Dara Khosrowshahi on replacing Uber drivers — and himself — with AI

Support for Decoder comes from Adobe. Life is unpredictable, and that means you need your projects to adapt with whatever gets thrown at you. That means mastering the ability to pivot and collaborate with others to reach your goals. Adobe gets that, which is why they made a tool that's just as flexible as you are, PDF spaces and Acrobat. Your PDF files are no longer static. Instead, they're living documents that flex with you and your project's needs. Learn more at adobe.com/do-that-with-acrobat. Support for the show comes from Hostinger. Ever had an idea for a business or side hustle, but never actually launched it? With Hostinger, you can turn that idea into something real in minutes, instead of weeks. Hostinger is an all-in-one platform that brings everything into one place. Your domain, website, email marketing, AI tools, and AI agents. You can create websites, online stores, and custom apps with simple prompts. Then use AI agents to automate tedious tasks and grow your business. Go to hostinger.com/decoder to bring your idea online for under $3 a month. Use promo code decoder for an extra 20% off. Support for today's show comes from CNN. Do you wanna live forever? Influential journalist Kara Swisher is taking a hard look at the longevity industry to separate the influencer hype from evidence-backed science. In her new CNN original series, Kara's talking to Silicon Valley power players and trying out the latest in anti-aging technology to see what works and what's a waste. Kara Swisher wants to live forever. New episodes streaming Sundays with a CNN subscription. Go to cnn.com/subscribe to start watching. Hello, and welcome to Decoder. I'm Nilay Patel, editor-in-chief of The Verge, and Decoder is my show about big ideas and other problems. Today I'm talking with Uber CEO Dara Khosrowshahi. It's become something of an annual tradition to have Dara join us in the studio when he comes to New York for Uber's big Go Get event every year. And it's always a lot of fun. The big news this year is that Dara is really starting to think about Uber as a much larger platform for travel, starting with the ability to book hotels in the Uber app. Thanks to a partnership with Expedia. There's also new services, like being able to have coffee and snacks waiting in your Uber when it arrives, and even personal shopping. Uber is going so far as to call itself an everything app now. So I wanted to see how far Dara thinks everything actually goes, and whether he's feeling pressure to own more of the user experience in a world where AI companies keep promising that their chatbots will book all the cars and hotels for you. I also wanted to know if these chatbots have created any opportunities for Uber. Last year, Dara told me he was wide open to partnerships with AI companies just to see if they were meaningful. But all the AI-Uber integrations I've seen so far have been pretty clunky and far slower than just using the app myself. So we dug into what Dara is seeing there, and if he sees any potential in the future. I've also been dying to talk to software CEOs about what AI is doing inside their companies. It's AI coding tools and agentic systems up-end software development. Just a couple of weeks ago, Uber's CTO said the company had already burned through its entire token budget for the year by the start of April. And Dara told me he was starting to rethink how fast the company would hire people as it spent more money on tokens. That's a big bet. And I wanted to know if Dara was also rethinking how his software teams were structured as AI starts to muddle the relationship between product managers, designers, and engineers. Lastly, we talked about Uber's increasingly large investments in autonomous cars, especially its big investment in Rivian, and what kinds of milestones Dara's looking for as the technology evolves. I also wanted to know what happens to all of Uber's drivers in a future where robots are doing all that work. Of course, that means I also asked Dara when he thinks AI will be ready to replace him as CEO. It turns out there's already a rogue AI Dara operating inside of Uber. There's a lot going on in this one. Dara was as clear and candid as ever, and I think you're gonna like it. Okay, Uber CEO Dara Khosrowshahi. Here we go. Dara Khosrowshahi, the CEO of Uber, welcome back to Decoder. Thank you very much. Good to be back. I'm happy to have you. It's like a yearly tradition. You guys do your go-get event, you have a bunch of news, and then you come down to where we are. Chock full of news for you. Chock full of news. And we hang out together in person, which is my very favorite thing. So thank you for doing it. There's a lot of news to talk about. As I was telling you just before we started, I'm very curious what it means to run a software company in 2026 in the age of AI coding agents. And I'm very curious if you're gonna have 6,000 people report directly to you, as Jack Dorsey has said. So I wanna ask about all that. I wanna talk about the news, which you can now book hotels and other experiences in the Uber app, which is a big deal. But I always ask everybody the same two decoder questions about how companies are structured and decision-making. And I just wanna do them as a little lightning round at the top. Sure. So last year on Decoder, I said, how do you make decisions? And you gave me the Amazon answer. You said one-way doors and two-way doors. A lot of pressure on decision-making lately. We're making big decisions. Even expanding the app is a big decision. Has your fundamental framework changed? Fundamental framework has not changed. Now, I will tell you that I am pushing the company in something that we talk about taking smart risks. The pattern that I keep seeing is that as companies get larger, they become more hesitant in terms of risk-taking. You know, it's more about playing it safe. It's you're a public company. You have to hit your quarterly numbers, et cetera. And to some extent, as companies get larger, they get more resilient. They can actually make bigger mistakes. And, you know, for us, we've got almost $10 billion in cash flow. And, you know, when I first joined, if we made a billion-dollar mistake, it would be a disaster, right? It would put the company on its knees. And I'm not saying that I want to make a billion-dollar mistake, but the risks that we have to take in order to get the right return, in order to keep innovating in the world, you know, for example, with AV, which I'm sure we'll talk about, are getting bigger. And we have to be willing