The economics and trends of the restaurant industry, with Tony Xu of DoorDash

28:01They've made it where it's highly irrational as a frequent traveler to travel not your preferred airline. Like they've really created a lot of lock in there. Whereas as I think about restaurants, there is like the super mass market punch cards, you know, 10th coffee free stuff. and then there's the like really old school restaurant where the owner might greet you and you know might comp your dessert or something but it's very sporadic and very dependent on the owner being there because as you say when you know the new waiter waitress is there they don't know you but there's kind of nothing in between systematic and it feels like some kind of way of rewarding regulars is missing yeah well it's a hard problem I mean let me ask you I mean what is your favorite food to eat?

28:44depends but at the weekend we went and we got good Taiwanese food. And that was fabulous. All right. But how often do you eat that? Once a month, once every two months. Once a month, once every two months. That's the challenge, right? Even your favorite food is probably not something you're going to do every single day when you're talking about an activity like eating, which is 20 to 25 times a week. It's not like coffee. Yeah, it's not like coffee. It's even different from travel where the product, you know, may be the same every single time. I think it is tough to create what you're describing, which is this program in which you'd be known as regular.

29:18But that, I think, is the opportunity that at least we're thinking about at DoorDash because if you think about it, our product with now over 100 million plus annual customers, tens of millions of monthly customers, they shop at various frequencies. And they're building relationships with all of these businesses, sometimes many times a day, sometimes once every other month, sometimes once a year. and I think because there's 20 to 25 moments per week, I think that there is an opportunity in which we can create that and now we recently acquired last year a company called Seven Rooms that manages a lot of the in-store bookings of restaurants, particularly of higher-end restaurants.

30:01If we can democratize that and give that to everybody and then also layer on the DoorDash dataset and actually kind of tell you that John is a regular and he tends to like the following things and here's other things that he tends to do, perhaps we can crack open that question. So you want to help restaurants take care of regulars? Yeah, because that is how you build a great consumer business. Yes, yes. You need the retention. That is true for every restaurant, every consumer business. That's interesting.

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31:18We were talking a lot about ghost kitchens, I don't know, five or seven years ago. You don't really hear about them that much. How big have ghost kitchens become? They're relatively small. People thought the model was going to take over, right? Yeah, look, the model sounds really reasonable and I think logical on face value, where if you can, you know, on that spectrum of restaurants where you have, you know, high-end service on one end and hospitality only to perhaps delivery only or more of a manufacturing concept on the other end, it seems reasonable that you can actually just borrow a small square footage of space, not incur a lot of not just the fixed costs, but also the labor costs of actually running your restaurant in quotes, and then selling through a delivery platform or acquiring your own customers or doing something like both.

32:10It just turns out it's extraordinarily difficult, however, unless you're a large brand or a house of brands, someone like DoorDash, to be able to attract enough customers to make that math work. So is another way of putting it that it's hard for a ghost kitchen to be as efficient as a restaurant that is also churning out orders across both, you know, in restaurant and delivery? Like, it's just hard for them to compete on the economics? Yeah, it's slightly different. So perhaps we can look at two types of examples. So you can have one type of example, which is perhaps, you know, my mom's Chinese restaurant.

32:53You know, it's an SMB where the name value outside of perhaps it's literally its locale isn't that well known. it's very difficult for that restaurant to acquire enough customers to make that math work because they still have to remember i mentioned that staffing was the number one challenge that restaurants um face they still have to staff these kitchens you know that's that's one of the challenges now you go all the way to the other side so pretend you are a large qsr with a big brand presence you certainly can attract lots of customers but you're gonna have to think for yourself, well, what's my opportunity cost?

33:29My opportunity cost might be to open up another restaurant. Why not do that and take my economies of scale and actually apply it to more orders, in-store orders, as well as to-go orders? Because I can do that with a restaurant. Hard to do that with a delivery-only kitchen. And so I think because of that, it's a tricky model to scale to every type of restaurant brand. Yeah. I think people maybe thought that big chains were going to do it more, where you're right, like the billboard effect for an actual retail presence is hard to compete with, where like you get this very cheap customer acquisition from the fact that people know your name from the high street or maybe have been to you.

34:09And as a ghost kitchen, you know, you need to make up for that awareness gap. But if you're Chipotle, maybe people thought that the orders get fulfilled out of a dedicated Chipotle central factory and then the retail space are separate. But also that hasn't really happened that much. That happens occasionally, right? And it's because I think these are not decisions where we're accounting for all of the variables. One variable we're not accounting for is, well, what else could I do with the space? You have to remember for businesses like Chipotle, who tend to identify real estate in fairly expensive areas, there's high opportunity costs of what you do with that space.

34:54Yes, you're right. One choice is to turn it into a kitchen or a delivery-only kitchen. And sometimes that happens. But there's also a massive opportunity to recoup the expense. And if you start introducing, for example, franchises, Chipotle is not really a franchise, but if you look at other types of brands where it is franchised, I think that the economics become even trickier. So there's a next best use kind of math. Which restaurants have actually invented something that's hard to copy? Well, I actually think any restaurant that's been around for, let's say, two plus decades probably has very interesting IP.

