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[00:00:01]

Today I'm here with Tony Xu. Pretty amazing, actually. You came from China really young, worked very hard, did all kinds of jobs, go to Stanford, started this incredible company, which is now the biggest food delivery company in America, about to conquer the world, made billions, given lots of them away in philanthropy. Basically, I'm sitting here in front of the american dream. What are you, what are your reflections about your journey?

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Well, I think that it's impossible to predict how things go for you, you know, as you think about these things. I think it's, you know, as you recounted that list of experiences, it's only one that can be told backwards. It's not one that when I was, you know, mowing lawns at the age of seven, trying to save up money for Nintendo games or duck hunts or washing dishes in my mom's restaurant, could I have predicted what would have happened later on? But I think it's just how incredible things can be if you put your mind to things, work hard and get lucky.

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How hard have you worked?

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Probably not as hard as a lot of people, but, no, I've been very fortunate. I think that working hard certainly is something that has always really been in my family. I mean, I think this really comes from my parents, right? Both of them came to the US, brought me from China to Illinois when I was five. And I really didn't get to see them that much. Not because of neglect or anything, but because they were trying to put food on the table. We came to the US with dollar 250 in the bank, and my dad was a full time waiter as he was getting his PhD. My mom was working three jobs a day for twelve years before she actually can save up enough money to practice what she always wanted to do, which was open up a medical clinic. But it took a while for our family to get our foundation and footing in the US. But thanks to them, I got to really live off of the fruits of their labor and carve out my own path.

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And what do you think it does to ambitions come from kind of, you know, to work, to work one's way up like that?

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I think you can have multiple effects. You know, I think sometimes when you grow up in a situation where you don't necessarily see a lot of outs or a lot of ways to progress your current situation, that can be somewhat demotivating. But at the same time, I think, you know, it also gives you a lot of independence. You know, when I was a kid, I spent most of the time by myself, right? Learned English by playing basketball and watching tv. You know, I named myself Tony, after Tony Danza, you know, from who's the boss?

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And that you did on your own when I was five.

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Well, nobody could pronounce my name, you know, nobody could pronounce my chinese name, that is. And so. But, you know, from being independent, you know, early on, you know, I learned both about good decisions and bad decisions, right. And I think it put me in environments where I had to be quite agile to adapt to whatever the circumstances. I changed schools a lot when I was a kid growing up because my parents were always trying to progress our economic situation so that I can attend better schools. I moved probably four or five schools in my elementary to middle school years. And as a result, I think of those experiences, it wasn't as if it increased massively my levels of ambition, but it certainly increased the practice at a very young age for independent thinking.

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First of all, what do you think it means to change schools? Often we hear that from some various CEO's that they moved quite a bit. They talk about it as helping their agility and so on. What is your view on that?

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Well, I think it's pretty tough to know this when you're a very young person, but I guess looking backwards almost always made you appreciate feeling like what it meant to be the outsider or the underdog, if you will. Right. You're always in the out community before you can become a member of the in community in terms of gaining friendship or getting privileged to certain circles inside the school. But I think for me, it taught me that there's value in every interaction, that you can be friends with people in a school that's known for teen pregnancy, sadly, or a school that's known for gifted children or everything in between. And I think as a result of that, it just increased the rate at which I learned, probably. I don't think I intentionally knew this when I was a child, but whether it was playing lots of basketball or doing lots of math, I got to play in different spheres. And I think probably develop in a way that was quite healthy. It again showed me the value of interaction, every interaction, that there is a superpower in everybody and to look for that. And I think if you can do that collectively, you can do great things.

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What were the important steps before you started at Stanford?

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One of the first moments I remember in adulthood is really graduating from college where my background was in math. I wanted to be a cancer researcher, and so I did lots of work in labs where the work was done at the intersection of mathematics and biology. It was a fairly young field at the time maybe 20 to 30 years old or something like that. Today I think it's quite advanced, especially with the recent developments in large language models, compute AI. But back then, I think it was just kind of in itself inception or its formation. And I thought I was going to do that and pursue graduate studies and all of that jazz. But my world actually 180 at graduation, where I decided to not start the graduate program in which I was accepted, but instead 180 into a world of business which I had no experience in.

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Why did that happen?