to take those risks. And the patterning that I've seen with a lot of companies is that as they get bigger, they get more conservative. The way they operate gets more set in stone. You have more management layers, et cetera. And we very much want to avoid that. And it's taking me really pushing kind of one-way doors, two-way doors as one framework of looking at decisions, but then smart risk-taking as well. We've got to keep taking smart risks as a company. It means once in a while taking risks that in hindsight look dumb, but we've got to push the envelope, especially during this time when there's so much innovation going on. Risks, everyone likes to talk about it, but taking the blame for when things fail is like the other part of risk. It's the other side of the coin. Also getting, empowering people to take the risk without that fear of failure, really important. How do you think about the stakes? Like how big of a risk is an individual software engineer in Uber allowed to take? So I think as long as you can identify the downside of a risk, if you can't identify the downside, don't take the risk, right? But if you can identify the downside, whether it's time that you're spending on a feature, whether it's compute that you're dedicating to a feature, or you've got to invest a certain amount of capital in building something or going after expanding a new line of business in a country. We're launching Uber Eats in seven countries in Europe as well. As long as you can identify the downside, then you can make the right calculus in terms of whether you should take the risk or not. We absolutely, you know, we want to learn from our mistakes. Like we don't, there's this, some people talk about celebrating mistakes. Like I'm not going to celebrate a mistake, right? But I do want to be able to make sure that I learn from a mistake so that the next decision I make can be incrementally better. That's usually the construct that we use. I think sometimes we over-examine our mistakes and, you know, we have meetings, we talk about it, we document the issues, what we did wrong, what could have gone better. I'm honestly not a big fan of that. It's a big engineering thing, etc. Is, hey, understand why you made a mistake, what you could have done better, and then move on with life. Like, let's go build the next thing. Put this into practice for me. What's a risk that came outside of your sphere of management control that worked out? And what's one that didn't? So one that absolutely worked out, for example, I was involved with, but it was the team that really pushed for it, was women riders and drivers preferred. There was some question as to the liquidity in the marketplace. Anytime, you know, one of the big things about Uber is, you know, push a button, you get a car in four to five minutes. There was a question as to whether or not we would have enough women drivers to introduce this feature for women riders. Because if you introduce a feature, Kind of adjust the way that we've built the product for Taxis. Taxis is now one of our fastest growing products. So that's an example also of like, you make a mistake once, but then actually, sometimes you have to try things again, even though it didn't work for the first time, with a different flavor, with a different approach. And I'm really glad that we took that shot on Taxi. We're gonna come back to risk, because you have a bunch of new products that seem risky. I'm gonna ask you the other decoder question about the structure. Last time you were here, I felt like I could have talked to you about the structure of Uber for the entire conversation. You had a wild answer. It was very lengthy. I encourage people to go back to listen to that part of the conversation. But the short version is, you said, quote, we have a combination matrix and line of business structure. You have global leads for mobility and delivery, and then everything else is matrixed. And importantly, the thing that you had changed was you had made product a central function. You didn't have separate product teams for each in the ride business. Obviously, I'm guessing something has changed here because you have many new lines of business. You have an autonomy division. Quickly describe how Uber's structure has changed. The only change in structure, because I do value stability, is that I now have a president COO, Andrew McDonald. And that was about Andrew ran our mobility global business. What we observed is that the platform, that is mobility and delivery coming together, and particularly users who use both mobility and delivery, has been growing much, much faster than the individual use cases of mobility and delivery. And it was always my hypothesis, one of the visions that I had coming to Uber was that once we have the delivery business post-COVID grow so quickly and show that it has the potential of being just as big as the mobility business, I had a hypothesis, which is, you know, we compete against mobility players and we compete against delivery pure play players. You could have a hypothesis, which is actually being a pure play could be an advantage, right? It's all lift. The only thing lift cares about, at least historically, was U.S. ride share. They're starting to expand internationally as well. Good for them. About time, you could argue. And the only thing DoorDash cares about, let's say, is food delivery. We're trying to do both, right? And it's hard as a company to do multiple things at once, to have skill sets in multiple business lines. And so to make up for that, we had mobility team, delivery team. We had a bunch of common structures and services platform. So where it came together was the technology platform. We started really pushing this idea of consumer side platform, driver side platform, to the extent we could get consumers to use both rides and eats. We had a hypothesis that we would retain them for longer. It turns out not only is the retention better, but they spend much more. Multi-platform consumers spend three times single line consumers as well. We launched the Uber One membership. Now almost to 50 million members, growing really, really quickly. They spend three times more. And they tend to be multi-platform versus single platform as well. And that we thought could be our secret sauce. That could differentiate us from the monoline players and allow us to acquire more customers, bring them into the platform, get them to use more stuff, have better retention, et cetera. Sounded great, but the P&L often got in the way, right? It's every pixel, it sounds easy. Well, let's use on mobility. Let's cross promote