35:32And obviously, you know, some of this information is not public. But you can imagine when you go into a McDonald's around the world, that French fry, perhaps they don't sell the same exact items in every single store in every country, every city, but the French fry almost always tastes the same. That is an extraordinarily difficult feat to accomplish. There's a lot that goes behind the scenes, just like there's a lot that goes behind the scenes at DoorDash in terms of getting you one order on time to make that sentence true. and the same can be said about a lot of other businesses that have been around for very long periods of time that's on the you know big brand you know qsr side where a lot of the innovation if you will is in the process innovation and then also how do you run um large groups of people and have very high and consistent standards of service extremely difficult extremely difficult And that's the IP, I would argue, for a lot of these large brands.

36:35Now, on the other side, there are small restaurants, some of whom have been around for almost a century, actually. There aren't that many of them. But when you look at what makes them special, it tends to be the same things that actually make startups special. It tends to be a small group of people that really believe in a certain idea, some commitment towards some standard of excellence. It could be excellent towards the food, the service, or takeout. There are some takeout-only businesses that have been around for many decades. And as a result, they have high retention, high usage, and they're very efficient.

37:12Can you speak about any specific examples of just the impressive IP that these chains have conducted over the years? Like it could be the McDonald's, French fry, how they actually make it taste consistent. I don't know the answer to that or any other of your favorite restaurants. Yeah, well, one of the things that I'll never forget was I went through a hospitality training at Chick-fil-A in, I want to say it was 2017, maybe it was 2018. And, you know, I don't remember everything on the checklist, but one of them that stands out is that the floors must be so clean that babies would lick them or could lick them.

37:54and the babies will lick them regardless exactly is chick-fil-a still the highest grossing fast casual restaurant per square foot i don't know actually but it's definitely people talk about it yeah but it's definitely up there why is it so successful well it actually goes back to i think the the standard ingredients of a great consumer business it has a highly retentative following, which it spends very little money acquiring, and they come back often. And they're extremely efficient with all of the scale economies behind the scenes around equipment, which is quite custom to that company, to the service training, to how they treat their staff.

38:40I mean, one of the most impressive facts about that business is that many people actually that I met with have spent over two, three decades of their careers at Chick-fil-A. And I think we find that to be a novelty actually here in Silicon Valley or in technology. And in the restaurant industry. And in the restaurant industry, one where we described all of the churn and the difficulty of staffing, Chick-fil-A has extremely high retention of staff. And it has, you know, so many repeatable stories of where, you know, it gives somebody who comes from not a lot of means, frankly, to become the general manager of one of these stores and earns a really healthy living, pays, you know, their entire family through college and beyond.

39:29And I think it's, you know, many ways, a lot of these restaurant stories, Chick-fil-A being one of them, have a lot of the essence still of the American dream. We're talking a lot about QSR chains here. And people often like to ask the question of why is there not a Chipotle of, you know, my preferred cuisine where it's, you know, slightly elevated versus like regular fast food, very good, consistent quality, good execution. There is no chain that serves you really good Neapolitan, you know, thin crust pizza in whatever city you're in or Indian food, or again, pick your favorite cuisine. Why don't we have more chains delivering just a really good standards version of the cuisine.

40:15Have you ever cooked for a large group of people? Or do you cook often? Yeah, we cook, but not for huge groups. Yeah. And one of the things I found is that as the number of people you have to cook for grows, the difficulty to keep the standard of service, whether it's the taste, the temperature, the speed in which you receive the food, goes up exponentially. And that is what's so hard about exactly what you just said around keeping that quality control really high. It's maybe easy to build you the Chipotle for one type of cuisine for one restaurant. And that's just on the skill perspective. Although, you know, I do have some ideas on how perhaps you can do that.

40:59But the second reason also is think about who you're competing against right so you have to now okay let's say that you want to make a neapolitan pizza you mentioned um or any kind of okay great great i can't wait to taste it i can't wait to taste it john okay well did you know that there are over a thousand different pizza choices in you know the bay area on doordash just on doordash right and we don't have all the restaurants yes And, okay, that is just one of the many things that you're going to have to do to be able to create this concept and actually scale it. It's not this. And then don't forget all the other challenges we talked about.

41:39The staffing. Yes. The permitting. But, like, what determines whether chains succeed versus whether they don't? Because there's a lot of pizza restaurants in the Bay Area. But at the same time, there's a lot of, you know, Mexican restaurants in L.A. that are really good. and yet Chipotle still has plenty of locations there. And so it doesn't just seem to be, you know, do there exist local options? Sometimes a chain can break through. And I also don't think it's a skill issue because it's very processizable to make a good Neapolitan pizza. It's about, you know, the ingredients and the temperature and humidity control in the proofing the dough and then the, you know, cooking it at very high temperature.

