The Exchanges

Q Did anybody have any restaurant or, or actually not even restaurant experience, because you're not even in the restaurant, any delivery, any of the founders have anything to do with logistics or delivery, anything?

A No. No, it's actually why we had to do the deliveries. I mean, I mean, the reason why we did so, the reason why we were so hell-bent on doing the deliveries, besides the fact that we had no idea whether we had any business recruiting other drivers was, How does this work? How should it work? I think DoorDash early on, even to this day, but early on, it was so hard to explain because it was actually, even to build the MVP, yes, to test it was just this website, you know, paloelto.com, but we had to build like four things. We had to build this website for consumers. We had to build some app for the restaurants actually received the orders. We had to build an app for the drivers, the dashers, and then we had to build the dispatch system. You know, that actually could oversee all of the operations. So even in the very beginning, we realized, wow, this is actually pretty interesting. It's just such a fun problem that you, in order to actually just bring you a burrito, you have to build these four things. And then to do it really, really well, I mean, that's why we did all the deliveries to figure out how you actually do that.

AI assessment note: “No. No, it's actually why we had to do the deliveries.”

Q Was there a specific source where you were finding people like this?

A Not really. There wasn't, um, in fact, to this day, I don't really look at people's backgrounds that much. I think one of the things I discovered along the way, you know, probably in the twenty-fifteen to twenty-twenty era when, especially when DoorDash was building out its team, um, there were more attributes that I was listening for than there were things on a resume that I was seeking or looking out. A bias for action, you know, and a lot of the ways I can tell in an interview is actually just what people naturally talk to me about. You know, for example, Christopher Payne, our first Chief Operating Officer, I didn't ask him a single interview question, but after a two-hour discussion about our logistics algorithm, he went home that night, it was Friday, drove with his son for four hours doing deliveries. I didn't ask him to do that. I also didn't ask him the next morning to write me a 3000 word email about why our logistics algorithm sucks.

AI assessment note: “Not really. There wasn't, um, in fact, to this day, I don't really”

Q What do you do when the data and the anecdotes conflict?

A It's a tough one. Um, I think that, um, usually there's always an element of truth in what customers are saying, and, and it usually becomes a trade-off, you know, discussion, uh, you know, for, for different teams. The, the reason why it's a tough decision is because it is so easy to always just veer on the side of the data, because almost always When a customer notices something that is wrong, um, or, or there's an anecdote, um, uh, that may be a quote unquote edge case, it's usually at some tail of a distribution, um, a distribution of the wait times for customer support, a distribution of how friendly we were when we actually took the call, a distribution of how on time we were, or how late we were, or how accurate we were, Or what are the number of items of the types of SKUs you care about in a particular category of lettuce? Just lettuce, not vegetables, but just lettuce, right? So, it's always some tail example. And so, the data is probably always going to win when it comes to some sort of a prioritization discussion. But when you actually think about how to make a product better, It's going to almost always by definition be in improving the edges, you know, and that's why a lot of times what I like to do personally is I love to spend time, um, uh, you know, with a lot of our power users, whether it's, you know, the, the top dashers or, um, uh, the consumers who order th…

AI assessment note: “what I like to do personally is I love to spend time, um, uh, you know, with a lot of our power users”

Q What are some examples of things that customers have asked?

A Okay, so one customer in 2014, I'll never forget, was a farmer, um, who runs one of the largest farms in the state of California. And they run hundreds of trucks every day up and down the state of California, okay, distributing their produce and their meats and other products to a variety of grocers, restaurants, hotels, etc. And they, they've been doing this for three generations as a family. They did not start their farm to drive a bunch of trucks. That is not the business that they aspire to be in or passionate about. And literally, um, in our second year of operation, they called me, or they wrote in actually, and then we had a conversation on the phone about, um, what they were interested in. They were, they were curious whether we could solve that problem for them.

AI assessment note: “They were, they were curious whether we could solve that problem for them.”

Q How are you using it? What are you doing? How's it affecting your work?

A Yeah, well, um, it changes by the month. So I, I, uh, this is a, this is a question that if we were to talk, you know, in the future, I'm not sure it'd be actually the same answer. Um, well, one of the first things I would say is You know, I think about some of the systems that we've architected here about how you can learn from doing things that don't scale all the way to, um, shipping, especially with something like coding. Right now, I think where the agents are, they're, they're still good at what I call, you know, functional tasks, um, for example, coding, um, but outside of coding and looking at cross-functional areas, they're not quite there yet for a lot of reasons, but, um, But within something like coding, the things that you could do today, um, where anyone actually, frankly, it doesn't have to be anyone of any function. Anyone can come up with an idea, run the prototype, run the experimentation and the analysis, and then actually ship to a small group of people all by themselves. Um, that is Very impressive, and that collapses, if you will, you know, the amount of activity required or speeds up the learning loop you can have in any scientific process inside your company that touches code. That's very cool. Second, um, LLMs, you know, what are they good at that humans are not good at or less good at? Well, they can have almost infinite memory and infinite context and…

AI assessment note: “where anyone actually... can come up with an idea, run the prototype”

Q I've heard you talk about developing this like last mile logistics network. Did you think about that back then? Or you're just like, hey, I'm just going to try to expand the market for food delivery?

A No, we did. So the, when we started, um, I guess to take a step back before we shipped Palo AltoDelivery.com or even how we got there, You know, my co-founders and I really got connected because of an interest in small businesses. You know, I think my story I've told publicly, which is really, I mean, I grew up, ah, coming as, to the States as an immigrant from China, and my mom, um, you know, put food on the table by working three jobs a day for 12 years. One of those jobs happened to be at a Chinese restaurant where she was a waitress. I got to hang out with her, wash a few dishes when she allowed me to. That's kind of how I grew up while my dad was getting his PhD at the University of Illinois. That was, you know, the first 10 years or so of childhood growing up in the States, and that moment and experience always just gave me a deep appreciation for what small business owners represent. I mean, to them, there's no such thing as work. Work, life, it's all the same thing. There's no concept of a weekend or a Saturday. It's Saturdays and Tuesdays are exactly the same days, and you just kind of get into this process where That becomes your identity, and it's actually one of the most fascinating things I find about the great experiment that's America where, you know, because it becomes this all-consuming thing, one of the nice positive derivatives is actually they don't just cre…

AI assessment note: “No, we did. So the, when we started”