeing really interestingly is 85, 90, 95% gross margins for some of these companies. Very cash generative, but the top line is growing very quickly. And those companies actually don't need access to capital. They're raising capital opportun.

Speaker A: So tell us what you are backing and how you're approaching this whole thing.

Speaker B: Yeah, so we've been looking really hard at that second category. We don't do a lot of infrastructure Investing. Goodwater is 100% consumer tech and prosumer tech focused. And what we're seeing now is a raft of applications that are growing really quickly in core categories that over time, 100 million people, a billion people on the planet will use. This is housing, healthcare, food, financial services, transportation, education, education, entertainment. And what's interesting about these companies is that they can grow really, really quickly. I can think of several entertainment companies in our portfolio, companies like Triumph and Ritten and Flow GPT, that the customer's not looking at this, saying this is an AI application, they're looking at it and they're saying it's an entertainment application. These companies are growing to 100 million, 400 million, 600 million of ARR very, very quickly. And they're doing so at great margins because AI is a part of how the application is delivered and it makes it more customizable and more personalized. But it's not the fundamental capability that they're selling. They're not just rebundling inference and selling it to the customer.

Speaker A: What are these conversations like with these companies? Because you are perhaps focused on areas that are a little bit less frothy. Maybe it's not so impossible to come up with terms that you're comfortable with at the outset. But I am kind of curious about how these things get negotiated when these companies are growing as quickly as they are.

Speaker B: Yeah, you know, the market is remarkably efficient. Over time, companies with good fundamentals will be valued highly. At this particular point in time, though, there is a mania around AI and AI infrastructure. So you see huge amounts of capital just flowing into the market around infrastructure. One of the things we did, Connie, is we went back and we looked at over time what has really been the pattern of how these companies are built across various different cycles. And what's really interesting is if you look at the PC cycle, the web cycle and the mobile cycle, they all follow fairly consistent patterns about the mix between infrastructure value creation and application value creation. What's pretty crazy is if you look at the PC cycle and the web cycle, infrastructure market caps actually peaked in the year 2000 with 85% or uh, 90% of the market cap concentrated in infrastructure companies. But you fast forward 25, 26 years later, and in nominal terms in dollar terms, the market cap of infrastructure companies has not surpassed the 2000 peak. Even in 2025, 2026, the total combined market caps of these companies, 2000 peaks. What has grown really quickly is the application side. So application companies from 2000 have grown and produced an enormous amount of value. And they didn't peak early because you have to have that, uh, infrastructure layer there in order for applications to get built. But once the infrastructure layer is built, then application companies can come in and they can build the various different products and services that real customers, humans all around the world are going to use on a regular basis. Right? This was true for PC, for Web, for mobile, and I think it's going to be true also for the AI era. Let me throw a few numbers and some data at you. In the Web era, new entrants, meaning companies that were started during the Web era in the infrastructure market, produced $400 billion of new market cap. Application companies that were started during the web era created $3.1 trillion of market cap. So 88% of the new value that was created in the web era went to application companies, not infrastructure companies. In the mobile era, it's very similar. Infrastructure companies started during the mobile era produced about $700 billion of net new market cap, while application companies produced $3.7 trillion of market cap. So 85% of the new market cap created during the mobile era went to application companies. This is companies like Netflix and Spotify and Facebook or Meta, Uber, Airbnb, these companies. So we think a similar pattern is starting to play out here, where arguably the 2025, 2026 year is going to be the peak of the infrastructure value creation. And then you fast forward over the next five or 10 years, a lot of that value is going to shift into application companies.

Speaker A: So the most obvious question is, what does this mean for these companies that are going public right now at these unprecedented valuations, these infrastructure companies that are also vertically integrated and increasingly offering applications?