42:18But it's not rocket science. You could make a process around this. Potentially. But I think the fact that there only exists so many of these QS, accountable number of these brands who have actually scaled to the size that we're talking about where they're ubiquitous, I think, you know, should be some evidence. It's harder than you think. You know, that it's a lot harder than you think. And because of what I just said, there's a lot of process skills that you have to be extraordinarily good at. In fact, I remember we partnered with one brand where we launched this brand to great fanfare, great fanfare, and sold a lot of burgers, actually, on a weekend, testing this idea.

43:04Can you make a healthy-tasting burger if you put a brand name around it? The answer is yes, and the answer is really hard to retain any of those customers. Because it's too healthy? No, because half of the reviews said your burgers were great and the other half said that they were inconsistent in quality. And it's because it's extremely difficult. You know, that exponential challenge as you try to, you know, grow scale and keep up the quality is very, very, very difficult. I mean, you have to get right the service. You have to get right the production. You have to get right the pricing, the packaging.

43:42There's lots of things you have to get right. So do you think reliability is the thing that people underestimate about the restaurant industry? Yes, or about a service like DoorDash. You know, I think when you have high volumes of activity, I think keeping the reliability as reliable as the electricity we have or the water, you know, inside of our buildings, that is extraordinarily difficult. Can we talk about the future of delivery and how you see it playing out in 10 years' time? There's a few different modalities being discussed. There's drone delivery. There's sidewalk robot delivery. And you guys have DOT.

44:15I'd love to talk about DOT. I don't know how much you're doing in drones. Maybe you can talk about that too. Maybe there's autonomous vehicles, like autonomous cars. People don't talk about that that much. But maybe in the suburbs, it would kind of work. That's what we have at the moment. Just like, what's the mix in 10 years' time? Yeah, well, I think even before we go there, I think the first question might be, what might be delivered? Because I think that's actually still not that well understood. You know, so today, yes, DoorDash is probably most known for food, potentially, you know, now increasingly groceries and household items.

44:49But that is a fraction of the tens of millions of items inside every single city. You know, one of the biggest things that, you know, we're going to have to do before we can just fulfill the items, which is, you know, what we'll get to, is where are the items and what are the items? There's tens of millions of items literally inside these cities, whether it's in the U.S. or different countries within Europe, other parts of the world. They're not cataloged. There's no structured data that you can scrape in order to figure that out. And I think that's going to be a long journey. Sometimes the inventory is not even close enough.

45:25And so you may have to house the inventory so that you can actually bring those goods and even have the right. A lot of what I believe makes for great logistics is you need a great setup. Because if you're always trying to figure it out on the fly and you're pulling some magic trick out of thin air and you have to be the hero, that is not a system. That is an exception. And I think great logistics or great reliability, they require building systems. And so, okay, you have the catalog. You got maybe the inventory close enough to where people live. Now we can talk about the fulfillment, right? But the entirety of that is what you have to build before we can get into the great technologies.

46:07The staging of what it is that you're delivering. Because if you don't know where to get the items or if you can't get the right item, what difference does it make if you have the right vehicle? And you're talking about the fact that like you don't actually know what's on a supermarket's shelves where the fact that you have to actually be able to predict when the restaurant will have the stuff ready, like all that kind of knowing what is ready to be delivered. Yeah. Or, I mean, take when the cheeky pint becomes an established bar and maybe Dorash can deliver from one day. What's inside the cheeky pint?

46:43You know, what's on the actual menu? What's off menu? And actually you can order. I mean, these are complicated issues before we even get to the fulfillment of the actual items. And so, okay, then you can get to fulfillment, right? And I think that's one where we're still exploring. And to me, the most important question we always ask on any, frankly, technology, but certainly a technology like this where there's long cycles of development is what problem does it actually solve? Obviously, in the case of drones, you mentioned it, it can cover a lot of ground very quickly. So longer distance orders, that seems to be a great job for it to solve.

47:21In a busy high-rise area where you got short, dense orders, which is the majority of these orders, maybe not the best solution for such product, right? And this is actually what led us to the creation of DOT, which was when we started the autonomy project in 2018, 2019, we actually did not set out thinking that we needed to build anything, that we would surely there would be someone. We'll just pick the best one, and I'm sure we can buy some tech off the shelves. Yes, we were out there raising our hand, you know, asking for a partner to the dance, so to speak, and someone, you know, who could specialize in that, and we could specialize in the operations and things like this.

48:01And it turned out that, well, no one was that interested. A lot of people were interested in building robo-taxis, and obviously we've seen that kind of come to fruition. A lot of people did build, to your point, sidewalk robots. But, you know, we found those to be too slow. So back to what problems are you solving? Because you've got to remember, you know, back to opportunity costs, humans are very good at delivery, actually, it turns out. We're also very good at driving, too. And so the bar is actually a fairly high bar. It's not as simple as just saying, oh, we can make the technology, let it rip.

