The Exchanges

Q What is the right way of thinking about it?

A Yeah. So the first thing I'd recommend if, uh, you're getting an assistant, uh, is to have them help you save money. Uh, if you have a big budget, not a big deal, but the first project can be, Hey, help. Pay for your salary by looking through all my subscriptions, finding things to say, uh, save me money, find me refunds. Um, so that's just kind of like a cost-saving bucket. Um, then there's admin paying bills. Um, and then there's coordination, which is what you're talking about, basically being a PM. So coordinating, you know, the tax attorney asks for something from the accountant, and there's a bunch of docs, and it's just moving paperwork between, uh, systems, um, at enough scale and complexity that becomes effectively a full-time job. And, Obviously, you need someone you truly trust, uh, to go deep with, and we kind of recommend that you build this trust over time, and, you know, you give email and calendar access at first and bank account later, uh, but as you earn that trust, then the more access you give effectively, the more leverage you get.

AI assessment note: “the first thing I'd recommend if, uh, you're getting an assistant”

Q Alex, why don't you give the perspective from the, from the growth team in terms of there's been a lot of players in this space over time. What got you excited about, about this space and why this team?

A Yeah. I mean, as you think about the space, a lot of it ties with what Mena just said, right? So our partner, Mark, every year, like clockwork, he sends out this updated chart and it shows consumer goods and services over time. And if you look at housing and healthcare, as Mena just said, like prices just go up, up, up to the right and any industry that technology has touched has gone down. So you can see that in computers. TV is video games. And we, we keep asking ourselves like, why hasn't software eaten this industry? Why hasn't software touched housing and healthcare? And right now it's, it's like such a paradigm shift with AI where the operational administrative and communication burden can really change. And so you look at Mena and Tony, like two incredibly tenacious technical co-founders. And they were early to this problem. They started in 2017 and they have gone deep first in housing and more recently in health care. And the results just speak for themselves. Customers absolutely are delighted with the product. You see that qualitatively in the feedback, you know, we heard, but then quantitatively, uh, the scale, the growth, the efficiency, and we're thrilled to partner with them.

AI assessment note: “And so you look at Mena and Tony, like two incredibly tenacious technical co-founders.”

Q On the regulatory side, do you think we'll see full Yimbyism in, in our lifetime? Uh, or, or is your view of, Hey, we just gotta, there's some structural reason that impedes that in the U S relative to some, you know, country like Japan. And we just gotta work with what, what we've got.

A I think we, we really hope so. Uh, I think different cities actually have kind of started making real progress towards this. Um, Minneapolis is a great example. They, they did a big housing reform. Part of that was actually ending single family zoning, um, rules there. And, and that happened back in two, 20,019. And I think ever since that we've seen like, uh, supply has grown, uh, three times faster than the national average and the rents have stayed actually flat. Uh, for that whole period, uh, compared to everybody else experienced about 31% increase. Uh, so, so I think we're seeing some early signs there, uh, and hopefully other cities and, and, uh, states take that example.

AI assessment note: “I think we, we really hope so. Uh, I think different cities actually have kind of started”

Q So how big is this industry? And also maybe talk a little bit about how long it's been around too.

A So the industry is valued at three hundred billion today with expectations to grow to over five hundred billion by 2030. And it's just because there's, there's just so much work that needs to get done for large enterprises to be able to function. As well, the industry's actually been around for a long time. Some of the oldest players in the space were started in the 19 forties to help manufacturing companies manage their operations. And today really touches on all the major industries that we think about when we think about like the fortune 500. So It includes retail. It includes travel, telecom, logistics, manufacturing, healthcare, insurance, banks. It's just a huge, huge swath of industries who all in some way, shape, or form rely on BPOs to be able to function.

AI assessment note: “industry is valued at three hundred billion today with expectations to grow”

Q Right. And since we are, in some cases, taking on things that previously were done by humans, how do you think about pricing, or what have we learned there? Are you, are you seeing most companies just basically replicate the pricing models of the previous version, or are there new pricing models that are coming up?