delivery as well. Sounds easy. But that delivery pixel on the mobility app could be taking away from your mobility experience as well. And also could be costing mobility. It's P&L. You know, I'm sending a customer over to do something else. So sometimes the P&L got in the way. And you know, I do a lot of stuff. And I was pushing platform kind of on the side here. In addition to everything else I do, I really wanted one member of our management team, and Andrew McDonald's been here, you know, he's one of the longest tenured employees and most capable team members that we have. I said, Andrew, it's time for you to move from running global mobility to actually become president and CEO of the company and think about the platform as a whole. It's been a big success and it frees me up to work more directly with the product and tech teams. So it's kind of a double benefit for me, but the platform is really starting to sing. The number of consumers using both rides and eats has six X in the past five years. And it's growing 50% faster than our general audience. So it's definitely, definitely working and I want to lean into it. Yeah. It strikes me just as, as you're talking here that you're, you're describing everything in terms of trade-offs, even risk. You're describing in terms of trade-offs. Everything's a trade-off. We might, we might use this compute instead of doing this other thing and putting a pixel on this screen might take a customer away from this line of business. Totally. And so you've installed the COO just to manage that trade-off more holistically. Yeah. He negotiates the trade-offs on the ground. He's ultimately responsible for one number, if you want to call that, whether it's a customer happiness or that it's a P&L and obviously often you have to manage for all of the above. I, you know, my joke on the show constantly is if you told me your org chart, I can tell you 80% of your problems. You know, it's like all the companies are kind of the same and I can get to about 80% of the tension. If you just tell me where all the executives are lined up and who controls what budget, like Kevin Scott at Microsoft is the CTO once was the person in charge of distributing the GPUs. And I was like, that's all I need to know. Like I, I know almost everything about Microsoft at this moment in time. Now it seems much more complicated for a variety of reasons, but at that moment I could just tell. It sounds like, and obviously the secret is in the last 20%. It sounds like you've installed an executive just to oversee the 20% of the prioritization and the trade-offs here. It's the 20% of the prioritization of the trade-offs, but you could argue it's our most important 20%. It's a 20% that no one else has. And in one year, the 20% doesn't really matter. But when you compound it over five years, over 10 years, you get the results that we've gotten, which is generally we've grown faster than our competitors and we're able to be more profitable than our competitors. That's the power of the platform. And I really want to lead in. At some point it was getting up to a scale where it wasn't a part-time job. I needed someone really focused on the whole thing. So the news here in that context feels like, oh, we're going to bet on the platform more. We have bet on platform for the past five years. It's a vision that we've always had. It's working. And when something works, you want to double down. OK, I'm going to be very reductive here, though. The last time you were here, I described Uber as a magic button that made a Toyota Highlander appear in my life. Wherever I am in the world, statistically, Something like a Toyota Highlander would show up. A Toyota Highlander is going to arrive. That's great. And then it's going to move me around. And the jump from there to the Toyota Highlander has food in it is reasonably small. It's a career service is reasonably small. We're moving things around. We're a logistics business. The news here is you're doing hotel booking in partnership with Expedia. You've got shopping assistants. Now the cars might have coffee in them. We got a lot going on. This is far beyond logistics for a platform that was pretty much organized around logistics. Tell me about that in the context of risk and trade-offs and platform bet. Yeah, absolutely. So first I would say, and these are different kinds of bets that we're making. And by the way, not all of them are going to succeed. And if they do, we're being too conservative. I expect some of this stuff not to work. Hopefully most of it will. One that I'm quite confident that's going to work is actually travel and hotel bookings. In that Uber is already, is very highly used by the global traveler, right? We operate in more than 70 countries. Often what's the first thing that you do when you arrive in an airport in a city other than a home city, you open the Uber app. And part of what we announced is usually that Uber app is kind of the same app regardless of the context that you have. If you think about it, when you open Uber at home, and we know, you know, you're in your home city, that should be a different experience if you've just landed in Paris and you open Uber, right? It's like, that's a different context. So for example, we have what's called travel mode. You open up the app and we first give you step-by-step instructions as to how to get to an Uber and how, you know, how long is the walk going to take? How long is the pickup? What are typical rides? We make it context aware, so to speak. And we give you highlights on what's going on in Paris. Lots of good stuff. Now, the sheer numbers that we've got, which is we have over a hundred million of our riders now are taking rides to and from airports every single year. A hundred million. That's a huge audience. We do 1.5 billion trips a year outside of your home city. So On-demand transportation to transportation by appointment, for example. So the first step that we took was actually Uber Reserve, probably three, four years ago. And if you remember, we used to have an old reserve product where you would reserve an Uber, but we would be hacking it in the backend. You wouldn't actually reserve an Uber. We would then call the Uber on demand when we thought that it could get to you by that reservation time. It was okay, but it didn't get you the reliability that you needed. It wasn't a guaranteed reservation, so to speak. So we took the signal, which is some people were trying the product, but it wasn't that good, to be honest. We said, listen, what if we really upped the reliability game and we sent the dispatch to drivers in advance? We