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Well, in one of the admit weekend activities where you get to visit the lab that you would be a part of, I realized that of the four or five students that would be members of that lab, I didn't feel the most committed. And for something that would be a twelve year journey, actually, that would have been a twelve year journey. As a 21 year old, I made the decision that there might be something else for me now that was quite scary for me at the time, where I think for a while, especially in the world of academics, it's a fairly straight laced, well understood set of progressions that you can take into getting to greater and greater specialties, where you have to concentrate on an area for a long period of time before you make a large or significant contribution. But for me, I took, I suppose, at the time, the path less traveled, which was doing something I've never done before. When I joined McKinsey out of college, I remember showing up in the first week in t shirts and jeans, and I didn't understand what business casual wear meant. I didn't know what Microsoft Excel was.

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I didn't know what PowerPoint was. I barely understood the word revenue. My background was more in the intersection of mathematics and biology.

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Well, you must have learned more science. You must have picked this up pretty fast then.

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Well, you have. Thanks to the awesome teammates and colleagues I had at McKinsey, I did. But I think what that experience taught me was that I think for me to have gotten to Berkeley, which is where I completed my undergraduate studies, that in many ways, life had already given me so much more than maybe what it's given some other people, that I'm gonna be okay. And I think that had a pretty formative opinion for me in terms of just something to remind me that it's probably okay to take more risk. And the fact that McKinsey actually worked out pretty well for me just added more confirmation to that bias.

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What did you learn at Stanford, then?

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I think Stanford was a fantastic journey into thinking about actually myself, more so than developing necessarily professional skills. And what I mean by that is, on one hand, I thought it was a fairly expensive use of time. I don't necessarily just mean in terms of tuition or things like this, know, you're sometimes your most productive in your twenties. And so those disproportionately expensive years of my career. But on the other hand, you know, the thesis that, that I had made for Stanford or just for business school, I should say, in general, was really to think, you know, what are other types of skills that I want to develop as well as what are things that, you know, I truly would want to go and do and to take maybe a little bit of time away from just working hard every single day to actually go and figure that out.

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And the skills that you wanted to acquire there, what were they?

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Well, so when I thought about my journey, a lot of the journey, whether it's growing up as an only child and then moving around a lot, or moving in high school from Illinois to California, or even working in a lab in research, or as working as an analyst at McKinsey or at eBay, most of those work experiences were isolated experiences or very solo journeys, if you will, where most of my contributions were measured by what I individually contributed. Right. And I learned a lot by doing hopefully what was considered great work. But at the same time, I also learned that great things get accomplished with teams and I didn't have that much experience working with other people. Now, business school in of itself does not offer that, but particularly at Stanford, there was this emphasis that on working well with others and figuring out how to motivate not just people that are similar to you or motivated similarly, the way that I'm motivated, that was a big selling point of the curriculum, and it's something that I still try to get better at every day.

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Now then you set up with some friends what was then Palo Alto on delivery and now Doordash. How do you come up with a. Yeah.

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So all of us came together because we were excited about local businesses. That's really the motivating theme for each of us. And I know a lot's been told about my background, but if you were to look at the backgrounds of my co founders and their family histories, they also have experience with small business too. And so the four of us kind of spoke with hundreds of local business owners. Some of these people were restaurateurs, others sold retail items. And it was interesting when we asked them, hey, show us all of what you do in a day, that when we followed them around, there was this one baker, who ran a macaroon shop on University Avenue in Palo Alto, who showed us a booklet of delivery orders she had refused, which to us was quite surprising, a, that you would turn down people wanting to pay you, and b, the significance of that decision, given the fact that she was a one person shop and that those orders really were the difference of making payroll or having some extra padded insurance money for the business. We started from that discovery. Talking to more businesses about this issue, it was surprising, this is 2013, that while delivery was not a new idea, that no one in America, outside of pizza places or certain cities like New York City, offer delivery.

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And that was true in restaurants, and that was certainly true beyond restaurants.

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So then you sit down with your mates and figured, okay, let's start a delivery company.