Speaker B: Well, I think you can hearken back to each of those eras, right? If you look, for example, in the web era, uh, the infrastructure companies were Microsoft, Cisco, Oracle, Northern Telecom, Lucent, Verizon, Verisign, Akamai, Equinix. Those are the top 10 names. Eight of the top 10 names during that period of time. A lot of those companies survived for a period of time, but aren't worth a lot today. And they're good businesses there. Don't get me wrong, there's some very good businesses there, but they're businesses that are in the picks and shovels. Infrastructure, part of the technology value chain. And what we know about that part of technology is over time, it gets commoditized. It gets commoditized very aggressively because the end customer doesn't think to themselves, ooh, are my bits moving on Cisco networking equipment? They're just thinking, how do I move my bits as cheaply as possible, Right? And so my prediction for a lot of these infrastructure companies is that you might see modest appreciation in the public markets. And when I say infrastructure companies, I mean, you know, an OpenAI or an Anthropic or some of the other ones, in particular the backend components, energy chips, hosting. There will be a period of time when these companies are valuable, but over time you will see them get increasingly commoditized. And I think this week you saw some something pretty interesting in the news. Google announced that their Google product, their subscription AI product, is dropping price from 7,99amonth to 499amonth and is doubling the amount of storage that they're offering. So we're already, this is, you know, direct competitor with ChatGPT, right? You're already seeing the era of price competition upon us now, where companies like Google that have pretty substantial structural advantages in vertical integration and distribution can start bundling and price competing for the average consumer. Like imagine you are the average American. Or in the case of global users, many of the biggest audiences in AI are in emerging economies like India. For someone to decide between their local equivalent of a $7.99 a month product versus a $499 a month product, that's a pretty substantial decision for them financially. And it has pretty significant implications on how much demand there is going to be in the market when you drop price by that amount.

Speaker C: I understand your analogy to companies during the web era, but it does seem like the definitions have melded quite a bit. You may call a company like OpenAI an infrastructure company, but it also is verging into the application layer. And in fact, Anthropic caused some, um, concern for companies like Harvey when it launched a bunch of products for the legal arena. Meta is another example. They're investing hundreds of billions of dollars into infrastructure. So at, uh, what point is a company in this era an application company? And at what point is it an infrastructure, uh, company?

Speaker B: Yeah, absolutely. I think you're totally right. The strategic objective of every platform company that starts at the infrastructure layer is to become an application company, because that's part of how they're going to defend their market position, because they know this Commoditization is coming. In the PC era, Microsoft was the platform company and they built applications. In the web era, Google arguably was the platform company and then they built applications. In the social era, Facebook was the infrastructure company with the social graph, they built applications. And then in the mobile era, Apple with the iPhone was really providing a lot of the infrastructure and they built their own applications as well. This is not to say, by the way, that none of those companies are going to have successful and valuable application businesses. Microsoft Office is a valuable application. Google's suite of productivity applications as well as Maps and Gmail, et cetera, are valuable and you know, as are Facebook's apps and Apple's apps. I think the question is where the net new innovation is going to come come from. And those I would argue are going to be new application companies that are built specifically around customer experiences that look very different from the existing interface. In the case of AI, right now we're in the command line era of computing as it relates to AI, It's a text based interface. You largely interact with the product through text and mostly the value is provided back to you through text. There will be many, many more customer experiences built that are very specific to the use cases that customers have. And those are likely, in my opinion, to be built by new companies. At every point in the innovation cycle someone said the equivalent of oh, Microsoft's going to win it all or Google's going to win it all or Facebook's going to win it all or Apple's going to win it all. Right, that would be the equivalent of saying OpenAI or anthropic is going to win it all at this point in time. But I think history shows that platform will always have challenges attracting the next great generation of talent who wants to build something net new because their alternative is to build something on their own versus to go be part of a large company that might have a set of constraints that they don't have if they're entrepreneurs on their own.

Speaker A: Obviously Uber and some other applications that were built on mobile, we couldn't really conceive of them until they existed. Are you investing in next gen type companies that are building AI fueled applications or are you seeing completely novel behaviors and services?