48:34And so then we said, well, okay, well, it has to be fast enough. it probably doesn't need to be the size of a car because cars aren't very good at parking inside these busy locations where a lot of these restaurants are. And so we had to think about all these things. We had to think about how to load the vehicle. We had to think about unloading the vehicle because unlike Robotaxi, the passenger solves all of those problems. But in our case, we have to solve that. So that's kind of how we ended up on this. Where are you enrolling out that? We're primarily testing right now. We really want to get it right in one market.

49:10We're doing a lot of this in Arizona. Because it's not just the technology. Yes, that is one of the things I've learned and come to appreciate about building something like DOT is that these autonomous vehicle companies are almost many companies inside one company. And certainly many different types of skills you have to be good at. Yes, I think everyone obsesses over the autonomy. Okay, but there's also the hardware. There's also the manufacturing. There's also the operations. There's hardware reliability. There's also the maintenance. Yeah. There is also the regulatory. Yeah. There are a lot of different components that you actually have to be good at.

49:48And then we can talk about the stack required to actually build the inputs to some of these things. For example, there's also understanding how do you procure supply when you have sometimes geopolitical tensions or when you have supply chain disruptions. where do you do assembly versus where do you do construction? Not super obvious answers to some of these questions at times, especially when you have to make these decisions sometimes years out. And so I think that's the stage that we're in right now, which is, okay, we got to figure this out correctly before we can actually scale it. Where do drones fit in, if at all?

50:26They definitely do. I mean, as I mentioned, back to jobs to be done, I think drones obviously can do a lot of these longer distance orders. And so we've been doing drone deliveries actually for a couple years now, mostly outside of the United States, outside of the U.S. Places like Australia. We're going to bring them to Europe, bring them to the United States as well. But again, you have all of those problems you have to solve. The autonomy is a little bit easier. You still have a routing problem. You have hardware problems. Obviously, you still have permits and regulation. set up, loading inside different stores, things like that.

51:04It's very interesting. We're talking a lot about some of these scaled tech problems. And one of the ones that people might not think about is fraud. But I feel like Stripe and DoorDash obviously work together in many ways. But one of the things we work together on is fraud. And I feel like the number of potential fraud vectors is much more complex than people think. Maybe you can just talk about trust and safety at DoorDash all the different ways that people try, like you're running this complex system that people try to game and what it takes to run that. Yeah, I mean, many times I kind of think about my freshman year electrical engineering course on state machines and where Dornash in some ways is like a large state machine, right?

51:52Where you have many systems in place and they're kind of observing, you know, what's happening. there are things that must happen when things are green to keep them green but as we start degrading gracefully you know from green to yellow to orange to red you know something like fraud as you mentioned other systems have to kind of kick in and do things like exception handling obviously you're spending most of your time building prevention systems but of course it's it's tricky um you also have to have the 911 response system that literally responds you know within minutes because sometimes we're talking about physical safety.

52:28We're not just talking about fraud, right? I mean, given the volumes that DoorDash carries, billions of orders per year, the one in a million incident, unfortunately, does occur. And so that's DoorDash. This is system. Now, in fraud, you're right. We partner, for example, a lot on online fraud. I mean, you have the largest database, right, of all of these transactions, and therefore you can give us lots of information that we ourselves couldn't do on our own. On the flip side, there's also offline fraud, which is very tricky, you know, to catch. Okay, for example, for example, let's say that a consumer suggested that an order was never dropped off.

53:08Let's say that a Dasher said that an order at a grocery store was already shopped and picked, but we're not sure. Or that let's say that But a Dasher said an item is missing inside of a store, any kind of store, maybe perhaps an apparel store. All of those, I would argue, have offline components that are difficult to verify. This is building the eval, if you will, for this set of conditions and use cases. It's actually extraordinarily difficult. And so a lot of what we're trying to do is we have to build those signals ourselves. There is no perfect science here. I wish there were. But in many ways, we kind of have to invent this.

53:47This is actually why, you know, I'll give you a few examples. So one of the things that we shipped, this is actually a couple years ago, was called SafeChat, where we noticed that prior to any physical altercation that may unfortunately happen between audiences, 90-something percent of the time it's always preceded by a verbal altercation. Knowing that alone, you know, allows us to prevent a lot of tough situations. Or building alert systems. For example, sadly, there are shootings, particularly in the United States. And there was one shooting in Manhattan where, you know, several people died in the lobby of a large office building.

54:32But within minutes of a Dasher seeing the shooter walk in to the building, you know, we have an alert system that doesn't just alert all dashers and consumers and merchants within that vicinity, but also all local law enforcement. And actually, we were the first to report that to the NYPD, who tried their best to respond in time. But, you know, there are a lot of those events. And so it's not always about fraud, I guess, is what I'm trying to say. And that you You have to build extremely responsive systems, and you also have to build as many signal detecting systems too. Yes. You're running a fairly large slice of the economy, and you're trying to have everything run smoothly, and there's quite a lot of failure modes that people might not think about that are possible when you're just seeing so many economic attractions all day.