A Yeah, it's early, it's changing every month, and I would say that's maybe the number one question that we get from companies, is how should I price? How do you see other companies in this space pricing? I think we've seen a few models that are starting to work or that people are experimenting with. So the most obvious one is you just charge per minute. So you can calculate kind of an hourly rate for the voice agent, similar to, like, what you would pay a human. There's a couple maybe wrinkles here. One would be a lot of these customers are informed enough to know that the underlying technology is getting cheaper. So they will come to you and say, hey, why am I still paying 30 cents per minute when Your costs have gone down, and you're probably just taking all of that in margin. And then as these spaces get more competitive, it's very easy then for a newcomer to come in and say, hey, I'm gonna only charge five cents per minute, and just kind of undercut you based on that. The other thing about the price per minute model is it really just puts your value as a platform solely on the phone calls, which again are kind of commoditizing versus like the other software that you're building around the phone calls. So, I would say as a result of that, we've seen a lot of companies evolve from just doing price per minute to some sort of platform fee. Um, maybe it's per month, maybe it's pe…

AI assessment note: “we've seen a few models that are starting to work or that people are experimenting”

Q Yeah. And I love those examples because you're touching so many different industries. And maybe if we zoom out just a little bit and think about maybe like a framework for disruption, how do you think about where maybe this could be applied?

A The way to kind of just zoom out and think about this opportunity is like, where are there a bunch of humans that are basically dealing with whether it's voice or, um, paper processes, where there's a bunch of unstructured data that they need to basically synthesize and then make sense of, and then generate some sort of output. Like obviously that's what LLMs are super good at. And so like the very common way of thinking about that might be like, Hey, there's a call center somewhere. Right. That's like the healthcare or the insurance example or the sales example. Um, or maybe you have some sort of, you know, we call it the messy inbox problem here where there's a bunch of different pieces of paper that are coming in and you need to synthesize them and put them into some database. But oftentimes that's like an internal team. Um, but then also you could look for wherever there might be BPO spend, like business process outsourcing spend, um, where maybe a consulting firm is doing this for you. So those are kind of the hot buttons of bits, not Adam's industry. Like you're dealing with paper. Um, not physical world things, um, and something that is conducive to be automated by all alums.

AI assessment note: “where there's a bunch of unstructured data that they need to basically synthesize”

Q Maybe we can talk about the use case, right? So when we're talking about, let's say, a military base, What is the current state, right? If we're not using these micro reactors, what is being used today, and what's the trade-off there if we can't actually get to that future reactor?

A Current state at the military base is that they have backup generators. Like any, any site that has critical infrastructure, um, those backup generators will have diesel storage tanks. There'll be 40,000 to, to a 150,000 gallons of diesel, um, on those sites, and they'll only, only use it in a backup scenario, so it requires they put batteries all over the installation, and, uh, if there is an outage, they're typically gonna run out of that diesel. Um, especially if there's, you know, something like the, that, uh, Colonial Pipeline ransomware attack, where we lost an ability to move fuel in a huge multi-state area. Um, and they run out of fuel before their, their timeframe, which is, uh, usually a 14 day resilience timeframe. Um, so they've got a problem, and they're looking for solutions, and they're actually very interested in, um, both categories of microreactor, because those are the, around the scale of the base. All of the larger ones, an SMR or a gigawatt class, uh, reactor would be too large for them.

AI assessment note: “Current state at the military base is that they have backup generators.”

Q say, it may sound silly to some folks, but you can imagine the human equivalent, right? So for Uber, it was literally calling up someone who then would dispatch a taxi, right? Or, you know, even Google Maps way back in the day, like before we had digital maps, you might even call someone or look up, you know, a physical map and say, hey, how do I get here?

A Steph, one of my favorite examples is, um, I'm a pilot and I, uh, fly a few different airplanes. A dear friend of mine, Richard Kane, built a company called VeriJet and uses the VisionJet. And the traditional aircraft chartering business is literally whiteboards and sticky notes where I'm taking this pilot and this airplane here, the fuel is here and it's like pathetic. So Richard, who's a brilliant computer scientist, built a platform on Verajet where the everything is optimized. Uh, he'll go to quantum compute later for, for doing even faster, but where the airplanes, the pilots, where the person is being picked up and dropped off and how they're being, All of it is fully digitized, and he used the vision jet, the SF-fifty, because it is massively connected. When the airplane lands, it sends all of its data of its, uh, systems check back to the AI. So you get humans completely out of the loop, and that's beautiful. It's efficiency, it's safety, and it's speed.