Speaker B: We are. And I think that's what is particularly exciting is we're starting to see the equivalent of uh, the Uber, The DoorDash, the WhatsApp getting created now for AI, right. None of those three companies were possible with the web and PC era. You could conceive of them, but you fundamentally needed Real time mobile computing for any of those three use cases to emerge. Well the same thing is now starting to happen and I think a good example of this is a company we backed in Korea called Written. It is a entertainment product that enables you to interact with a virtual world, kind of like webtoons style virtual world, but it's intensely personalized. There's an extremely high degree of personalization so that every single person's entertainment experience is unique to them and their interests. This before was impossible. You know people would build entertainment experiences in games. But you go to YouTube, if I watch a video and you watch a video it's going to be the same video. You go to play a video game largely within the levels, it's going to be a similar type of experience with very little variance between my experience and yours. These new entertainment experiences and oftentimes uh, technology is first. The new capabilities of technology is first evidenced through entertainment experiences because they're very flexible. So in these entertainment experiences you can dive in and you can be a 1850s Civil War participant, you can be a ah, 1200s Japanese Shogun participant. You go into a fantasy or a sci fi world that hasn't existed before. And your trajectory in that experience and mine are going to be completely different and personalized. We're starting to see that more and more and more in a way that you could not have delivered cost effectively or with very high customer value and customer satisfaction. Before AI enablement, AI infrastructure and compute models were there.

Speaker C: I guess one trade off is you have to give up a certain amount of privacy in order to have that personalization.

Speaker B: Yeah, well don't think of it as privacy meaning it's not going in and downloading your bank account statements and all your chat messages in imessage and things like that. It's much more the gameplay or the dialogue. If you are interested in pretending you're an astronaut, you go through a dialogue of what that would look like.

Speaker A: So is it personalization sort of the through line of everything that you're doing?

Speaker B: Yeah, I think hyper personalization definitely is a key through line because what does personalization give you if done right? It gives you higher customer satisfaction, deeper engagement and higher arpus over time. Right. The average revenue per user is going to go up. Another area that's really interesting is you're starting to actually be able to see examples where the quality of uh, product that's being delivered is better on an individualized basis because AI makes it possible. We have a women's health company called MIDI Health and in that particular case. One of the fundamental constraints in women's health is that there aren't that many providers that are actually well trained and knowledgeable about hormone replacement therapy for premenopausal women. The underlying reason is there was some research that turned out to be incorrect about 20 years ago that caused the core medical establishment to pivot away from training people in this particular type of medical care. So there's actually a supply constraint with doctors and nurses who know how to do it. By using AI, they're able to substantially expand the supply, meaning the ability to provide care and treat hundreds of thousands of patients that otherwise could not get treated by the existing healthcare system. And they're able to do it at reasonable profit margins. That's the hard thing. The really hard thing is if you have a ton of humans involved in doing something, yes, you can provide high quality of care, but it becomes extremely cost inefficient and as a result you can't build a good business, you can't attract financing. All those problems with AI. And in the case of MIDI health, they're able to do it, provide extremely high care in a personalized way, in a clinically accurate, with great outcomes, and they can do it cost effectively, which expands access to the market which previously had been supply constrained. So you can actually play that forward and you can imagine how in every general purpose health category where historically it's taken you two, three, four, five weeks to get a doctor's appointment, that doctor might only have 10, 12 minutes with you in the clinic and they have to move on quickly to the next patient. Any supply constrained category where human expertise is the bottleneck to delivering a lot of value to customers, that is another vector where AI unlocks massive market opportunities. They're using AI to make the well trained, certified humans, licensed humans, much more efficient. But you still have the human in the loop. You're ensuring that the human is ultimately responsible for delivering the care. But a lot of the administrative tasks, a lot of the repetitive tasks, a lot of the background, maybe non customer facing tasks that take up a lot of time for these highly trained humans, that ends up becoming much more efficient because you can train AI to do those repetitive tasks very efficiently.

Speaker A: I think MIDI is such an interesting smart bet. It's shocking how big the market is. There's 1.1 million women who are either pre or postmenopausal in the world right now, which is something that I just discovered yesterday while I was editing a story on the greater tension that Apple is paying to that population. I'd like to understand as well what you're doing in transportation.