55:27Exactly. We're trying to be the digital representation of these cities, right? Whether it's a city, a suburb, a neighborhood, a rural area. And sometimes it's not always of what's transacting, but it's just what activities are occurring. One of the hardest kinds of frauds to prevent is like the classic credit card fraud. One that people think about is your car got stolen and it's actually someone overseas buying stuff for themselves rather than you buying it for yourself. That we've actually now got very good at detecting. It's quite hard to do. And there's just like so much data we can bring to bear on that problem.

56:06A much harder one that we see that businesses face is the kind of thing of the industry term of ours, which is kind of funny, is friendly fraud, which is a bit of a euphemism. But the customer buys something and just says it never arrived when it actually did. And they're just straight up lying. But you don't really want to call them on us. You also don't have proof that they're lying. but it definitely does happen to some degree. And so how do you deal with, I mean, maybe there's a photo of the Dasher having delivered it, but I'm curious how you deal with people just kind of defecting from the system.

56:39There's no one answer, as you know, with fraud, because as soon as you figure out how to measure the risk and contain the risk, obviously the incentive for the fraudster goes towards the next axis of breaking it. Exactly, exactly. And so I don't think there's a perfect solution to the problems that you're describing. But you're right. I mean, a lot of this is about a lot of how you build systems, I think, you know, where obviously the metric is around reliability and consistency and great customer outcomes. The inputs are a lot of measuring things before things happen. You know, I talked about, you know, I think one of the most important things about logistics is the setup.

57:17That happens even before a delivery event is somebody hits place order, right? The setup is extraordinarily important. Did you get the right catalog? Did you actually, you know, label correctly the catalog? Blah, blah, blah, blah, blah, blah. A lot of that sort of stuff. Okay. Now, in the case that you're describing, you know, we can track several things. We obviously can track what is happening with the Dasher. You mentioned some of these ideas. Taking photos of receipts or orders being dropped off. We have our own mapping system, for example, that we built. Why do we build our own? Well, it's because we care much more than any, you know, third-party mapping system of exactly where the last two feet, forget 20 or 200 feet of some apartment unit door is, for example.

58:00And we know if we reliably deliver to that door and that we saw the pin actually hit exactly where, we have a little bit more fidelity on whether something was dropped off. We build profiles of customers, I'm sure you do too, of their behavior and what they tend to say. So there's lots of things that we're trying to do behind the scenes to build these signals to figure out what is the likelihood here of fraud. Yeah. Makes a lot of sense. Tell me about DoorDash Tasks. DoorDash Tasks is something that we shipped recently where actually, you know, it started with a project where we were trying to solve our own problems.

58:37So it started with trying to figure out where is every item, you know, inside the city. And so we have millions of dashers and they're usually frequenting different types of stores. We know that consumers move around items a lot, which makes it extraordinarily difficult for any store to track their own inventory. And so, you know, Dasher sometimes are collecting this information, right? That was one of the problems that we were solving. Interestingly, while we were doing this, we started getting calls, actually, from people you probably would expect, retailers and CPG companies who might be interested in this information.

59:18And then, you know, especially as companies, I think it's well known at this point that a lot of the large LLM companies have been building lots of repositories of online information. Well, what about the offline information, you know, to bolster, you know, some of those models or just to help some of these companies building robotics and things of the sort? Well, we said, oh, interesting. Well, okay, we're building a catalog for ourselves. but we ought to be able to help other people too. And if it's an opportunity to help dashers earn more or give them more choices to earn more, great. Why not build that solution?

59:58And so that's really the story of DoorDash Tasks which started organically probably a couple of years ago as we were solving our own problem. And we started realizing that there may be other people who have similar tasks. And so as a platform for having kind of fairly small tasks done, you can give the task to DoorDash and you guys go complete it? Yeah. Do you guys excited about an AR angle for DoorDash? Are you one of the best use cases of the meta glasses? No, you can get directions within the store and everything. You actually speed things up quite a bit rather than wandering around lost. I think we could be.

1:00:31I think we definitely could be. But again, back to the question of asking, what problem does this solve? The human is pretty good with their eyes at some of this stuff. So the bar is pretty high in order to do some of the things you're talking about. Yeah. As I just kind of think through AI applications for DoorDash, one thing I'm struck by is that the LLMs are pretty good recommenders just by tossing things into context. You don't need to train a custom model. But I don't know if you've ever tried for like book recommendations or TV recommendations. You just like tell it a bunch of the stuff you like already.

1:01:06Restaurant recommendations. It's like, here are 15 restaurants we like to go to. Give us other recommendations and it'll do a really nice job. and yet within products, you know, if I open DoorDash, it's kind of the same categories and things like that and it's less personalized to me than if I took my DoorDash history and put it into an LLM. Isn't that, like, shouldn't we be somehow using the fact that LLMs are pretty good recommenders within products? This is not just DoorDash, it's every product I use. It feels like those recommender capabilities are underutilized. No, I think you're definitely right that there's an opportunity here where there's almost like the traditional school of thought, which is to use the information that you have, right?