did some research. Drivers are like, hey, I like knowing what my next day is going to be like. So it was good for drivers. We were able to charge a premium, give it to the driver, essentially to up reliability. And we started building the habit of this is an on-demand service to actually, this is more than an on-demand service. And I'm going to think about scheduling things in my life often having to do with travel. Now, what we're finding is actually some people are hacking reserve, if you want to call it that, for reliability. So if you're in Westchester County in Armonk and the liquidity for Uber is lower, you may not want to use on-demand for your commute, but you can use reserve for your commute as well. So what started as, let's try this for travel, is now being used to hack reliability to some extent. That insight of reserve building, and we've been at it for four to five years. You know, reliability is not perfect, perfect, but it's 99% now. And we're always kind of working that trade-off between reliability and price because we want the price premium to be as low as possible, but you can't lose too much reliability. That insight led us to believing that you actually can move from on-demand to scheduled. And the offerings, the Uber One kind of discounts, we think will hopefully over a period of time change behavior. So you actually come to Uber to reserve your booking in advance. We don't think this is going to be a last-minute thing. Like, if you get to a city and you don't have a hotel, I mean, there is something wrong. Maybe it'll be there on a cancellation basis, but we are trying to drive reservation behavior and we've demonstrated previously that we can. Yeah. I feel like hardcore travelers who know to reserve an Uber, who are some of your best customers, they like price shopping hotels. Yes. Totally. There's a lot of credit card points in the world. My sister's a credit card points person. Yes. It's frankly a little terrifying, but she's really good at it. How are you going to compete with that? Because that is the, that's the customer. In my mind, the customer who knows to book a hotel in Uber is also the person with five different credit cards trying to get the best deal. And they know that this portal is where they need to go this time. How do you compete with that? So I actually, I had an earlier interview with the points guy and I asked him, what's the best credit card for travel? Because I was curious. Yeah. It turns out Amex Platinum, according to the points guy, is the best credit card for travel. And by the way, I don't believe you because this worked out too well. I'm just letting you know, this worked out too well. It was amazing. And we have a great relationship with Amex where you get benefits and free bookings on Ubers as well. So it's actually, there's a lot of layering that we're doing. If you've got Delta SkyMiles, you can get Delta SkyMiles for booking on Uber. We have a relationship with Marriott Bonvoy. We've got travelers using Uber all the time. We've got the Amex Platinum card, the best card for travelers as well. So I think we have kind of the right elements coming together to get some percentage of our Uber One members to try the booking experience. And then we'll go from there. And I do think that this would be a failure if it ends with hotel booking. You know, one of the pieces of magic that Uber brings is, it's actually the backend experience. You know, one of my learnings when I was at Expedia, it was basically a booking, you know, after the booking, there weren't that many services that Expedia offered other than if something went wrong and you know, you do everything you can to, to help the customer. But actually what we can do is kind of connect all these logistical elements of your travel. So obviously, you know, your Uber to the airport, if you did that with hotel booking, we already know where your Uber is. Maybe we'll give you a discount to the hotel. And I'm hoping that as we build out travel, we can actually improve the in-market experience. I don't know about you, but like, why do I need to check into a hotel? Like, what's the deal with that? Right. Like, you know, I've got my phone and if you have a hotel booking, like maybe you can walk into the hotel and we give you all the information and you can just go up to your room and maybe your app can act as a key, et cetera. There's a lot more that we want to do in terms of the in-market experience. And it's something that Uber is uniquely positioned to do because we're already in market in almost every city that you're going to want to travel to. There are competitors in these markets. Expedia is an interesting partner because you used to be the CEO of Expedia. Yeah. So you just made a phone call and said, Hey, what's up? It's me. So actually I had to recuse myself from the process entirely. The idea, the strategy, let's get deeper into travel. Obviously I was, I was involved with, but because of the conflict, I'm still on the Expedia board. I had to recuse myself from the process. The team ran it and I'm like, guys, what's going on? They're like, we can't talk to you. So they got to Expedia won because of the great job that that team did. They got no help from me. I'm sorry. The CEO of Expedia wasn't like, I got a board member breathing down my neck. It wasn't. I had to like recuse myself from those discussions. It was a little awkward, but it all worked out well. So obviously Expedia would be a competitor, but they're your partner. There are other competitors. There are the hotel loyalty programs. Booking.com exists. They say the same sorts of things that you say. Of course. They've been on the show saying literally the same sorts of things. Connect the trip, I think they talk about, right? All the time. Yeah. Why do you need a hotel? So I think a lot of people like checking into the hotel. The free water especially is very useful when you arrive at a new hotel. That piece of the puzzle where you're going to connect everybody's backend systems together and build one unified experience where the Uber app is the primary interface. I could abstract that away and say, well, that's everything. That's what OpenAI would like to do. That's what Google would like to do. Sure. Why is Uber going to win that fight? Well, I think it's a different question or service offering in terms of offering the availability of the service, but to the extent that you can actually deliver it in market. OpenAI is an incredible company. They build a lot of cool things, but they, they don't live in the probabilistic real world that we live in. You know, it's