AI assessment note: “traditional aircraft chartering business is literally whiteboards and sticky notes”

Q one who needed a reminder that Airbnb, Uber, a lot of these super familiar companies are marketplaces and also huge companies. I could even say generation defining companies that, um, didn't exist a couple decades ago, right? And so when we're evaluating these marketplaces and developing the marketplace, 100, how do we think about what metrics really matter? Because today in 2023, there really are so many marketplaces to compare.

A Yeah, we have a ton of amazing data this year. We expanded our sample size by three times, so there were more than 12,000 companies that we looked at when deciding kind of what would go in the marketplace 100. The number one factor we look at is consistent across years, and that's arguably the most important kind of top line metric for almost all marketplaces, which is gross merchandise value or GMV. So that's over the course of a year. For this report, it was the year 2022. How much did consumers transact? Aggregated across all of the purchases on the platform. So how much did people spend on your marketplace? And then we kind of ranked from top to bottom the platforms that had the most consumer spend. GMV in some ways is almost a lagging indicator of all of these other kind of amazing things that marketplaces have built to make themselves ideally a sticky and highly retentive platform. So while GMV is kind of the end result of all the work that they do, when we evaluate marketplaces to invest, we're often looking at things like growth in active supply and demand, conversion from listing to sale, and then retention. So both on the user side and on the revenue side, once a seller has sold an item, how likely is it that they come back to sell another one? And in the best case, they don't just come back to sell one more, but they sell one in the first month and then five in the s…

AI assessment note: “The number one factor we look at is... gross merchandise value or GMV.”

Q A-C-C-Z fund. For more details, please see A-C-C-Z dot com slash disclosures. I am so excited for this conversation today. I've been seeing you post on Twitter. I've been seeing news articles everywhere about what DoNotPay has been experimenting with. And so we'll get into some of those timely topics, but first let's start out with where DoNotPay originated. So how did DoNotPay start and what really inspired this company?

A So it's no secret that I'm a terrible driver. And when I started driving at age 18, I got about 30 parking tickets between the ages of 20, um, in London and also when I moved here to study in college. And I couldn't afford to pay these really expensive tickets. And I learned something remarkable, which is if you know the right things to say, you can save a lot of money. And, um, I got this reputation among my family and friends as the person who can help with parking tickets. And it wasn't long before people were just messaging me, just pictures of their tickets. They wouldn't even say anything. I didn't want to copy and paste all of these documents. And so I thought, why not build an automated solution with templates where a user can select an option and then a defense is generated and sent to the right place. And I really just did it for a few family and friends, and I never could have imagined that it would go globally viral because people hate parking tickets. And that's what made me realize that the idea of helping people with technology and consumer rights is bigger than just tickets. And so I spent the past almost seven years now expanding Do Not Pay from parking tickets to many other areas of the law.

AI assessment note: “when I started driving at age 18, I got about 30 parking tickets”

Q So tell me a little bit more about that particular use case where you are helping someone get a refund or get access to something where it typically would take hours of someone sitting on the phone. How are you actually facilitating that with technology?

A So our motto is the squeaky wheel gets the grease. So if you are on a flight and the in-flight wifi doesn't work and you've paid, it's now 50 dollars for transcontinental in-flight wifi and it doesn't work. Our software will generate a letter and send it off to United Airlines, and it will cite FTC statutes and be really aggressive. United will receive that letter and think it's not worth it. And so, 80% plus of the time, they just grant the refund. And that's what's amazing is just with a template letter, we've managed to achieve all of this success over the past few years. But what's really exciting is in the past kind of six months, we're actually using more and more true AI. Versus decision tree templates.