1:01:46And you build the best personalized models that you can. And, you know, one of the things that LLMs obviously does is it kind of throws efficiency out of the wall, right? Right, from the wall. And it kind of throws as much compute towards it. And interestingly enough, one of the things that spits out, you know, when you put in enough tokens and have big enough context windows is you're right. It has actually better models because it's, I mean, It's just using much larger data sets. And it's a world model. And it's a world, exactly. And so I do think there's an opportunity in what you're saying, which is that products like DoorDash, like consumer products, will definitely have their own ordering agents.

1:02:29And I think we're all trying to figure out what is that right modality, right? Because it's not obvious to me that everything's going to be done through text. We don't buy things through text. And we don't always get inspired through text either. And so I think it's something that we're all figuring out. What else are you excited about these days from a product point of view? What's a new part of the product that is close to your heart? Or where do you want to take things? Well, we have a few missions that we're on. And we talked about several of them, I think, in this conversation. One of them is we've got to bring you everything inside the city.

1:03:05And we're a long, long, long ways from that. You know, we can go super deep on restaurants and food, but as you start going into category N plus one, you know, we are just a smaller and smaller and smaller drop in the ocean. So we got a lot of work to do. A second mission, obviously, is we also want all of the businesses that we support to have their own software. You know, I mean, DoorDash's goal is not just to grow your business by sending you customers. We also want you to learn how to do it on your own. And that's why, you know, we have products like DoorDash Drive or Storefront or Seven Rooms, which are really B2B products, which is probably why consumers don't think of us for them, and help you build your own omni-channel business.

1:03:46We have a mission in which we want to actually bring you inside stores. That's actually something that, you know, we're trying to do, right? And we started that about a year ago. I mentioned earlier that one of the perennial challenges or trends for restaurants is how do you grow your own brand? Well, if we can also help you with that, both by helping build for you a CRM of a 360 view of guests where we can also send you customers inside stores, we'd love to do that. We're starting with restaurants with two products. One is called Going Out. The other is Reservations. You know, that's a big mission that we're on.

1:04:26And so we have several of these, you know, missions that I'm pretty excited about. Yes, yes. You mentioned reservations. There's a number of quite established companies in that space. And restaurants are famously, you know, they're not exactly just eager to wake up and switch all their systems, you know, one morning. So how do you plan to unseat the existing guys in reservations? Well, I think it starts with the idea that I believe that no restaurants should own their own reservations, ideally technology. It starts with that. A reservations book, we can get into super deep here, is actually quite complicated to run a book, actually.

1:05:02I mentioned earlier this idea that restaurants, North Star really should be to build regulars. But that's not how every reservation system is designed. And so I actually think the most important thing is that restaurants can have reservations on any platform, actually. That's actually what I believe. And so that's one of the main premises behind Seven Rooms too. It's that it's agnostic to who generates the demand for you. What it's trying to do is to make sure it achieves your objective function. It may be to grow profits one year, it may be to grow locations the next year, maybe to get a certain type of customer the next year, so on and so forth.

1:05:46And so I think it starts by building what's best for the merchant. And then, you know, hopefully DoorDash can make a difference, you know, too, where we just have more customers, you know, than, you know, people that play with restaurants and also more information that we can supply to these restaurants on how do you make more money to achieve whatever, you know, outcome you want. And so if we can help achieve a restaurant's objective function, you know, better than anyone else, well, then hopefully, you know, we have a seat at the table. Talk in reservations, they carved out a successful niche in high-end reservations.

1:06:22And I think about one of the beliefs that informed their products most strongly was that no-shows are terrible for restaurants. And a restaurant reservation should be like a flight reservation where you don't just get to decide you're not going to go to the restaurant. You put a little deposit. Yeah, exactly. You put a little deposit down. Do you subscribe to that philosophy? Do you think it's maybe less relevant? And they were really dealing with very high-end restaurants. Do you think it's less relevant for regular restaurants? I'm just curious what you think of that viewpoint that we're doing reservations all along was, I think, kind of one of the founding insights of Tuck.

1:06:55I think it makes a ton of sense. The implementation of the idea is what's difficult, right? And, you know, restaurants that have very limited seating and very long seatings, you know, the opportunity cost for a cancellation is very high, you know, versus a restaurant that may have infinite production capacity, if you will. So I think the implementation of the idea is what matters, but I think the idea itself makes a ton of sense. How do you, with reservations, plan to ensure that people aren't no-showing to restaurants? Well, we're working on that problem right now, but I don't think there is one thing.

1:07:34I think the first thing is we have to help you find reservations that you want to go to. I think there's a lot of room left in the space to innovate there. I don't think there's been that much innovation in that area. So discovery is almost a bigger problem. I think discovery is very difficult. I mean, how do you find out about restaurants today? I'm curious. My wife finds them on Instagram. Yeah, okay. Yeah, and I think that that's right because there are so many different sources now. Instagram is one I'm sure other social channels are another. LLMs you mentioned earlier about throwing things in there and getting something out.