a, there's a Mike Tyson saying is like everything is theory until you get punched in the face. Everyone has a plan until you get punched in the face. Everyone has a plan to get. And, you know, we get punched in the face daily, which is drivers are canceling, riders are having issues, et cetera. Deliveries are late. And so we already deal with this probabilistic world on the backend where things go wrong all the time. And it's one thing to try to chain all of these events together, but, and, and get the logistics right. But to adjust to real world traffic conditions, cancellations, road closures, all of that stuff we do daily. So I just think we're, we're much better equipped to actually fulfill this seamless, delightful end-to-end experience from planning to booking, making it incredibly easy, and then to delivery, the actual experience on the ground. You know, your partnership with Marriott, for example, Marriott wants those to be their customers. You're the app that everyone's doing everything in that relationship gets intermediated. Is that attention? I mean, it's, it's a tension at the same time. It's a tension that everyone deals with, right? Marriott competes with Expedia to some extent, you could argue that they compete with us, although we're a much smaller player today in travel. Maybe we'll get bigger. We work with Starbucks at Uber Eats. And of course they'd rather have people come direct to their app, but the fact is that Uber Eats brings them a lot of incremental demand as well. So this coopetition theme is something that many, many players have been comfortable with for many, many years. Comfortable with for many, many years is in one context, right? Everybody has an app and it doesn't really matter. You're all going to open the apps and maybe we can get you to open our app. Now you're in a world where you're going to open an app and maybe an agent's going to go off and do something for you. And the idea of being the everything app in that context, Uber is describing this as a step to being an everything app. It's in the press materials. Yeah You know, all of these businesses have been built organically. So I think there is kind of a builder mindset at Uber and we're going to give it a shot. And so far, the signal is pretty, pretty damn good. We have to pause here for a quick break. We'll be right back. Support for the show comes from Upwork. Think of the fastest growing businesses you know. You might think they've gotten where they're at just by doing more, but that's not always the case. Chances are they're just delegating smarter. Upwork helps you bring in expert freelance help fast so you can delegate and keep moving. Upwork is a one-stop platform to find, hire, and pay expert freelancers. Find specialized talent across web and software development, data and analytics, marketing, business operations, and more. Upwork also has business plus, which gives you access to the top 1% of talent on their platform. With AI powered shortlisting, you get matched to the right freelancer in under six hours. No endless searching required. And when it comes down to contracts and payments, don't sweat it because Upwork has the operational stuff covered. It's free to sign up and posting a job is easy. Visit Upwork.com right now and post your job for free. That's Upwork.com to connect with top talent ready to help your business grow. That's U-P-W-O-R-K.com. Upwork.com. Support for Decoder comes from Adobe. For every big idea, your documents folder tells a story. Let's say you've just finished pulling together a brief, so you hit export on final version .pdf. But then you open the file and you immediately notice a typo. Several versions later, you're exporting final V4.actual.finaldraft.pdf. Adobe Acrobat can save you the digital clutter with PDF spaces. It takes your documents and turns them into a living project that you can engage with, get insights from, and collaborate with others on. You can gather all your files into one workspace and have a whole conversation with your AI assistants about it, and ask questions to get deep insights about your project. You can even invite people to your PDF space and let them add files, comments, notes, and more. You could doodle in the margins or even turn your project into your own personal podcast episode. Acrobat lets you generate an audio overview of your project in just one click. Learn more at adobe.com slash do that with Acrobat. Support for this show comes from Doppeld. Maybe that ping you just got is an urgent message from your CEO, or maybe it's a deepfake trying to target your business. Doppeld is the AI native social engineering defense platform fighting back against impersonation and manipulation. As attackers turned to AI to power increasingly sophisticated strikes, Doppeld uses it to fight back. Their digital risk management dismantles attacker infrastructure while human risk management builds team resilience through simulation and training. With automated takedowns, multi-channel coverage, and AI defenses that build intelligence with every fight, Doppeld works relentlessly to protect people, brands, and trust. Doppeld, outpacing what's next in social engineering. Learn more at doppeld.com. That's D-O-P-P-E-L.com. Welcome back. I'm talking with Uber CEO Dara Khosrowshahi about how everyone seems to want their agentic AI to call you an Uber, and why that's maybe not such a great idea. Last time you were on the show, we talked a lot about agents and accessing Uber as a service inside of an agentic workflow. I will tell you, I asked a lot of CEOs that time this question. Everybody who had a physical product was like, we'll be fine. And then it was Amazon, who has an interface to a bunch of drop shippers, that is like filing the lawsuits. They have a virtual product. Everybody who is in the world of atoms was like, go ahead and try. Like, try to make another Uber. You just give it a shot. We'll be here when you're waiting. That was very much your attitude. What you said to me was the price of calling an Uber in ChatGPT should be zero until they prove it's valuable. And then I'll figure out what the rate should be. It's been a year. Have you seen any meaningful uptake of calling Ubers from ChatGPT? No, no. And it doesn't seem to be, at this point, a priority for a lot of the foundation model companies, whether it's ChatGPT or Gemini. I think they're experimenting with it. But I think, you know, the enterprise market is growing much faster than anyone thought that it was going to. So I think there's been a pivot towards enterprise. And by the way, rightly so, based on the growth