Video · 2026-07-23 · 49m · 6 moments

Building an Autonomous Delivery Experience with DoorDash Co-Founders Andy Fang and Stanley Tang

✦ AI generated

GUEST Andy Fang GUEST Stanley Tang HOST Sarah Guo HOST Elad Gil

timeline · colored by role

Data◆

Ask DoorDash's natural language interface drives significant behavior change: 50% of restaurant trajectories are from people ordering from new places, and grocery basket sizes are 40% larger.

Andy Fang shares metrics showing that Ask DoorDash's conversational interface drives discovery of new restaurants and larger grocery orders.

transcript

Andy Fang: So, I would say on the restaurant side, we are seeing people 50% of trajectories of people using Ask DoorDash for restaurants. Uh they're or 50% of those trajectories are people ordering from places they've never ordered from before, which is huge because that's one of the hardest metrics historically for DoorDash for us to uh move. And so, that's been big. And then another one is on the grocery side, we're seeing a lot higher basket sizes, like I would say like 40% larger basket sizes on grocery.

Prediction

If someone were to create DoorDash today, it would look very different — probably more agentic-first — because there is now more agent traffic on the web than human traffic.

Andy Fang speculates that a modern DoorDash would be built agent-first, reflecting the shift toward agent-driven web traffic.

transcript

Andy Fang: It's like if someone were to create DoorDash today like I don't know like college kids in a garage trying to start DoorDash I think it would look very different probably more agentic first. You know, one stat that I always like to uh think about nowadays is just like there's more agent traffic on the web than human traffic, you know, and so it's like how do we have a DoorDash type experience that plays into that trend?

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Claim◆

DoorDash's robotics journey taught them that the industry's dominant approach — building technology first and retrofitting a use case — doesn't work; they had to build their own robot because no existing form factor (sidewalk robot or rob-taxi) fit the 3-to-5-mile delivery use case.

Stanley Tang recounts DoorDash's 8-year robotics journey, explaining why they rejected the tech-first approach and built DOT from first principles to solve their specific delivery problem.

transcript

Stanley Tang: There's a lot of autonomy startups out there. Um but we it always felt like these these companies weren't really focused on a use case. It always felt like they kind of build the technology first. And then retroactively try to go find a problem to fit into. Like these these things were all built in a vacuum. Which is kind of weird cuz cuz it's it's like cuz in in in software world like when went through YC like we're always taught to oh you got to serve the customer build something people want. That's kind of like drilled into you and then you can iterate. But then when it comes to like hardware and hard tech and AI and and robotics, it's see it's people just kind of do the opposite where they try to build the tech first and and and not really think about the use case they're building towards and whenever that happens, you just end up with something that just wasn't quite the right fit.

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Context

DoorDash's physical-world complexity — 3 billion diverse deliveries per year across different geographies, merchant types, and order types — gives them an insurmountable data advantage for building autonomy that no outsider can replicate.

Stanley Tang explains that the sheer variety and scale of DoorDash's delivery operations creates proprietary data and operational insights that competitors cannot access.

transcript

Stanley Tang: I think one of the things I think people don't realize is just how complicated DoorDash is. I mean, we do what over 3 billion deliveries a year. There are no two deliveries that look the same. All three billion deliveries look look different. Uh, and they all come in all sorts of shapes and sizes and different geographies. like a delivery in downtown San Francisco is completely different than uh a delivery done in Dallas or or or even in Europe or in Helsinki where it's snowing or if you're doing a uh pizza is very different than ice cream like your your dinner is very different than your grocery order which is very different now that we're expanding to retail and and and pharmacy and parcels as well. It's like the diversity of deliveries that happen at DoorDash is so complex that I I think people sometimes don't realize just how nuanced the problem the problem the problem is.

Mechanism

Scaling autonomous delivery requires solving three problems in sequence: first autonomy (now solvable), then operations and fleet management, then hardware manufacturing — and DoorDash is uniquely positioned to tackle all three because of its operational scale.

Stanley Tang describes the three-phase challenge of scaling DOT from 100 to 10,000+ robots, noting that autonomy is no longer the bottleneck — operations and hardware manufacturing are now the hard problems.

transcript

Stanley Tang: I think it's really three three components is can we get the autonomy to scale 5 years ago the question was like was autonomy even possible like was this was this just a research project is this a science fiction um you see kind of Now with especially with AI like Whimo's kind of made that breakthrough. I think Tesla's starting to make that breakthrough. We made that breakthrough last year. Um like our entire autonomy stack is built in-house but purpose built for for delivery which is again it's a little bit different. ... the autonomy is probably increasingly becoming less and less of a constraint of of a blocker. It's really like now how do you it's really more the next two which is um the second is like operational like how do you scale operations ... and then the last piece is is is hardware like how and it's kind Funny. It's like when we first started like 5 years ago, like everyone thought hardware was a commodity and now it's starting to look like hardware is starting to become bottleneck.

Prediction

In 10 years, DoorDash will have more human Dashers, not fewer, because the business is growing 25% year-over-year and demand will surge as autonomous delivery makes ordering cheaper and more accessible.

Stanley Tang predicts that despite — and even because of — autonomy and robotics, DoorDash will employ more human Dashers in 10 years due to business growth and demand elasticity from cheaper delivery.

transcript

Stanley Tang: My guess is that in 10 years time, we're actually going to have more Dashers doing doing deliveries, not less. uh simply just because again I think it's just the well one I think the pace at which DoorDash is growing is just I mean and the scale at which we're operating is is pretty insane. I I don't know if people know, but like we have over 9 million dashers doing deliveries and the business is growing 25% year-over-year. Like fast forward 10 years time, like like and if we want to 5x from here, 10x from here, well, where are the where's the supply going to come from? ... I think you're going to see a world where we're going to have this multimodal fleet like we're going to need our hand get our hands on every single modality we can get. So, I think you're not only going to see more autonomy and more robotics, but I think you're going to see even more humans as well.

gives example · 1rebuts · 1

Highlight slides

Ask DoorDash drives discovery and upsizing✦ from: Ask DoorDash's natural language interface drives significant behavior change: 50% of restaurant trajectories are from people ordering from new places, and grocery basket sizes are 40% larger.Grocery basket sizes jump 40%✦ from: Ask DoorDash's natural language interface drives significant behavior change: 50% of restaurant trajectories are from people ordering from new places, and grocery basket sizes are 40% larger.DoorDash Rejected the Tech-First Robotics Approach✦ from: DoorDash's robotics journey taught them that the industry's dominant approach — building technology first and retrofitting a use case — doesn't work; they had to build their own robot because no existing form factor (sidewalk robot or rob-taxi) fit the 3-to-5-mile delivery use case.No Existing Robot Fit the 3-to-5-Mile Delivery✦ from: DoorDash's robotics journey taught them that the industry's dominant approach — building technology first and retrofitting a use case — doesn't work; they had to build their own robot because no existing form factor (sidewalk robot or rob-taxi) fit the 3-to-5-mile delivery use case.

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