AI assessment note: “Our software will generate a letter and send it off to United Airlines”

Q apps. And again, I'm feeling kind of old here, but during my era, you know, we're, we're thinking of Facebook, we're thinking of Twitter, um, Instagram, Snapchat, and none of these appeared in the top three. And so I don't know, what's your, what's your take there? Are we in like a new age? Are we diverging from the past in terms of what people want in terms of social?

A Yeah, it's a great question, and none of the, the kind of usual suspects, the Instagrams, the Snapchats, or the Facebooks appeared in the top at all, let alone the top three. The top five apps this year in terms of days at the top were actually all social media products, and three out of those five were apps that didn't even exist two years ago. That is definitely not always the case. I pulled the data for 2021 as well, and the top five for that year was a mix of some social media, but also FinTech, more utility or, or business apps like Zoom, and then traditional media apps like kind of HBO Max. To me, the fact that Instagram and Snapchat didn't appear at the top doesn't necessarily mean they're kind of dead as products. I think part of what it means is they've saturated the US user base, so they aren't getting a ton of new downloads every day.

AI assessment note: “three out of those five were apps that didn't even exist two years ago.”

Q to the top, but also staying at the top? It feels like we have smaller attention spans, people are excited to move on to the next thing instead of sticking with the applications that they know and love. Is that just me Interpreting the data, or are we actually seeing something here where it's not only harder to reach the top, but it's also harder to stay at the top?

A I completely agree. The largest number of apps that hit number one this year were number one for just a day, or maybe half a day, not that long at all. And more than half of the apps at number one were up there for less than five days throughout the whole year, not even five consecutive days. What I've seen is, you know, it's If you have a tick tock viral hit, you can maybe get a lot of people to download it, but then it needs to be a very strong product with network effects that encourages people to share it via word of mouth and to keep using it every day beyond that initial, oh, I saw this cool video about this app and I'm going to download it. So my view is it's in some ways easier to break into the top than it was five years ago. But it's probably actually quite a bit harder to stay at the top unless you have a very kind of magical and retentive products.

AI assessment note: “I completely agree. The largest number of apps that hit number one this year”

Q but I think there's maybe a further extension of that. Which is not just solo interacting physically, but also how, how do these digital apps potentially impact the way that we engage with other people physically, right? Like kind of a cyclical nature to our digital and physical lives. So are there examples of apps that you've seen that our online behavior actually penetrates the physical world or changes it?

A Yeah, absolutely. And, and I think like the first wave of subscription products, Uh, like the comms, the head spaces, the fitness apps, the nutrition apps were very much kind of single player mode and helping you optimize yourself and your life and your habits. We've definitely seen kind of this rise of this new wave of apps focused around relationships and really, you know, the app just needs you and one other person to work, but they'll prompt you with daily questions about the other person, things you want to talk about, basically ways to use this digital product to enhance This real world relationship that's happening and, and to maybe make things easier or to strengthen or to improve these relationships. The most kind of basic version of this was the widget apps that went popular. Lock it widget, the founder, um, he's a, his name is Matt Moss. I think he's either a college student or a recent college graduate. He made it for his girlfriend. They were in a long distance relationship and they wanted to see what each other was up to every day. Uh, and I think that use case is, is very strong of kind of how can we integrate technology more seamlessly to help us have better in person or in real life relationships. Another trend that we're seeing quite a lot of is apps and products, and especially platforms like TikTok, to be honest, driving traffic and driving engagement toward…

AI assessment note: “driving traffic and driving engagement towards real world businesses.”

Q to the top, but also staying at the top? It feels like we have smaller attention spans, people are excited to move on to the next thing instead of sticking with the applications that they know and love. Is that just me Interpreting the data, or are we actually seeing something here where it's not only harder to reach the top, but it's also harder to stay at the top?

A I completely agree. The largest number of apps that hit number one this year were number one for just a day, or maybe half a day, not that long at all. And more than half of the apps at number one were up there for less than five days throughout the whole year, not even five consecutive days. What I've seen is, you know, it's If you have a tick tock viral hit, you can maybe get a lot of people to download it, but then it needs to be a very strong product with network effects that encourages people to share it via word of mouth and to keep using it every day beyond that initial, oh, I saw this cool video about this app and I'm going to download it. So my view is it's in some ways easier to break into the top than it was five years ago. But it's probably actually quite a bit harder to stay at the top unless you have a very kind of magical and retentive products.