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Well, so there are a few things that we were thinking about. And so we said, okay, well, if our goal is to help local businesses, and we found this discovery that delivery could be a need, the question is, well, do consumers actually want this product? Because we live in a very capitalistic market in the US, and so a lot of times business ideas perhaps were not started because nobody wanted them to be started. We wanted to test a few different ideas. The first is, do consumers actually want delivery from stores that never offered delivery before? Second, would stores actually want to partner with us and pay us to help them get new customers? And three, could we attract and recruit a group of drivers who would be willing to work for a wage that we could afford? And so that was really how we thought about it. In many ways. It was a hypothesis of what needed to be true in order to start the company. And then the reason why we chose restaurants was because we thought, well, if delivery was going to be the way in which we made a difference for local businesses, and we wanted to build the largest delivery network with the highest quality and the lowest cost.

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Well, you need the most amount of order density, and with order density, you kind of need two things. You need lots of frequency of activity and you need lots of coverage. So one of these two requirements was an observation we made and the other was a bet. So the observation we made was, if you looked across every category of local retail in America, restaurants has the highest count of stores. It didn't, at that time have the highest dollar spend, but there's a million restaurants as an example, versus, say, just a couple hundred thousand grocery stores as a counterpoint. So that's why we started with restaurants. And the bet would be that if you can start with restaurants, that there would be the most frequency of activity with the most number of stores that that would generate the most order density, which would make it easier to build the last mile network for any other category.

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Tell me about the first order you got.

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The first order we got actually happened on a Saturday, January 12, 2013. So we shipped paloaltodelivery.com dot. Okay. This was the most minimal version of a minimal viable product where in 45 minutes we built a website with eight PDF menus. There's no way to order. The only way you can order is to call a Google voice number that rang the cell phones of the four founders.

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And, yeah.

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So a customer in Menlo park actually placed an order. I think the only way he found us, because the order was placed 45 minutes or so after we launched the website, was literally by typing in Palo Alto delivery.com in the browser, because Google, I don't think, would have indexed our name at the point yet. But he placed for himself an order from Bangkok cuisine. And it was two items. It was chicken pad Thai and it was spring rolls.

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So pretty good, basically.

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It sounded delicious. He calls in, one of my co founders answers. He's in the car with me. I'm in my 2001 Honda at the time. And we are literally about to drive home from campus, but instead we detour and go to Bangkok cuisine, place a takeout order, bring the order to his house.

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So you did it yourself?

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We did it ourselves, and then we went in and I was an intern the previous summer at square, and so I had a lot of these square card readers at the time. It was this white register product that you can insert into the jack of the iPhone. And so that's how we accepted payments.

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What did you feel?

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It was awesome. It was in some ways not believable that somehow he found us. We were shocked. He found us. So, as they say with entrepreneurial journeys, you may have this amazing feeling of euphoria when you launch. And then quickly that's followed by a trough of sorrow. The trough of sorrow followed pretty quickly thereafter where it wasn't that easy to get the next set of orders for the first few months.

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And how did it scale? I mean, what happened?

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We effectively were a delivery service at the time for the Stanford campus. Right? So we're still students, you gotta remember at the time. And so we're students, we're running this survey. So we're taking classes, you know, in the daytime and at lunch we would take turns, you know, doing deliveries. We would call and take turns dispatching by calling in the orders and then using find my friends, the iPhone app to track where, you know, each of us, four founder drivers, we're the only drivers you know of the service were. And then we would dispatch the orders ourselves. Right. We were the human algorithm behind the scene. And we did this for about four or five months before we applied to Y Combinator. And we launched officially as Doordash, June 21 of 2013. In the summer 2013 batch out of YC.

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How many deliveries do you have now per year?

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Per year? I believe the last reported number is in the billions. But.

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So from one to billions. Yeah. When you set it up, what was kind of the dream? What was the biggest that you thought could happen to this?

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So it's funny you asked that question, because that's literally the question why combinator asks you in the application. I wrote the application.

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And just to fill in a Y combinator, that's Sam Altman's company at one point, right?