1:08:09friends, I'm sure. I think it's really difficult still. When I think about no matter the sources of input, most restaurants still struggle generating their own demand. And so I think that's, so long as that's true, I think that we have a shot at making a difference. Yes. You talked about your European expansion. You just acquired Deliveroo. In what ways are the Deliveroo and DoorDash businesses different? Well, fundamentally, they're more of the same. I started with that, actually. Hence the acquisition. Instead of the, yeah. But, okay, well, we talked a lot about systems and logistics. Have you been to London?

1:08:52I'm sure you've probably been there many times. You probably know it better than I do. But it is an interesting city in that it doesn't actually have a lot of the grid-like, hub-and-spoke properties of a lot of cities. And there's a lot of reasons for that. I know we could go into the history. It's mostly age, but yes. Yeah, but well, no, no. There are other cities that are actually designed differently in other parts of Europe, actually. We can get into other countries and cities, but like age is one of them. Obviously, it's not meant to be a city where you drive a lot of vehicles. No vehicles it managed.

1:09:24But I think it's older than even a lot of other European cities. It is. Even as European cities go, it's really old. Yes, and as a result, you know, that alone makes the logistics problem very, very different. And the logistics, not just the algorithm, which I think is just one part of the system, But the signals that you'd want to collect are very, very different. You know, vehicles are very different. You know, we predominantly are non-autos in the city of London, which is very different in the States, as an example. You know, that's very different. The regulatory setup is different. It has parts that rhyme with, you know, the U.S., but as you well know, each country is slightly different, even though I guess the UK is not under the EU, but even within the EU, each country kind of has their own local version of regulation.

1:10:14That's very, very different. You know this probably better than anyone in the world. Payment processing is very different. There are many more card types in parts of Europe than, say, in the US. So industry dynamics on retail are very different. In the US, we have a fragmented retail industry that has a lot of different players. That's more concentrated in the UK? Yeah, in the UK, in Germany, in France, in a lot of European countries, actually, this is more the norm than the exception. Whereas in the US, you have maybe hundreds of different big brands that are strong in certain regions. But in Europe, that's less true.

1:10:56Those are some of the immediate differences that come to mind. A mystery to me is why the pharmacies are so much better in the UK versus the US. You go into a Boots versus you go into a CVS or Walgreens, and it's like night and day. Yeah, well, one of the things I would say, just as a standard matter, is because of the concentration. And it's really concentrated by category. You know, pharmacies can be a category. Certain apparel can be another category, et cetera, et cetera. And this is true in, you know, Australia. This is true in Germany. The standards are higher and they're more consistent of that service.

1:11:35But where in the U.S., when you have tens of thousands of supermarkets, hundreds of big brands, it's different. It's different. And then if you look even more upper funnel, say CPG, there's a lot more CPGs in the U.S. market that are competing than, say, in some of these other countries, which make things like inventory management, the SKU counts, the size of the stores, all of that, therefore, is different. Yeah. You referenced some of the stuff we're doing together. I think of Stripe and DoorDash as almost having grown up together, founded at very similar times, and then you guys were early users of all manner of products, be it to be Connect or Radar or issuing for cards or things.

1:12:17What would you like to see Stripe do that it doesn't today? Either because you guys would like to use it or just because you think it's something we should be doing? I've been giving you all my silly product suggestions. This is where you get to turn the tables and give me yours. I would always start with what our teams would say. So probably the first piece of advice always is, what problems are you solving for us? Because I think especially as companies grow in size, success, variety of products, I think there's a natural temptation to start imposing what the companies want to do or want to solve or want to sell versus say, what problem does it solve for the customer?

1:13:01So, you know, I am sure, you know, one of the things that, you know, could be true is making sure that you're solving our top problems versus just introducing, you know, the range of products. Yeah, the next thing. That's probably, you know, one thing that we probably both share as advice on one another. Oh, wow. We got Dot coming. Oh, awesome. So this is Dot? This is Dot. Well, there you go. Wow, it's kind of like a TARDIS. Oh, yeah, we were talking about, what were we talking about? One of the things I'll never forget talking to you and Patrick about as we kind of grew up together in the years of building our companies was I think you've always, both of you have always had the idea that Stripe is a technology company that happens to be in payments.

1:13:50It's not a payments company. And you've always challenged, I remember, your customers to think about, don't just think about accepting payments and there's more that you can do. So I am curious, what more can we do? Should we be doing with things like crypto or stable coins? Two topics that are on the minds of all our customers today are, yes, stablecoins and then AI specifically with respect to changing buying, you know, agentic commerce. On stablecoins, I think maybe DoorDash is not where I would start. Two places that we're seeing tons of interesting stuff is one, any kind of cross-border use case where if you want to send money to 100 countries, it's already the case that stablecoin is a much better way to do that than anything else.

