The Frontier with Brendan Foody
00:05:14 · Andy Fang, Brendan Foody
[00:05:14] S1: Not like because we planned it that way, but I feel like our vision was always pretty consistent, actually. Like our vision, and I think Tony's um YC pitch is actually on YouTube, but like the pitch was always we wanted to be like the logistics network for your city, for your neighborhood. We wanted to like we I think Tony said we wanted to be the FedEx for local. And I think that was something where even though we started in restaurants, we were always very keen on kind of generalizing it and scaling it to something much bigger than that. And I think even our mission statement of empower local economies was something that was very consistent from our early days. But it's not like we planned it that way, it just happened to be very consistent. Even before we landed on delivery, we were still toying with things in the local commerce space. We interviewed like hundreds of merchants in the Bay Area just to see, like, as part of our class project, to see like, hey, what are problems that local merchants have? And you know, that's kind of how we stumbled on the delivery issue. [00:06:07] S0: And what was it that drew you to that problem specifically?
00:06:07 · Brendan Foody, Andy Fang
[00:06:07] S0: And what was it that drew you to that problem specifically? [00:06:11] S1: We still remember this. It was an interview we did with a local macaroon shop. And the store manager, she was like, I have this book of delivery orders that I can't fulfill. I have to turn them away. And we thought that was crazy because it's like, you know, for a local restaurant or store, it's like everybody's looking for sales, and like for you to turn away sales was a crazy idea for us. But then when we dug like one level lower, we're like, well, the only way for you to get these fulfilled is either pay 50 bucks for like a local courier or you do it yourself. And so that's kind of how we just stumbled upon the idea. [00:06:41] S0: Roughly 15 years later, almost that now, you guys have transformed DoorDash into a really category-defining company. And I'm curious how that mission continues to play a role in the AI economy that's emerging and how it's transforming commerce and the whole way the economy works and what role you see DoorDash playing in that.
00:06:41 · Brendan Foody, Andy Fang
[00:06:41] S0: Roughly 15 years later, almost that now, you guys have transformed DoorDash into a really category-defining company. And I'm curious how that mission continues to play a role in the AI economy that's emerging and how it's transforming commerce and the whole way the economy works and what role you see DoorDash playing in that. [00:07:04] S1: I mean, to be honest with you, I think we're all just learning and exploring here. And I think one thing that we're very keen on is learning more about agentic commerce and exploring like what that can look like and how like commerce isn't getting transformed. And I think we've done a ton of explorations in the space. I mean, when I first visited you, I think we were very keen on understanding how do we get these agents to like do what we want it to do. And then you were teaching me about evals and stuff and like kind of the nuances there. And I think for us, that's kind of how we landed on you know iterating in the space. And we launched Ask DoorDash a couple weeks ago. And that's been a very, very promising product for us. I guess the first vector there is seeing how we can introduce this type of agentique experience into the core product. And we're very fortunate that this product that we're rolling out has seen a ton of um early success.
00:07:04 · Andy Fang, Brendan Foody
[00:07:04] S1: I mean, to be honest with you, I think we're all just learning and exploring here. And I think one thing that we're very keen on is learning more about agentic commerce and exploring like what that can look like and how like commerce isn't getting transformed. And I think we've done a ton of explorations in the space. I mean, when I first visited you, I think we were very keen on understanding how do we get these agents to like do what we want it to do. And then you were teaching me about evals and stuff and like kind of the nuances there. And I think for us, that's kind of how we landed on you know iterating in the space. And we launched Ask DoorDash a couple weeks ago. And that's been a very, very promising product for us. I guess the first vector there is seeing how we can introduce this type of agentique experience into the core product. And we're very fortunate that this product that we're rolling out has seen a ton of um early success. [00:07:54] S0: I remember I would often like be looking for something on DoorDash and spend five to ten minutes looking around. And I've started using Ask DoorDash. And so I'm really nice, excited about all the progress there. Yeah. How do you see that evolving? Like if everything goes well with Ask DoorDash and the variations on that product direction over the next five years, what will the future look like for DoorDash customers and more broadly?
00:08:17 · Andy Fang
[00:08:17] S1: I mean, five years, I have no idea what things are gonna look like. But even just like thinking like six to 12 months out for a sec. I mean, I think what we're seeing in the early rollout is like, you know, we're seeing our grocery basket sizes are like, I think 40% larger, which is like a number that's been really hard for us to move historically. And then on the restaurant side, we're seeing like 50% of conversations of people in Ask DoorDash there are ordering from restaurants they've never ordered from before. And so these what we call new merchant trials at DoorDash. And that's also been a very hard metric for us to move. Um, and so for us to see that type of impact in this early rollout and see it sustain as we've been increasing the rollout size, that's very exciting. But I think one thing that we've been so caught up on the past couple quarters is like, how do we get the intelligence to be good enough? Once we felt like the intelligence is good enough, now the question is how do we actually make it easier for people to get introduced to the experience and know what to do inside the experience? Because I think a lot of times, like if people just see like a chat box uh and they're like, okay, like what do I enter or what do I type into this? It's can be a little intimidating. But what we're seeing is like people who engage with it, we're seeing really promising results. So we're trying to figure out ways to make that a little less intimidating.
00:09:26 · Brendan Foody, Andy Fang
[00:09:26] S0: When you talk about the intelligence being good enough, are you guys using closed source models under the hood or open source? And how are you seeing that evolving? [00:09:33] S1: Primarily we're using closed source, but we are using some like open weight models for like some like tool calls. But I would say like the primary intelligence of the agent is through closed weight models right now. [00:09:46] S0: Especially for like search over a giant catalog is actually a really surprisingly challenging problem. That exactly I agree that mainly the distribution is strong in the uh closed source models, but not yet the open source ones. One thing I've been thinking about a lot is that right now the these agents are mainly reactive. If we go to and we say we want a high protein meal, and then we're able to get that. And over time they'll start to become more proactive, right? Where it might identify what are the things that you might want to buy in the future, paying you around the time that you usually order dinner, all that kind of stuff. Yes. How are you thinking about that future developing? Definitely.