Speaker B: Yeah, transportation, we haven't yet seen much. I think there was a nice run of innovation with Uber and ride sharing. There was a false start with scooters and micromobility and transportation. At this point in time, I think the big story is an area where we are not direct investors, but the big story is around the autonomous vehicles. What's happening with Waymo, what's happening with uh, Robotaxi from Tesla, and what's happening with the companies in China that are actually building fairly advanced self driving hardware. I don't know if you guys have a Tesla, but I have a Tesla Model Y that's become my daily driver. So long as you obey the rules like, you know, you keep your face forward and you're not looking at your phone or trying to, trying to watch Netflix or something, it will take you from point A to point B in nearly every scenario except for construction zones or some highly complex situation. My guess is that ultimately once that is unlocked, you're going to see a lot of secondary and tertiary innovation around applications for what people can do in the car. Groq in the Tesla is a initial illustration of what becomes possible, but I think there's going to be a whole lot of downstream opportunities as well.

Speaker A: Speaking of voice interfaces, I feel like what comes up sometimes when we're talking to investors about this is whether or not we're going to be using phones in five or 10 years. I'm wondering what your thoughts are about that and if hardware is something that you're willing to or have bet on.

Speaker B: Um, we haven't yet bet on hardware, but it's becoming more and more interesting to us. Historically, hardware required very deep technical expertise to understand supply chains. Manufacturing in China, you know, returns inventory and the like. But the supply chain in Shenzhen has gotten to the point where it's really efficient. You can get prototypes made. There is an entire ecosystem there that can enable pretty simple devices. So I think what's going to happen, and we talked about this Connie, a little bit at the event that we did together, what's going to happen is that the phone is going to become much more of a consumption device and input is going to start to become voice based or passive vision based. The interesting thing about LLMs relative to computers is computers required you to have correct syntax and to be as efficient as possible with your commands. So if you go back to the command line interface, you needed to type very specifically the command with the right directory in order for it to Work. And then with the gui, you had to point the mouse at the exact right place to click on it and then it would enact a particular type of action. Well, what's interesting about LLMs now is you can kind of muse to Gemini or Claude or give it some ideas, hey, work on this thing. But I'm not sure about this. And then there's all this other idea I have and go work on it and come back to me. So I think what that points to is it points to the fact that there's a step function change in the amount of context that you can give your computer. And so if you think about the phone, the phone right now is designed for very discrete inputs. You have your finger and you have your keyboard. Those are fairly discrete inputs that are the equivalent of a concrete set of commands that you can give the computing device. Well, what happens when you have a passive information consumption device that you can be talking to all the time through a voice and audio interface and it's just consuming that information, making it useful for you, building context around it. Also, what happens if you have passive information collection through a visual device, your glasses or otherwise, that's actually taking in all of the information around you and starting to organize it and make it useful? I think at that point the phone becomes a consumption device because it has a screen, but the inputs actually get separated from the phone. And that, I think, is going to unlock a whole bunch of new opportunities as well.

Speaker C: It sounds a little bit like what you're describing is sort, uh, of a personal agent that is always on and looking for opportunities to engage. I'm just wondering how far away do you think we are from a world in which people are creating new software, new agents, just through, you know, musing with their phone?

Speaker B: I don't think we're very far away at all. All of the technical capabilities are there. You can run locally now on your phone or computer. AI models that are as good as the best AI models were about six months ago. And that delay, that lag is actually shrinking. You go back two years ago, the lag might have been 18 months, 24 months between what you can run locally or open source and what was in the cloud. With the frontier models, it's now six months. It's probably getting down to three months by this time next year. So a lot of the capabilities, the technical capabilities are there. What we don't yet have, we don't yet have the use cases very well defined. And you saw this, by the way, in mobile as well, right? When the iPhone launched in 2007, people largely thought that it was going to be all of the web applications ported over initially to mobile web interfaces, and then one year later with the launch of the App Store apps, right? Oh, you can have Yelp. Remember Steve Jobs did the demo of Yelp on the phone and email on the phone and the browser on the phone, right. Those were like a bunch of the big demos. It takes time for entrepreneurs and the overall startup ecosystem to percolate around what is now possible. When there's a new technology, and in this case the new technology, if you extrapolate away from how it works into what it does, is it basically does two things. One, it makes it possible for you to process large amounts of context and make sense of it all. And then two, it allows you to do personalization down to the individual and to do it cost effectively with a feedback loop that actually will be self reinforcing and make the product better and better for humans. So for example, for a long time people have worked on this idea of the pfm, the personal financial manager, right? Quicken did this, Mint did this, There's a bunch of others around. But what it required, all of those things required some variation around inputting of a lot of information on the part of the consumer. I remember in the early 2000s, you know, my wife and I would sit down at the end of every week and we would input all of our transactions manually, look at the receipts for the week and figure out where we'd spent money, you know, and then reconcile to our bank accounts and all that stuff that's gotten easier and easier with connectors like plaid. But it hasn't yet become truly dynamic where all of it is happening in real time. And the coaching around personal finance is coming back in real time, right? There is no product right now that really understands each of the customers on an individual level and caters the advice and the specific user interface and interaction based upon your stage of life and your goals. I think we're gonna see those types of products come out here in the next couple of years. Cause entrepreneurs now recognize what's possible.

