The Exchanges

Q is a technology company that happens to be in payments. It's not a payments company. And You know, you, you, you've always challenged, I remember, you know, um, you know, your customers to think about, don't just think about accepting payments and, you know, 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?

A Two topics that are on the minds of all our customers, uh, today are, yes, stable coins and then, uh, AI specifically with respect to changing buying, you know, agent of commerce. On stable coins, 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 a hundred countries, it's already the case that stablecoin's a much better way to do that than anything else. And that's where we're seeing a ton of adoption, where just that long tail coverage, and they, they really work for that. Um, the second, and this is where Tempo, our new, uh, initiative, That, um, you guys were nice enough to work with us on is, uh, coming in is very scalable, uh, crypto payments, and obviously agents is what we have in mind as we're, uh, developing Tempo, where, you know, 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. Ok, so that's all the, the crypto side of things. 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, and 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, lik…

AI assessment note: “Two places that we're seeing tons of interesting stuff is one, any kind of cross-border”

Q has my, uh, sort of, you know, lots of my history, and ask, is that the kind of product that I would appreciate? It would, like, it would just return yes, right? Because it's like, it solves the problem in its entirety. It's like a travel adapter, which, like, for any country, to any plug, to any other, um, all sorts of stuff, Good, good product, right? I want it.

A Okay, so we're, we're, we're getting down the road here. I mean, it feels like step one is, that's going to happen with agentic commerce is, I feel like existing aggregators, if just aggregation is their raison d'etre, then they're going to have a lot of, ah, questions that they need to answer, because ChatGPT and the AI apps end up as a new aggregation point. And so, It seems to very much benefit the tail. It benefits all the Shopify merchants, just like, you know, we had a new set of content creators emerge on YouTube that effectively compete with kind of TV. They're both just entertainment, and the tail becomes much more powerful when you have over-the-top distribution through YouTube. Similarly, it feels like once you have over-the-top distribution through AI apps, it becomes, you have a much more powerful position as a tail merchant because, you know, Momax is a tiny brand, Uh, but they can just get recommended as the best product. So that's step one that I think happens.

AI assessment note: “you have a much more powerful position as a tail merchant”

Q I think we could be, but, but I think we definitely could be. But, but again, like back to the question of, uh, of asking What problem does this solve, right? That the human is pretty good with their eyes, you know, at some of this stuff. So the bar is pretty high, you know, in order to do some of the things you're talking about.

A 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. Restaurant 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, um, 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. It's not just DoorDash. It's every product I use. It feels like those recommender capabilities are underutilized.

AI assessment note: “one thing I'm struck by is that the LLMs are pretty good recommenders”

Q Um, marketplaces slash app stores have been a thing. What comes next? You know, what happens to e-commerce in an agentic marketplace or an agentic commerce? I think these are the interesting things that need to be litigated.

A Well, I want to talk about that and I want to talk about commerce, but actually first, while we're on the topic of, while we're still in the nineties, um, everyone is making comparisons to the dot com bubble right now. It's almost a cliche. And I think it's actually a reasonable comparison, you know, it's cliche for a reason, which is, it is a very CapEx intensive build out for a new paradigm that is in fact a big deal, and yet there's an awful lot of CapEx. You were there, uh, at Microsoft, uh, during the, uh, the thousand dot com bubble, and it really was, uh, you know, Microsoft's share price peaked in the late nineties, early 2000, and then didn't surpass it until 2016, I wanna say. What did it feel like in 1999? In particular, did you know you were in a bubble, or was it like, oh, this is the new, this time it's different?

AI assessment note: “I want to talk about that and I want to talk about commerce, but actually first”