rates that we see, based on our internal usage of these foundation models. So at this point, that part of the market hasn't developed. And the cool thing is, we're building some really cool products. You know, you can scribble a shopping list. You can take a picture of food that either looks really tasty, and we'll put together a shopping list for you. If you tell us what merchant you want to go shopping at, we'll put together the list for you and we'll get it delivered automatically. So a lot of these experiences that I think people thought you'd find on OpenAI, et cetera, you're actually going to find first on an Uber. I wouldn't be surprised if it's built over a period of time. But right now, enterprise is coming first and you could argue rightly so. Uber is a favorite of agentic demos. You pop up all the time. I'm just going to go down the list. Is that right? Yeah. It's kind of an everyday use case. It's great. Google and Samsung announced Gemini task integration on the newest Samsung phones where the model will literally open the Uber app in the background in a virtual container and click around it to get you a car. Have you seen any meaningful rides from that integration? Not yet. Not yet, but we'd be delighted to see it. I mean, we want to bring more experimentation, more opportunity for our drivers. It's just really small now. It doesn't mean it's not going to be big 10 years from now. We had a whole year of these demos. Totally, totally. Alexa. Has Alexa sent you any meaningful rides? No. Small. Very, very small. Okay, and I can keep going, but it seems like the answer... Have you used any of these products? I have to. I'm required. And how is it? You know, I think they all have the problem. They're slower than me just doing it myself. Like kind of down the line, they're slower than me just doing it myself. Also, I'm only ever calling a car from work to home, to work or to the airport. The app is one tap away for all of those experiences. Exactly, and it's pretty easy to use. Now, I do think that one area that, for example, we are looking at is, while the front end, the initial demand may come from any agent, I am going to want our pixels in front of you. So, for example, I'm perfectly fine with OpenAI calling Uber, but then I want in that web interface and within that ChatGPT app, kind of the Uber pixels and the Uber brand so that you know who is fulfilling that ride for you. So, you know, we'll see how things turn out. If you're an Uber One member, you're going to want to use our product, especially for travel. I mean, again, this is the fight that I've seen coming where getting people out of your app and just using Uber as a backend service, as a commodity against every other service, pure play or not, nobody's going to want this, but it seems like they've all pivoted to enterprise so fast that that fight is delayed or maybe never coming. I think it's delayed. It's going to happen because I think the size of the prize is too big. Now, there's, if you talk about kind of history rhyming, not repeating itself, there's some of what I went through in my former job at Expedia. If you remember during those times, there was a big debate about metasearch, right? There were these metasearch players, Kayak, TripAdvisor, Trivago, that were amalgamating a bunch of travel content. And there was a point at which metasearch was quite powerful in terms of customer acquisition, et cetera. But as the supply consolidated, really the value started accruing to the suppliers much more than the meta players and, you know, the travel business consolidating into Expedia, Booking.com, Airbnb. There's more, but the three very, very big players. So I do think also on the supply side, when you look at mobility, when you look at delivery, there's usually two or three players in every market. So even if you get that front end being particularly big in a consolidated, let's say supply marketplace, and with our size and scale, multi-platform, all the countries that we operate in, I think we're going to be more than okay in terms of kind of the leverage and the negotiations that happen. I always try to push the negotiations to the backend, build a great experience, figure out kind of the balance, the economic balance later. But, you know, sometimes you've got to figure that stuff out upfront. This is a slight difference in the last time you were here. And I just noted that companies are all different, not Uber, but the AI companies, they're all in a slightly different posture than they were a year ago. Yeah, totally. They're racing towards IPO. They are constantly calling code reds. Like every week, it's a code red at OpenAI. It's a cool thing to do. Yeah, I mean, we've had CEOs come on the show and say they've called the code red. I'm like, did you actually do it? Like, no. We definitely had our share of code reds. And there's a danger of code red fatigue in companies too, It's a great company now, and I think that it's an adjustment that every company has to go through. So many people are interested in how OpenAI does, because it's an important company in the world. So they'll get through this. Do the model companies feel interchangeable in a way that has always seemed like a small danger here? I think interchangeable is a little bit too strong a word. I mean, I do think that what Anthropic is building, Claude, is it's spectacular. Like, our developers are using it all the time. Codex is definitely picking up use of our developers. Now, what we do do is we use some of the frontier models and some of the more advanced models to pilot, build demos if you want to build something quickly. And then what we do look to do is we have, it's much more than an API layer, but we've got a platform, Michelangelo, that has all the data feeds, and then essentially you're able to switch models. And early on, as this market is developing, we want lots of experimentation, and we want to give our devs the freedom to try a bunch of stuff. I don't want this to be top-down, thou shalt here or there. Of course, there's going to be optimization, but right now there's a lot of experimentation going on internally. We have to take another short break. We'll be back in just a minute. Support for the show comes from Hostinger. Every business has its impact, and with AI changing the landscape, the barrier to entry has never been lower. Whether you're starting a side hustle or building the next big thing, Hostinger lets you go live in minutes, not weeks. Hostinger is an all-in-one platform that brings everything into one place. Your domain, website, email marketing, AI tools, and AI