Speaker A: You're always curious to know if the incumbents, which in some cases are not that old, but maybe 5 or 10 years old, are gonna win those markets or we're gonna see a spate of complete new upstarts.

Speaker B: The incumbents now are stronger and faster to enter these markets than ever before. It used to be like, you saw this a lot in China, where the big Chinese companies would very quickly copy and effectively commoditize any new startup innovation. So it sort of consolidated around the four or five big guys in America. That was not the case because American companies had a little bit of a high minded view towards innovation. They didn't want to copy directly, they wanted to innovate on their own or they tended to get stuck in their single product mindset which really limited their ability to innovate and enter adjacent markets. Now that's no longer the case. Amazon, Apple, Meta, Google, all these guys are innovating pretty aggressively. You see how quickly ChatGPT and its capabilities are getting commoditized really by incumbents, not only by other new entrants and startups. That having been said, I think the flip side of it is also true, which is the market opportunities now are way larger than in previous cycles. So the incumbents will suck up some of the market opportunity because they're moving quickly. At the same time, I think there are so many more market opportunities available and there's going to be a lot of room for new entrants to go after those.

Speaker A: So interesting, you have a global portfolio. You're mentioning this very interesting company that I want to learn more about. Ritan. What trends are you seeing, if any emerging outside of the United States that are not here yet?

Speaker B: So fintech innovation in the US is basically done, but there's actually a lot more fintech innovation happening outside the U.S. than inside the U.S. and so in Asia you see a really rapid rate of fintech innovation. We have a company in Korea called Toss that is a very large business, over 2 billion in revenue, $10 billion market cap, private valuation. And they're building a financial supermarket and a super app that is distinctly Asian. You don't get these financial services super apps here, but you see them in Asia. In Europe we've got a company called Monzo that is building a proper digital bank, over 2 billion in revenue, growing very quickly, profitable. They're now at 25% of the entire UK adult population, has a Monzo account and they're adding 7 to 8% of the UK adult population every single year. So you can imagine as they continue to grow, how important of a company they're going to become.

Speaker C: You know you mentioned super apps and you have had a very long connection to Facebook. Connie probably knows this. I didn't know this about you, that you possibly originated Excel's investment in Facebook.

Speaker B: Yeah, yeah. I was um, a 27 year old associate working at Excel when in the basement of Stanford Business School I found this little company that had six employees

Speaker C: called the Facebook, have they ever come close to realizing a vision of a super app?

Speaker B: Yeah, that has always been a part of their ambition, going all the way back to the mid 2000s. And I'm not sure honestly what it is. I do think people have a particular opinion that is intuitive, probably not stated, but an intuitive perspective on trust. And there is a trust gap between entertainment and social products and commerce, banking, financial services products in particular in the western world. I think it's very hard to blend the two of those because in the customer's mind there is a seriousness to financial transactions, financial data control of your financial capabilities like bill pay and credit card and the like. That is very different from the triviality of social media and social networking. Now the triviality, don't get me wrong, has created a trillion plus dollar company, right? But the way they've created it is by audience. Lots and lots and lots of consumption and engagement in their audience. Financial services, if you think about it, is actually the complete inverse of that. While audience has very high time and relatively low monetization, financial services transactions are very high monetization and relatively low time. You don't want to hang out in your banking app. It's not like you're in there spending hours a day, you know, like enjoying your financial services. You want to transact and be done, but you want to have extremely high confidence in the security and the reliability of that transaction capability. I think that psychological expectation from customers is a very tough one to bridge. You know.