1:14:39And that's where we're seeing a ton of adoption, where just that long-tail coverage, and they really work for that. The second, and this is where Tempo, our new initiative that you guys were nice enough to work with us on, is coming in, is very scalable crypto payments. And obviously agents is what we have in mind as we're developing Tempo, where if you want to pay for your API consumption or if your agent wants to be able to pay for things around the internet, you actually need a really good scalable blockchain for that. Okay, so that's all the crypto side of things. The other thing that we're thinking about a lot is just how does commerce change now that people's expectations are increasingly, they ask their AI for stuff.

1:15:26And so it feels like you should be able to ask your AI, whether that's, you know, ChatGPT or Gemini or whether that's Siri or like whatever your interface is to AI. Sure. It's like, let's just order again what we ordered on Sunday. You should be able to make that natural language query and have it take care of interfacing with DoorDash and payment and everything like that. I'm curious how you guys think about the interface changing. I mean, you've thought a lot. Do you want to, like, enable people to order within the AI apps? Do you want to have just more of a natural language input to DoorDash?

1:15:59Just how is that going to happen, given that that is presumably what people want in terms of the low-friction AI experience? Yeah, well, I think what people want is definitely low friction, but I think people also want the products to show up on time and think they want... You only get a right to do this cool UI stuff if the logistics is right. Totally, and the challenge with a product like a DoorDash is you kind of have to do the whole thing end to end, or you have to have great coordination or communication mechanisms. And so, you know, we definitely agree with you that I think there's definitely going to be a place where in the future, as these AIs develop their, whatever we want to call them, app ecosystems, relationships, I think, with, you know, companies like ourselves that can exactly what we just said, like do the jobs to be done in their regular life.

1:16:47I think that will be a source of top of funnel, you know, for us. I think the hard part is making sure that we can actually deliver on the promise. You know, sometimes in a cautionary tale of the past, you know, I remember services, you know, Google food ordering launched in, I forget, 2015 or 16. And they allowed you to order delivery, for example, from various Google services, you know, Google Maps, Google Search, et cetera. And while on the one hand, it was low friction and lots of traffic, they couldn't get the retention. And this is where we're talking about consumer businesses and retention kind of be the name of the game.

1:17:26And the reason was because they didn't know how to contact the driver. They didn't know if the driver couldn't find you, if something was taking a little bit longer, if something was out of stock. So there's a lot of things that happen after the checkout button. And I think this is one thing, you know, back to what we were talking about earlier about what is the correct UI. It's not obvious to me that it's just a chat interface, that there are, you know, all of these different components that have to be solved. And so I think, you know, the way I think about it is, okay, regardless of whatever we ship, whether it's on our own, you know, surface, other people's, you know, surfaces, are we solving the end-to-end job?

1:18:05If we are not solving the end-to-end job, it's not going to matter. Last question. What is food that you can get in other places when you visit London, when you visit some other city that you wish you could get in the Bay Area but you can't? Actually, I really like tea sandwiches. I was literally in London. Like afternoon tea? Yeah, like little cucumber sandwiches. I'm always looking for a healthy snack in the afternoon. Today I had an awesome thanks to you. Healthy snack? No, delicious, delicious, delicious. Have you done the proper afternoon tea with the three-level platters and the little cakes and everything?

1:18:41I did it once. I took my kids a couple of summers ago. That was an experience, I think, in part because it was new to me and my kids, in part because I had kids with me, playing with all the different things that they gave us. But yeah, no, I think this— Yeah, one of the things that's really interesting about some of the grocery stores, for example, in European markets is, you know, prepared meals is a massive focus, massive. And, you know, we have some of that here in the U.S., to be fair. But in London, I just found myself finding that in every store as I went to shop, you know, you would see so many.

1:19:19No, there's a few of these things that I find that are so much better back home in Ireland, the U.K., Europe. And prepared food is one of them. Like a sandwich you get in Heathrow were probably pretty good, as sound as you get in JFK. Don't, you know, don't go there. And like, you know, on a shelf, in a shop. And yeah, some of the stores we have. The cookies, obviously, much better back home. There's some delicious cookies, yeah. There's some, the teas, there's a lot more choices of teas inside restaurants, I found. Yeah, it's been, I think one of the coolest part and, you know, greatest privileges, frankly, that I have at DoorDash is, you know, because we get to interface with all the businesses, you know, of all these different wonderful cities and really like get to meet the people who are building the GDP of those cities.

1:20:08It's not just like the cool economic impact that they're having, but you get to find out about all their passion projects. You get to find out whether it's passionate about, everyone's passionate about something. And that's one of the coolest things about my job where I, I don't just, you know, you asked me a bunch of questions about, you know, different IP and process and things like this, I promise you there is that for every single business inside every city. Yeah. Yeah. It's a cool job where, yeah, you get to work with people who are incredibly passionate about what they do all day long. Yes.

1:20:37Yeah. Well, Tony, thank you. Thanks so much, John.