[00:19:01]

Yeah. So Paul Graham, Jessica Livingston and others founded Y Combinator, which is this incubator program in Silicon Valley that helps start companies. Sam Altman, to your point, at one point, ran YC. Today, Gary Tan leads YC. But one of the questions, certainly in the 2013 era that they asked in the application was, how big can this service be? Or how big can your product be? How much revenue do you think you'll earn by year seven? Or. I think it was some version of the question. And I think at the time, for consumer companies we were studying, achieving $100 million of revenue was a very significant milestone. And so I just remember writing, doing some sanity math about, well, today we launched in Palo Alto, or we operate in Palo Alto. How many Palo Alto do there have to exist, and how many orders in each Palo Alto do we have to complete such that we can generate $100 million of revenue? And that was the math I remember answering. So $100 million is what I answered. Thankfully, I was off by a couple orders of magnitude, but these are things that are hard to predict.

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What are the important milestones from that stage until now?

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There are many along the way. I think it really helped that when we started the company, we did have this organized framework that is really centered on our audiences, our customers. We have three kinds of customers. We have consumers, we have merchants at the time. There are restaurants today, they span all of retail. And then there are dashers, the drivers on our platform for Doordash to work. From day one, we had this belief that it has to work for all of these audiences. It can't just work for one of the audiences or two of the audiences. It really has to work for everyone. That was a nice organizing framework for us to figure out. Okay, great, you made it work at Stanford. Can you make this work in Palo Alto then? Can you make this work in a larger area like San Jose? And how extensible is the service? Can you repeat this in places of all social economic backgrounds and populations? And so that was really the journey, I would argue, between 2013 and 2016, where we proved to ourselves that, a, we can make it work for all the audiences and make a dollar doing it, and, b, that we can actually launch this in a mainstream way.

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And what were the main setbacks?

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Oh, there were many. So did you, like, nearly die during this period?

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Sometimes.

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Many times. I mean, between 2013 and 2018, the company almost always felt broke, and I was singularly responsible for it because as CEO, one of my key, or maybe sole job responsibilities, top priorities, is to make sure we never run out of cash. But it was really hard. The fundraising process, I remember there were three years between 2016 and 2018. That's about 1000 days where I felt like I was wandering in the desert asking for money from investors for people to fund Doordash. It was.

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So what kept you going on?

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There's never one answer, I think, because at some point, willpower gives out, and you need something beyond that. And for us, I think one of the lessons I learned throughout that journey, even in some of the tough moments early on in the company's life, is that while you have this grand vision and mission as the entrepreneur that you're always holding onto, it's really the team that dictates your day to day satisfaction. And if you can build a culture where it feels like, yes, you want to win, and, yes, you want to do all the things for the customer, and it feels like you're playing for one another and playing, you know, for the team versus just playing for yourself, it's a lot easier to get through whatever the moments are because it's a lot easier to have, you know, at the time, there's about 250 of us, you know, go through this together versus just me single handedly trying to do this on my own. And look, I mean, it doesn't mean that there weren't losses, right? We, you know, we had a quarter of the team, you know, maybe a little less, but close to a quarter of the team who decided that maybe there were greener pastures elsewhere because, you know, you see the bank account declining every single week.

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We're a highly transparent, high ownership company where we report out on numbers, and I understand that. But if you think about the people that remain and stuck with it. And perhaps this is one version of survivorship bias, but for the people that remain that hung in there long enough and won by building a product because we didn't have any access to dollars, so there was no marketing spend or things like this that had a product that had higher retention and order frequency so that we can then get lucky enough to get an investor or two to say, yes, that, you know, that group of people, I think, share a bond that is very, very, very difficult, impossible to break.

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Now, you started with food, and then you broaden out. You now do groceries. You do other things, too. What are you doing? What's the limitations here in terms of what you can deliver?

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Well, if you can deliver ice cream cold or pizza hot, you basically can deliver anything. And so that was part of the thesis of, again, starting with prepared meals, not just because of the order density perspective, but also from what you're talking about, which is the logistics capability. So we've effectively built the most sophisticated point to point system where any business can deliver to any consumer and back. Any business can deliver to any other business. And, look, there's a long ways to go. I think there's the logistics element to how hard this is as you go from category a to category b to other categories. But there's also just organizing the information that's offline. None of this information exists. We're sitting today in Los Angeles. If we wanted to ask, where's the last parking space in downtown La? That's a really important question for dashers who want to be doing deliveries, or if we wanted to ask, where can we find the last bottle of coke at a particular price point? Very few stores know that information. And I think while there's an amazing revolution happening, certainly with large language models online today, there's still so much information that is offline that still needs to be organized and assembled.