AI assessment note: “I completely agree. The largest number of apps that hit number one this year”

Q apps. And again, I'm feeling kind of old here, but during my era, you know, we're, we're thinking of Facebook, we're thinking of Twitter, um, Instagram, Snapchat, and none of these appeared in the top three. And so I don't know, what's your, what's your take there? Are we in like a new age? Are we diverging from the past in terms of what people want in terms of social?

A Yeah, it's a great question, and none of the, the kind of usual suspects, the Instagrams, the Snapchats, or the Facebooks appeared in the top at all, let alone the top three. The top five apps this year in terms of days at the top were actually all social media products, and three out of those five were apps that didn't even exist two years ago. That is definitely not always the case. I pulled the data for 2021 as well, and the top five for that year was a mix of some social media, but also FinTech, more utility or, or business apps like Zoom, and then traditional media apps like kind of HBO Max. To me, the fact that Instagram and Snapchat didn't appear at the top doesn't necessarily mean they're kind of dead as products. I think part of what it means is they've saturated the US user base, so they aren't getting a ton of new downloads every day.

AI assessment note: “three out of those five were apps that didn't even exist two years ago”

Q the fact that there would be an elevator without some of those things, and now there are, but I never noticed how that might influence people today because we're so used to elevators and just accepting the fact that they're part of our everyday lives, but there was a time where I guess that really mattered. That's so fascinating. Let's move on to number four. What's your framework number four?

A Right. So framework number four is we mistake a one percent problem for a worse problem. So I'll tell you another story from history, which is, um, which is that the waltz, when it was first introduced centuries ago, was, people talked about the waltz in, uh, society Europe The way that people talked about Miley Cyrus twerking at the VMAs a few years ago, right, like it was this incredibly scandalous, awful, destroying the youth kind of thing. Society had all sorts of reasons why they hated the waltz. It was, it was, you know, it was sexual, it involved too much, too much physical contact among young people, um, but doctors were saying that the waltz was Physically harmful. That dancing the waltz would take years off of their people's lives. Now, this is something that comes up all the time. I, I, you know, mentioned a little earlier, you know, there were doctors who said that the bicycle made people insane, and that novels made women infertile. But I, I talked to a historian of the waltz, and he made this really interesting point, which was that in that case, the doctors were actually right. The waltz was actually very bad for people's health. But the thing was that they thought it was the dance that was harmful, the spinning, the contact. It wasn't the dance. It was literally everything around the dance. So how did people dance the waltz in the, in like the early 1800? Well, …

AI assessment note: “framework number four is we mistake a one percent problem for a worse problem”

Q Awesome. Darren, I want to hear from you because you work at, well, actually both of you, Darren and Alex, you work at incredibly large, fully remote organizations. How did each of you go about that same process of building culture within your companies?

A I think it starts with defining what culture is at your particular organization, because everyone will join your organization with a different interpretation of what culture is. Past experience, their own personal beliefs, so step one is actually defining what culture is. So, of course, at GitLab this is documented. It's really composed of three things. One is values and operating principles, which Sandra already emphasized. The second is building camaraderie. You have to Formalize ways to encourage informal communication. And then third is how you work, defining how work happens. And this goes back to the sync and async conversation. Customer service, for example, works far less async than other organizations. And so you have to understand what are the ebbs and flows between the organization, uh, hedge against that friction that's going to, um, find its way in if you don't. But defining how we work plays, uh, A big part in culture, and I think a lot of companies don't pay enough attention to how work gets done and how communication happens. That is critical to culture, so being very intentional about that is a massively important third leg. I do want to say two things on that. I mentioned operating principles within values. This is how we create behaviors out of those words on a wall that you mentioned. If you look at the GitLab values page, it doesn't stop Talk with the six c…

AI assessment note: “step one is actually defining what culture is. So, of course, at GitLab this is documented.”