agents. You can create websites, online stores, and even custom apps without coding or design skills. Then use AI agents to automate tedious tasks and help grow your business. Turn your one day into day one. Go to Hostinger.com slash decoder to bring your idea online for under $3 a month. Plus, get an extra 20% off with promo code DECODER. That's less than the price of a cup of coffee per month. That's Hostinger.com slash decoder. Promo code DECODER for an extra 20% off. Support for today's show comes from CNN. Do you want to live forever? Influential journalist Kara Swisher is taking a hard look at the longevity industry to separate the influencer hype from evidence-backed science. In her new CNN original series, Kara's talking to Silicon Valley power players and trying out the latest in anti-aging technology to see what works and what's a waste. Kara Swisher wants to live forever. New episodes streaming Sundays with a CNN subscription. Go to CNN.com slash subscribe to start watching. Support for the show comes from AWS. How much of your workday is actually work and how much is just hunting for information? The answer you need is buried in a Slack thread, the data is in Salesforce, or in an email from two weeks ago. By the time you've pulled it all together, half your morning is gone. That's the problem Amazon Quick was built to solve. Quick is an intelligent workplace assistant that connects to all of your systems. Your documents, your dashboards, Salesforce, Jira, Slack, email, and gives you complete answers in seconds. Not links to dig through, actual answers with full context. And here's where it gets interesting. Quick doesn't just find answers, it turns them into action. Create a deck, update a ticket, send a message, right there in the conversation without switching tools. It's AI that actually works the way you do. Learn more at AWS.com slash Quick. Welcome back. I'm talking with Dara Khosrowshahi, CEO of Uber, about just how weird the experience of running a software company is getting right now. Let me ask you about running a software company in 2026. This is the thing I was most excited to talk to you about. It is true, the last time you were here, we were talking broadly about AI and I had all these questions about agents and the big labs coming for you with their consumer chatbots. Maybe that's not happening yet. The thing we did end up talking about, just as you were walking out, is you said, we had GitHub Copilot, but all the engineers want to use Cursor. And now you're saying, and Cursor is around, but they're all using Claude Code. Or maybe they're using Codex. The increase in Claude Code usage and sometimes the replacement of Cursor usage is fairly remarkable. We use both. They're both terrific products. And then there's a group that's using Codex. And they're all really good. And I'd say the big change is with Cursor, it was coding and coding assist, so to speak, complete. But now these agents and agentic coding is something that is, it's just blowing people away. It's very, very cool. And when you say blow people away, I would say many of your peers have gone crazy. Like they have seen agentic coding, it's looked them in the eye and they have responded by losing their minds and saying that the entire structure of a company should change around this. I'll give you some examples. Meta is reportedly going to have teams where 50 people report to one manager. Jack Dorsey can't lay off enough people fast enough. And his goal, he said this out loud, he wants all 6,000 people agentically assisted to report to him at Block. I don't even know how you would... It's a show about org charts. And I read that and I thought, well, our show is going to keep going for another decade. Like I know what kind of conver... We're on the cusp of the weirdest org charts in history. Yeah, yeah. Are you there? Are you saying, okay, agentic coding is going to fundamentally change how you construct a software company? We have not gone and examined the fundamental org chart of the company yet. I'm not saying it won't happen. We are pushing the company hard. And by the way, I've got to push the company harder to go to first principles in terms of how you work, period. What we found is, and again, our culture is like bottoms up, let people do a bunch of stuff. And listen, the engineers are using it, the debugging. Like all the cool stuff is happening as it should. But what we saw is like in sales, right? Salespeople now use agents to summarize information on a client that they're going to call to build out a really cool presentation. We're using agents and AI, though I would describe around the edges of how we work. So that's one. And we're not kind of thinking about, well, let's think about the sales function from the bottoms up. Customer service is another example where, you know, we've got agents who generally follow policies. There's a policy if you're an Uber One member and your order is delayed by 20 minutes, you know, we're going to give you $15 back because you're a loyal customer, et cetera. That's a policy that's in place. And there are agents that are following those policies, et cetera. Human agents, you mean. Human agents, human agents. And we then said, well, let's build virtual agents to follow those policies. And it turns out that actually our policies on a global basis, the documentation is complete crap, to use a technical term. And what happens is, you know, an agent, a human agent, I'll be sitting in SCN and be like, hey, do you, what does this policy mean? It's kind of unclear. And you coach me and then I figure it out. Like humans are quite flexible. When we had AI agents go through these policies, they just went nuts, right? And so one approach was, let's rebuild all the documentation and policies the right way, and then let's have the agents work based on these policies. But why do we put those policies together in the first place? It was to get to goals and outcomes based on standardized ways to get to those outcomes. I don't want to go bankrupt, but I want to keep you, the Uber one customer member happy. And so we made a policy to approximate the optimal outcome for the population, right? But now I can just tell the agent what that outcome is. I want actually to be fair to a person. I want Uber one members to be happy, et cetera. I don't want to go bankrupt. So the approach that we're taking now within customer services, throw away the policies, describe to the agent what you're trying to accomplish, and then let the agents go. And obviously train them on good interactions, bad interactions, and give them feedback, et