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You talked previously about wars. There were two wars. There is a war on bits, and there is a war on atoms. What do you mean by that?

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I think if you think about what's happening in technology today, and this is, I think, even true, beyond technology, we have one world where it's a digital first or possibly digital only world, where there is a lot of dynamic behavior in the environment, thanks to llms, but also just thanks to a lot of people vying for the consumer's attention who ultimately want to be that center point, that digital assistant for your life. Right? And there's a big battle going on right now, but there's also another war where we're talking about physical atoms, where people like ourselves are trying to organize all of the offline information. And we're also trying to deliver all of the products and help local businesses grow incrementally, as well as build their own capabilities for their first party channels. And I think that what's interesting is that there's lots of activity happening in both of these arenas. And I also think there's going to be, over time, intersection between the arenas. But I think right now there's so much interesting activity just happening in developments that literally are progressing by the day and by the hour in both worlds.

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Now, you were expanded outside the US as well. Well, you expanded to Scandinavia, you bought vault.

[00:27:44]

Yeah, yeah. Doordash is now live in about 30 countries worldwide, 29 outside of the US. And you're totally right. We teamed up with an awesome company called Volt, who is headquartered in Helsinki, so the Nordics, and they actually, Mickey Kusi, who's the founder and CEO of Volt, actually leads all of Doordash's international efforts.

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So how many different experiments are you running?

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Well, we run a lot of experiments, but it doesn't necessarily mean that's a reflection of how many different projects we have. So Doordash has always been a company where the bias for action is the way we solve and settle debates. We don't analyze a lot or debate a lot. We tend to ship lots of experiments, hundreds to thousands of experiments per week, recognizing that most of them will not make it to our audiences, most of them will not make it to customers, consumers, merchants, or dashers. On the one hand, you can argue that feels really unfortunate, and there's a lot of just productive energy going away. But the way we think about it is it's about how fast we can learn and how fast we can fix things. And if we can do that well, then hopefully we've earned another rung in the ladder of satisfying a consumer. One thing we've learned.

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So how fast can you trial and fail and move on?

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Well, I mean, I think with experiments that can probably happen in hours, but building businesses, you need more than one type of skill. One type of skill we're talking about here is this learning, agility and speed of execution, and the willingness to try and fail. But there also is, I would say, another side of business building, which is really hard sometimes to keep in conjunction with this willingness to learn, which is the ability to have the patience and the long term conviction that perhaps the path that we're traveling on is the wrong one, but at least where we're going is the right place. And I think as the operator, in some ways, you need two management systems. One that's used to manage something where you have a pretty good idea of where you're going and you can even forecast with great accuracy kind of the variance along the paths. These might be some of your more scaled businesses or businesses in which you've surpassed product market fit and finding efficient ways to grow. That requires a very different set of management techniques than inventing new businesses where you want to be stubborn about, you know, the vision of where you want to go and what the job to be done for the customer is.

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But you have to be super creative, patient and open minded about the path in which you're going to get there. And I think, you know, that's been true in Doordash's life. In each one of the businesses. We have about five businesses now that we operate. But as we think about inventing business number 6789, et cetera, et cetera, et cetera, we have to keep an open mind to have two different systems in which we operate.

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So now I work for you and you say, hey, Nikolay, could you go and check out this thing? I do this experiment, it's a failure. I come back to you and say, tony, I'm really sorry, I've screwed it up there. How do you react?

[00:31:16]

I would ask, what did you learn? And I think one of the things that is so important to contextualize as the entrepreneur on a new journey is that there's always elements of skill and elements of luck, and you need both as the entrepreneur. I think that when we were founding DoorDash, we made some good decisions about what to prioritize, how much to bet on certain dimensions of how a consumer will judge us versus a merchant versus a dasher. And there's some points that we scored from the skill category, but there was a lot of luck around how large these categories could be, or that if we made certain decisions to invest more in this market versus that market, it's not always something that you get to know in advance, otherwise it wouldn't be an entrepreneurial journey.

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Moving tank a bit here. AI and technology, what's the next thing it can do for the company?