Q is like shock to the system. So it sounds like we haven't kept up, but I think there's, there's also something you've talked about, which is that the people who were involved several decades ago are also starting to retire. So what does that look like? How many companies are actually involved in this space of advanced manufacturing? And what are we seeing there in terms of that almost lapsing?

A Yeah. So there's something like 20 to 30,000 small businesses that make up the majority of the defense industrial base. And I think just to frame this before I go into the detail, basically, if you're making a fighter jet, you know, you're actually outsourcing most of the assemblies like a wing or an engine to another company like Pratt & Whitney. And then Pratt & Whitney has a network of, you know, 2000 suppliers that give them the components and they might do some engineering. And then, so what these companies are actually doing is taking a lot of, taking the Lego kits and assembling them and then throwing the assembly up another layer and then Lockheed finally stitches the whole thing together to, to give an example. So there's about Um, you know, we have, um, 30,000 or so of these small manufacturers that in aggregate make up the entire defense industrial base, but individually are like small businesses where maybe they have 10 to twenty million in revenue max, and there's maybe 15 to 20 employees. have, And the danger there is, um, because we outsource manufacturing and because we culturally decided that if you don't have a college degree, you're worthless to society. There's been no new entrance to the manufacturing workforce because it's not sexy and it's not rewarded in the culture. And because we've had no shocks to the system, no one's realized what a big problem it i…

AI assessment note: “something like 20 to 30,000 small businesses that make up the majority”

Q I want to close by asking you guys then, for that very reason, to come full circle, because I didn't even ask you this. Like, what actually brought you to crypto in the first place? I mean, Brian, where'd you get the idea for Coinbase?

A You know, there's a few pieces looking back that had to come into place for it to happen. I mean, one was that I studied computer science and economics. I was always interested in how software was going to disrupt These industries which seem to be the holdouts, right? You know, finance and education and healthcare, and so that was the first piece. The second thing was that I spent a year living in Buenos Aires, Argentina, in 2009, and I got to see really what a country looked like that had gone through hyperinflation, and I had never seen that before living in the U.S., and I remember these little details, it affects the whole culture, right? Like I was at a restaurant and there was a menu, and the prices, you know, there was like a sticker on top of a sticker on top of a sticker on the menu, They couldn't print a new menu every week, so they had to keep putting new prices on there. And the third thing, I think, was that, you know, I joined Airbnb. I was, I was probably employee 40 there or something, and I was working on some of their payment integrations, and they were in, you know, maybe a hundred countries or something at that point. And it kind of gave me a front row seat into just how broken the global payment system is. It's this patchwork quilt of different countries. They all have their own proprietary system for pay-ins and pay-outs, and They don't really have an ince…

AI assessment note: “one was that I studied computer science and economics”

Q And there's a lot of people that have come out of Coinbase doing really interesting things. And every classic company has a way. There's the Intel way that Andy Grove wrote about. There's the Toyota way. What is the Coinbase way? How does your container of tribalism, or whatever you're working towards, organize to build something that people can actually use?

A Well, in addition to just being really mission focused, which I mentioned already, And also being a fintech company, meaning, you know, we're about 37% engineers, we have a strong legal and compliance component, you kind of have to marry those things. I would say there's four things which really define the Coinbase way and the Coinbase culture. So, the first one is clear communications. We look for people who are concise, candid, kind, good listeners, just convey information really effectively to help us get work done. The second thing we look for is positive energy, and that's our way of saying, Optimism about the future, determination to get there, intrinsic motivation, and, you know, there's gonna be a lot of setbacks on the way to creating an open financial system for the world. I mean, you're basically trying to reinvent the economy of the entire world, and so it takes a lot of, every setback is an opportunity to, like, come back with optimism. The third one is continuous learning, and this is something I've been really passionate about is, you know, I've had an executive coach throughout being a CEO. We have lots of opportunities for people to learn. We put them in stretch roles. We're really big on two-way feedback, I try to create these environments of really high trust where a team can not be afraid to surface what they're really thinking, and, you know, we'll go aroun…

AI assessment note: “I would say there's four things which really define the Coinbase way”

Q I want to close by asking you guys then, for that very reason, to come full circle, because I didn't even ask you this. Like, what actually brought you to crypto in the first place? I mean, Brian, where'd you get the idea for Coinbase?