Speaker A: One, uh, last question. Speaking of social media and I guess honestly, you know how isolating it turns out it really is. I don't know if Silicon Valley is making bets on people coming back together in person. Every once in a while I see a consumer bet like Andy Dunn's newest company, Bryn Putnam of Board is trying to bring people together around an actual board game interface. Is that something that's interesting to you or that you're tracking or interested in funding?

Speaker B: Yes, we really, really, really believe in this. So my old partner at Kleiner, Bill Joy, who is the founder of Sun Microsystems and one of the co creators of Java, he had this belief that I think over time has really played out that technology and consumer behavior basically swings as pendulums. So you start in the early days of the Internet with something like AltaVista, that's algorithmic because the Internet was really, really small and not very complicated. But then you swung to something hand coded in ontology like Yahoo, because you had to organize the Internet into categories that really only humans could understand. But then as the Internet got bigger, you swung to algorithmic like Google, because Google was able to manage that quantity of information. But then the information became overwhelming so you swung to social, which enabled information again to be organized or transmitted through humans. I think the same thing is happening in terms of customer behavior around online versus offline. So we went through a really big swing to pure online. Right? You think about the rise of Facebook and Snap and Instagram and TikTok. Those really are fundamentally an individual concern. Consuming the digital publication of many other individuals but not interacting with them at all in the physical world. I think we're swinging in the other direction. So we've got an investment. Really fantastic founders. They were the original founders of Zenly, which was acquired by Snap, uh, back in the day and then rolled into snapmaps. They've started a new company called Ammo and the product is called Bump. And the under 30 demographic, what you'll find that's really interesting about them. We did some customer research on this, uh, not too long ago if you look at my Find My on my iPhone, I might share my location with like four or six people, 30 and under, call it 20 to 30 year olds. They'll share their location in find my with 30, 40, 50 people, which to me is like crazy that you would share with that many people. But that has been a hack for them to be able to find their friends in the physical world. Bump is streamlining that and making it super fun, really easy to use great functionality around it. Like even they have this one piece of functionality. This sounds trivial, but it's actually immensely valuable On Find My. If you're going skiing and you pull up where your friends are on the ski slopes, you have no idea where they are because there's no lifts, no run names, no information. It's just a blue dot and then their face, right? And they could be on any run, you have no idea. Bump has coded all of the ski runs and lifts and it's real time. So you pull it up and you know exactly where are my friends, or in my case my kids. I ski with my kids a lot. Which lift do I meet them on? And I can ski over there and I can find them, right? So that metadata getting built more and more and more into the physical world and an interface that allows people to interact in the physical world catalyze by digital prompts or digital information. That's an area that to me is super interesting. We have another company, uh, based in London and Madrid called Fever. It's the live nation of Europe basically doing live events everywhere. And it's incredible. They started doing these, like, small events that were kind of like, um, you know, quirky, not big name things. Things like candlelight concerts you've probably seen on Instagram. They hosted these events partnered with Netflix like Bridgerton Experience or the Stranger Things. They've now become a mainstream player because what do people want in the world where you have unlimited digital content, which you already had with Instagram and TikTok, but in the world of AI, it's 100x, 1000x because there's AI that can create infinite amounts of near perfect looking content. What do people crave in a world where there's an infinite supply of digital content? They crave the thing that is most constrained, which is real human content, real world experiences. So I think that's a big investment area for us. We have several investments there and we continue to make them.

Speaker A: Oh, great. Well, I'll have to look into Bump and TO Fever, but those sound really interesting and I couldn't agree more. It feels to me like that's the direction people are moving in, especially as we're looking for reasons to get out into the world and see other humans.

Speaker B: Oh, for sure.

Speaker A: Chihuahua. So fun talking to you.

Speaker B: Thank you.

Speaker A: I hope that it's not too long before we catch up again and I really appreciate the time.

Speaker B: Yeah, let's do it again soon. Thank you for the opportunity and it's great to speak with you both.

Speaker A: Equity is produced by Teresa Loconsolo with editing by Kel. We'd also like to thank TechCrunch's audience development team. Thank you so much for listening and we'll talk to you next time.