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I think right now the answer is we don't know and we're trying our best to learn as fast as possible. We certainly have been playing with a lot of the advancements in large language models pretty much for the last two or three years, and certainly it's become even more popularized over that period of time, we've seen glimpses of a lot of success, especially as we think about how can we help organize the physical world and build datasets from that and use AI to understand how to fill out those catalogs. We've seen AI in other use cases, whether it's helping us with customer support or detecting fraud, there's lots of use cases. And I think the best way to think about where we are is just we're very small percentage of the progress bar. It's one we're very bullish on in terms of the general technology, but in terms of finding the home run, I guess the mantra we have right now is about making sure that it's about having enough shots on goal where we don't know the silver bullet. Answer to your question about what is the killer application with respect to some of the advances in llms as it applies to our kind of business.

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But we're learning quickly.

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Who else is trying to organize the physical world the way you are?

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Well, I think it's happening in pockets. I think what's so hard about this is that unless it's your mission to grow and to empower local economies where, you know, you're on this many multi decade journey, where that is the sole source of what you want to do, I think it's really hard. And that's why I think in the past it's mostly been done in pockets. Right. You know, some people will organize, I don't know, parts of retail, other people might organize, you know, parts of services, other people might organize parts of department stores. And I think what's both daunting as well as exciting for us at Doordash is just the enormity of the challenge that we see ahead of us, where we do want to be both the infrastructure in the physical world for every city we operate in, and we also want to connect every local merchant with every local consumer. And I think doing these things are just. It's only two things, but it's going to take many decades.

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At the same time, you try to kind of put yourself out of business.

[00:34:58]

Well, we're always trying to make sure that we're inventing a better product. One of the things that I've learned is that consumers are never satisfied. There is like no consumer is going to remember the fact that we've delivered faster today than a year ago. They're just going to expect us to deliver faster, you know, a year from now or even tomorrow. Right. And no consumer is going to ever ask us to increase our prices or lower our selection or make worse our customer support. So I think, you know, instead it's, I think, building the fortitude as well as the team with the mentality that we always have to invent new businesses. But we also must understand the importance that we always have to keep getting better at the main thing, too, right? It's like you have optimization on one side and innovation on the other. And they require very different management systems. They also require you to hold both of these things in your head at the same time.

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What kind of culture do you need at Doordash to achieve this?

[00:36:03]

I think you need several things to come together, because I'm glad you asked about the culture that might be the only thing that actually allows you to achieve all of these ambitions and build all of the products, which is, I think it's first and foremost, start with a very high ownership, high accountability kind of culture, where if you think about what we do, it's more of a utility service versus an entertainment system. So if we mess up and we don't bring you your products, that is extremely disappointing in the eyes of the consumer. That's a lost sale, which is for a business that might be very thin on margins, and it's a lost work opportunity for a driver. It really is a reflection of the local economy. The way I see it is if you think about GDP and where it gets created, most GDP is still produced by the small, medium, and large businesses physically inside every city. And they also, these businesses describe the personalities of why we choose to live in Los Angeles or Oslo or San Francisco or other great cities. And I think in order for that to stay vibrant and true, where we live in a world where all of these businesses will be successful, instead of a world where there might just be success at the hands of one or two merchants, then we have to take great ownership and seriousness of that responsibility.

[00:37:39]

I think it starts there.

[00:37:41]

So you talk about accountability and ownership. So here you interview me now for a job. How do you figure out whether I have it?

[00:37:49]

I don't think there are any magical interview questions. I think most of these things happen through listening than necessarily asking the perfect interview question. I recognize it's a bit ironic as we're talking about this in a podcast, but for instance, I'll give some examples when we talk about high accountability. If I see a senior executive come, and the first thing they tell me in the interview is, here are the five reasons why you should not hire me. That's a very different communication mechanism or choice than someone who just tells me all the wonderful things that they've accomplished. Something else we look for is this strong bias for action. One of our early builders at Doordash, and he's still someone who works with us, but in a smaller capacity, was Christopher Payne, who was our first chief operating officer and president. He, I remember, spoke with me on a Friday for about 4 hours in 2016. And later that evening, like, you know, within a matter of a couple hours, basically, he and his 13 year old son, Andrew, at the time, 13 at the time, you know, they literally went out and just did deliveries for three or 4 hours.