A You know, there's a few pieces looking back that had to come into place for it to happen. I mean, one was that I studied computer science and economics. I was always interested in how software was going to disrupt These industries which seem to be the holdouts, right? You know, finance and education and healthcare, and so that was the first piece. The second thing was that I spent a year living in Buenos Aires, Argentina, in 2009, and I got to see really what a country looked like that had gone through hyperinflation, and I had never seen that before living in the U.S., and I remember these little details, it affects the whole culture, right? Like I was at a restaurant and there was a menu, and the prices, you know, there was like a sticker on top of a sticker on top of a sticker on the menu, They couldn't print a new menu every week, so they had to keep putting new prices on there. And the third thing, I think, was that, you know, I joined Airbnb. I was, I was probably employee 40 there or something, and I was working on some of their payment integrations, and they were in, you know, maybe a hundred countries or something at that point. And it kind of gave me a front row seat into just how broken the global payment system is. It's this patchwork quilt of different countries. They all have their own proprietary system for pay-ins and pay-outs, and They don't really have an ince…

AI assessment note: “there's a few pieces looking back that had to come into place”

Q I mean, your whole book is about leadership lessons. What was, like, the biggest leadership lesson in that moment?

A Well, for me, it was, if you have a crisis and you've got to take a tough step, do it quickly, get it over with, and move through. Reset the clock so you can Then charge ahead. And that turned out when the financial crisis hit, you know, Stanford lost billions of dollars of its endowment. About 28% of the endowment vaporized in a six-month period. So there was no way we could continue to spend money the way we were. We were gonna have to go through that process again. I realized, you know, that's gonna lead to five or 10 years worth of small budget cuts that are gonna not be very efficient, and we're gonna not be able to do anything new. So we sat down and said we need to do this quick.

AI assessment note: “if you have a crisis and you've got to take a tough step, do it quickly”

Q Didn't you used to call it like gravity?

A I called it gravity. It just would get, it comes down to earth. And then the job of the entrepreneur is to be looking years down the road and say, okay, at some point growth in business A is going to stop. And so I want to keep it going as long as I can. And there's a whole bunch of taxes to do that. But then the other strategy is, okay, I need new layers on the cake of growth. At eBay, the original business was an auction business in the U.S. And so, you know, some of the things we layered on earlier, we layered on fixed price in the U S not revolutionary, but it really did increment growth. Then we went international and then we layered in payment integration. And each time we did that, the total growth of the company would actually accelerate, which is very hard to do at scale.

AI assessment note: “I called it gravity. It just would get, it comes down to earth.”

Q Didn't you used to call it like gravity?

A I called it gravity. It just would get, it comes down to earth. And then the job of the entrepreneur is to be looking years down the road and say, okay, at some point growth in business A is going to stop. And so I want to keep it going as long as I can. And there's a whole bunch of taxes to do that. But then the other strategy is, okay, I need new layers on the cake of growth. At eBay, the original business was an auction business in the U.S. And so, you know, some of the things we layered on earlier, we layered on fixed price in the U S not revolutionary, but it really did increment growth. Then we went international and then we layered in payment integration. And each time we did that, the total growth of the company would actually accelerate, which is very hard to do at scale.

AI assessment note: “I called it gravity. It just would get, it comes down to earth.”

Q the very minimum share with us the taxonomy for what we're looking at here? Because I hear this list of names and I'm just like, it's like alphabet soup, you know, it's, I don't know what's going on. So like, how would you break it down at a super high level? What's the big thing to know for where each of these are at and how they might be involved?

A Well, so just taking treasury, I mean, FinCEN, the Financial Crimes Enforcement Network, They're trying to assure the integrity of the financial system against nefarious actors. That's their broadly stated mission. So monitoring the financial systems like banks and all other kind of financial services companies for suspicious activity. OFAC, the Office of Foreign Assets Control, you know, the United States maintains a list of people and countries or nation states that is sanctioned, and so OFAC makes sure that transactions aren't going on in the financial services realm with those countries or individuals I'm sure you all unfortunately know what the IRS is, but yet very important of what the IRS is going to do with cryptocurrency. I mean, really, it's quite hard for people who have cryptocurrency gains to figure out what is the right thing? What are they supposed to do? The OCC, Robin just alluded to the fact that you need 50 different money transmission licenses to do business as a cryptocurrency exchange in those states. OCC is trying to come up with a federal fintech charter. So that only one license would be needed. So far, that hasn't gone anywhere. Do you want to cover any others?

