Sure. No, I think it's a great question. And the first thing I always come to when it comes to any new technology, whether it's autonomous vehicles or agentic commerce, and kind of how that interacts with LLMs, it's really how well does it solve the end-to-end job for a customer, kind of becomes the lens in which I approach all of these things. And I actually think that maybe the best way to think about this is to look a bit through history and maybe offer you a couple of examples and then maybe work our way towards the present and think about the future. So when I think about these terrific products, whichever chat assistance that you love using or just protocols with agentic commerce that you like using, I kind of view them very much as almost like the new forms of the Googles or other large kind of top-of-funnel channels, if you will. And if you think about -- I'll give you a couple of examples from history that kind of maybe touch on your question. One is, look at what happened to product search over the 2010s. You saw over time, companies like Amazon take increasing share of product search from traditional search engines because they did the end-to-end job for customers because searching to buy an item is only one task, but perhaps reading reviews or tracking the package or returning the package or any other form of customer support are also part of the end-to-end job that you have to solve for customers. And over that decade, you saw, I think, companies like Amazon and others take increasing share when it comes to something like product search. Another example that comes to mind and maybe closer to home, is something that actually Google launched was called Google Food Ordering, which they launched in, I believe it was like 2016 or something like this, where they offer the ability for restaurants to offer delivery directly through Google Maps and other Google surfaces. And look, they drove the ton of traffic, multiple fold traffic of what DoorDash could generate to these restaurants. But when you looked at the retention and the frequency of use of that channel versus companies like DoorDash, it really was a fraction of what DoorDash could provide. Why is that? Well, because after a checkout, things can happen in the physical world. For example, a driver might be late or an item might be missing or some substitution on a spoiled carton of milk needs to be made or not the exact brand of whatever produce that a customer was looking for needs to be changed. So the end-to-end job at the end of the day, I think, is how customers will ultimately judge where they do their shopping. And at the end of the day, wherever the customers keep going back to, that's where the audiences will flow and where the audiences flow so will the advertiser budgets as well as the interest along that dimension. And so when I put all this into perspective, the historical context into where I look at DoorDash today, I think, DoorDash is really well positioned because we're actually solving the end-to-end job for a customer, which is to get them some item, brought to them in the condition they expect, on time, every time. That's actually really hard to do. You got to map the physical world, all of which that information does not exist anywhere on the Internet. That's data that DoorDash has to collect in a proprietary way. You have to actually be excellent at the execution of the operations. You have to be excellent at collecting all the metadata as well for all of these different items as well as the personalization you can perform if you actually have all of the customers and all of the customer information. And I think when you put it all together, we're going to be the best place to solve the end-to-end job for customers. And so long as we are that best place, we will also attract all of the audience and all of the advertiser dollars that comes from that audience. But look, I think with respect to how that informs our partnerships with some of these AI systems, I view them as channel partners and we'll see how much traffic they can drive in a very similar way to how companies like Facebook and Google did the same for DoorDash in the past.