[00:39:10]

That's a high bias for action. I didn't ask him to do that. I didn't say, hey, can you tell me what's wrong with our logistics system? No. He just went out and did deliveries and figured it out. Right. We care about people who operate at the lowest level of detail because the physical world is messy, and everything is an edge case. So our former CFO, our current president, Prabir Darkar Prabir, shows up in my first interview or conversation, where he brings a ten megabyte file that's a model of what our financial projections would look like for the next five years. I didn't ask this was a coffee or supposed to be a coffee chat. What turned out to be a four hour examination of unit economics and the progression of our markets and our performance. We look for people who can hold two opposing truths at the same time, people who are not dogmatic in how they think. We look at people who are great at building teams. We look at the track record that doesn't have to come from an interview. Strong followership, because it takes a team to sustain in order to win.

[00:40:15]

And so we look at when people move jobs, for example. So even before the interview, we look at when they move jobs, how many people literally follow them. And so these are some of the things we call them, the attributes of excellence that we look for in building a culture that I think can meet the demands of what we're trying to do at Doordash.

[00:40:36]

This ability to get people to follow you or being a talent magnet is key here. Why do people want to follow you? What is it that you have as a leader which makes it attractive to work for you? You think?

[00:40:48]

Well, I think you should ask that.

[00:40:50]

I already would love to work for you. So you got me already.

[00:40:53]

I think you should ask them, Nikolai. But look, I think one of the things I always believe, and I believe, and I told you this at the onset of our conversation today, is that I believe that everyone has a superpower, and it's my job as the leader to get it out of them and give them the maximum exposure for that superpower. And I hope that superpower, that that exposure will always be at Doordash. Right? I hope that to be true. But even if it's not true and it has to be somewhere else, I think maximizing someone's strength is really, really important. And so I think one of the things that people have appreciated when they come to Doordash is that it's a place that sets a high bar for achievement and excellence. And I think people who are very motivated tend to be motivated similarly. It's a place that is very rigorous and maniacal about the outcomes, but we are very flexible in how we get there. It's a place that bets on people, perhaps before their resume has achieved maybe the credibility to deserve or warrant that job opportunity. It's a place that is willing to take, you know, risks.

[00:42:14]

Sometimes that's time risk, sometimes that's financial risk, sometimes that's operating risk. And I think, you know, all of this sums up. It's a place where we are trying to make you the best version of yourself. And hopefully, you know, one of the aspirations I always have had at Doordash is it's not to just make you successful at Doordash. That's great. But really, if, you know, we are successful as leaders at Doordash, if the day that you left Doordash and decided to do whatever happened to be next for you, that you are so confident that you can achieve that scale of ambition, then we've done our job.

[00:42:50]

What is your superpower?

[00:42:54]

Sometimes I'm still trying to figure that out, but I think one of the things that I find a lot of joy and spend a lot of time on is spending time with people that have more talent than they do experience and identifying those people early, but also giving them exposure in the right ways. So that means that you don't just give them maximum exposure and just let them sink or swim, but giving them the right amount of support while pushing them to the edge so that they still have their confidence, so that they can achieve the next level much faster than they otherwise would have.

[00:43:45]

You are on the board of meta, you know, Facebook, basically. What are you learning there that you have taken into your business?

[00:43:56]

I think sometimes one of the hardest things to keep up as you become more and more successful. And when you talk about meta, you're talking about, you know, a family of apps, right, that are used by more often than any other products in the world. And you're talking about audacious bets in AI, in reality labs, and building the next ecosystem. I think to see that constant drive, despite all of the success it already has achieved, is astounding, because it means that the company has an enormous willingness to fail. If you think about it, they're still trying to invent new things, whether it's in AI or in the metaverse. And some of these ecosystems certainly are not here yet, some of which might be many years away. To have the willingness, I think, to perhaps go against the wisdom of the crowd to do that, to have the courage of their conviction to do that, both in the new as well as the existing. The family of apps with Facebook, Instagram, WhatsApp and many other fantastic products. I think that's super inspiring. And I think it's a great, almost like look forward for me and I think others where you can see both management styles of running scaled businesses and inventing the new.