AI assessment note: “FinCEN, the Financial Crimes Enforcement Network, They're trying to assure the integrity”

Q Right, is that like a natural selection effect?

A Yeah, you don't, you can't vary radio circuits and then suddenly get a computer out of that or radar. You can't vary air piston engines in 1930 And get a jet engine out of that. These things come along as completely new combinations using new principles, and that keeps adding to your Lego set. And that starts to explain why there's a controversy or a question, say, in the 19 twenties, anthropologists were asking, why don't you have trams and steam engines in the Trobriand Islands? And they began to say, well, it's not because the Islanders are stupid. It, It's because they don't have these building blocks to build it out of, and that in turn has many implications. One of them is if you get a region like Silicon Valley with an enormous number of these building blocks, and more important, it has the people who understand the craft to put all this together, not just the science, but what parameters, then it can very quickly keep coming up with new combinations.

AI assessment note: “Yeah, you don't, you can't vary radio circuits and then suddenly get a computer”

Q I mean, I would agree, but is that the big transformation now, that we have the modern tech equivalent of the printing press?

A What's gone external now is not information, what's gone external is intelligence. I may be driving in a convoy of 50 driverless cars, And the whole idea of the car adjusting, the car is talking to roadside sensors and servers, it's talking to other cars, it's talking to the highway patrol servers and so on, and it's basically farming out its intelligence into this other economy, and then getting back intelligent actions in return. So it's a bit like phone a friend, Only the friend is incredibly smart, and the friend consists of, again, these hundreds of thousands of servers talking to each other and then adjusting what you do. So suddenly intelligence doesn't just exist on human beings. Suddenly intelligence exists in the cloud or in this autonomous economy, and we can format not just getting information, But getting smart moves back, and this is making all the difference.

AI assessment note: “What's gone external now is not information, what's gone external is intelligence.”

Q Right, is that like a natural selection effect?

A Yeah, you don't, you can't vary radio circuits and then suddenly get a computer out of that or radar. You can't vary air piston engines in 1930 And get a jet engine out of that. These things come along as completely new combinations using new principles, and that keeps adding to your Lego set. And that starts to explain why there's a controversy or a question, say, in the 19 twenties, anthropologists were asking, why don't you have trams and steam engines in the Trobriand Islands? And they began to say, well, it's not because the Islanders are stupid. It, It's because they don't have these building blocks to build it out of, and that in turn has many implications. One of them is if you get a region like Silicon Valley with an enormous number of these building blocks, and more important, it has the people who understand the craft to put all this together, not just the science, but what parameters, then it can very quickly keep coming up with new combinations.

AI assessment note: “Yeah, you don't, you can't vary radio circuits and then suddenly get a computer”

Q of theory or not. And we also discuss the problems of data and optimization, as well as the pros and cons of machine learning as a service and touch on the theme of the API economy. But we begin by quickly reflecting on where we are right now. What are we seeing with companies adopting AI beyond R&D? The first voice you'll hear is Scott followed by Joe. Why now?

A So I think AI is kind of this, in this unique position that it hasn't been in historically before. All the pieces are coming together. People have the data sets now. They have the tooling and the open source community has been huge in that with tools like MXNet and TensorFlow being widely adopted and productionalized. And now they have the infrastructure readily available with things like AWS and all these new Nvidia chips. In addition to a whole bunch of APIs to make a lot of the hiccup and like difficult parts of the system easier and easier. And so the combination of all these things together means that instead of spending a decade in the R&D lab to try to come up with something, now a couple of data scientists can make real business impact almost immediately with the AI go-to-market.

AI assessment note: “All the pieces are coming together. People have the data sets now.”