[00:45:26]

The other thing I've learned is just how great the leadership team at Meta is at building the next generation. Meta is a company that largely, not entirely, but largely, has been built from within in terms of mentoring and giving the opportunities across the board, across various products. And I think that also is something that resonates quite a lot with how we think about talent development at Doordash.

[00:45:56]

How do you relax?

[00:46:00]

I love to exercise.

[00:46:01]

And I heard you do a norwegian kind of exercise regime, right?

[00:46:04]

I've tried. I've tried. It's called the norwegian four x four, which is one of the most proven exercises scientifically to increase your vo two max. Although I would say it's a, it's a difficult workout, and I wouldn't recommend it if you've never ran before. That's not the first exercise I'd recommend for you. But, you know, for me, I really believe in routines as a way to find balance and normalcy, or balance may not be the right word, but to integrate my life and my work. Right. And so for me right now, and routines can change, you know, your life circumstances can change. I started Doordash as a single person I was dating, but, you know, now I'm married with two kids, and my life is very different from, you know, 1011 years ago. Right. And so now my routines are continuously exercising still. I still exercise every single day. For me, that used to mean running, and a lot of it was distance running. Today, that's shifted and morphed into other types of sports, whether it's weight training or jiu jitsu, trying new types of sport beyond just running.

[00:47:09]

What do you read?

[00:47:11]

I try my best to keep up in reading, although that's been a bit light recently. I try my best to read books every month, one book a month, where I'm a big fan of nonfiction.

[00:47:23]

Do you read history?

[00:47:24]

Yeah, a lot of history, but a lot of it is different from my wife, who is an exclusive reader of fiction. So we don't really have overlapping, necessarily, reading interests.

[00:47:34]

And what kind of history do you read?

[00:47:36]

What do you find useful? A lot. One of the things I love to read about real people, I think one of the things is I truly believe that life is more interesting and entertaining sometimes than fiction. I think some of these things you just cannot invent.

[00:47:50]

Well, tell me some of the real people you admire or have read.

[00:47:54]

Well, there's a lot, and so I don't want to necessarily single out any particular leader, but I've really enjoyed histories and biographies around military leaders or different wars that have been started, or the study of industries or the study of businesses. That more is not necessarily a business school per se, textbook, but more a book, actually, about the business and the people that are at the beginnings of that company and trying their best to not tell the story backwards, but really to tell the story from the perspective of when things were happening. And I think it just goes to show you how incredible humanity is.

[00:48:40]

When are you going to write the story about Doordash?

[00:48:43]

Probably not anytime soon. But look, our story is still evolving. We're a ten year old company. I can't believe it. On one hand, that it's been ten years. On the other hand, I still remember the apartment in which my co founders and I built the company out of.

[00:48:58]

What is your advice to young people?

[00:49:00]

How young are we talking?

[00:49:02]

We are talking 20.

[00:49:06]

I think one of the things I would say is to be proud of the person in the mirror. I think that sometimes young people get thrown lots of advice, you know, from their parents, from their friends, from social media, from the news, and it's really easy to get lost in the wind. I was almost that way. And what I mean by being proud in the mirror is to figure out what are the things that make you who you are? What is your superpower? What are the routines that describe you such that you feel like work is not work that you would do, you know, this for free. Or that the type of people you enjoy spending time with, the people that give you energy, the people that replenish you. And look, it doesn't get figured out overnight. I'm still trying my best to figure this out, but I think sometimes the world's advice isn't about being proud of the person in the mirror, it's about chasing some shadow or finding the next exciting thing to be excited about. And I get that topically. Like, I'm super curious about lots of different things intellectually, but I think the ways to build strategy, whether it's for your life or for your work, is you kind of have to bet on the things that don't change.

[00:50:28]

And I think one of the things you have to bet on is to figure out what are the things that you're truly. That were really gifts given to you that naturally make you, you know, really excel at something. And I think if you can do that and figure that out in terms of what it means for your personal life, I think you're going to live a very satisfied life.

[00:50:49]

Well, Tony, you should be really proud of the person in the mirror. And this has been a really wow conversation for me.

[00:50:55]

Likewise. Thanks, Nikolay.

[00:50:57]

Thank you so much.

[00:50:57]

All right, thank you. Appreciate it.