cetera. Wait, can I ask you just a foundational philosophical question? Yeah. Why trust computers to make those determinations and not people? Because the model can learn based on the population of everything that is happening versus an individual human just learning based on the experience that he or she is having that day. And models are easier to track and tune than humans are to train. Right, if you see... this is a scale answer. It can see all the data, so you can just describe a generalized outcome and we'll just have policies for it. You can retrain based on that data and you have perfect visibility into the actions, reactions, and the retraining output you don't have perfect visibility into, but you can kind of iterate around that. So it does demand a different approach and it's a little bit back to what you and I were talking about, which is a smart risk. It's a riskier approach. Like, we got to throw stuff out and just completely rebuild in a different way. And I'm really glad, like it wasn't, in this case, it wasn't me who pushed the Caltech team to throw everything out. They were frustrated with the results of it that they were seeing early on. They're like, we have to be able to do better. We're going to try this out. The signal looks really promising, but I can't tell you it's actually going to work in the end. That kind of dynamic customer response, in terms of pricing, people are making it illegal in this country to do dynamic pricing in that way because it feels unfair. Yeah, we, we're not going to, that that is actually an issue, which is what we don't want to do is have different outcomes based on targeting you versus another person versus another person. But you can have different outcomes because there were circumstances that were different. So for you, if your food was 15 minutes late, another person, you're both Uber One members, another person's food was 45 minutes late, you could actually have different outcomes because actually the circumstances are different. So it's not based on targeting or optimizing based on targeting. It's, it's optimizing based on context. That's really interesting. It strikes me that we, we could probably do another whole hour on, we wrote a bunch of rules for humans and now we have to write a system prompt that isn't the rules. It's actually the outcomes that you're trying to get at. Yeah. Yeah. We'll see if it works. You're going to come back next year. I'm going to ask you if it works. But let me ask you just more at the base level. When I think about software companies generally, the creative tension of any software group is you have a PM, you have a designer, you've got some engineers. They all want to be in charge. They all think they are going to do it. And they all need to work together. And if you get, if you can get that right, it's magic. It feels like with the power of vibe coding, everyone is going to try to do everyone else's job and no one's going to be good at it. And that is, we're all, it's all a mess. I can see it happening all over the place. Totally. Totally. Are you rethinking that basic triad inside of Uber? So it depends on the kind of project that you're working on. There's some larger projects that you need design. You need proper planning, et cetera. But we are having some product team members, whereas previously, if there were some simple bugs in the code or very, very simple features, they would have to then prioritize it with their engineers, et cetera. Now they're just going in and they are vibe coding and an engineer is going to review it, the code, but essentially the product person is going direct into the code base, so to speak, or going direct with an agent into the code base. So I do think for simpler problems, smaller problems, the dynamics are going to change. We're going to try it out. We're going to see what happens. When you look at a company like Meta, which seems to just be in the midst of endless rolling layoffs, you know, they're saying it's because AI is making everybody more productive. It might be because they're just freeing up capex to go spend on whatever they're spending capex on to whatever end that Meta is going to do AI. Super intelligence, I'm told. Are you in that same spot where you're like, we're getting more productive. I need less people. No, we are, my view is if an engineer is going to be 50% or 200% more productive, I want more engineers. Like there are the list of ideas in terms of what we want to build. So out scales our throughput at this point that generally we are looking to add more engineers to our employee base. Now there is a trade-off and we are dealing with a trade-off right now as we speak, which is, I don't know if you saw it, but our CTO was talking to a reporter and made a comment, which is true. We have blown through our AI token and infrastructure budget for the whole year in about three to four months. And it was a big thing when that happens, but it happened. And the trade-off is going to be headcount. So the, the, we are budgeting differently. Previously, you would have a headcount budget or plan, you know, doesn't mean it would actually happen, but it's a plan going in. You would have an infra budget. Now there's an active trade-off going on between the two. And to the extent that we have overages in terms of token spend or infra spend, which theoretically those overages are products that are being built and are productivity that's being added to our engineers, we're going to hire less aggressively, so to speak. That is a live trade-off, how far it's going to go. I don't know at this point. Are you all the way at I'm spending so much on tokens and it's costing me more than hiring one junior engineer. We are spending a lot on tokens. I haven't done the math yet, but it's, it's significant, but the throughput is really accelerating. So at this point it's, it's something that needs to be managed. And, and I do think it's just taking different muscles. The way that we're managing budgets, it's just, especially on tech is fundamentally different than how we did three, four years ago. Well, I'll ask AI a question that I want to talk to you about autonomy, which is also AI, but in a very different way. Physical world AI, yeah. You were on diary of a CEO and you said the employees at Uber have created an AI version of Dara to practice presenting pitches to you. Is that real? And how close are we to AI replacing the CEO? So it is real. I have not witnessed the Dara AI, but I, I, it is real. People have done it. Honestly, I don't know how good it is. It's clearly not as good as a real thing. I mean, come on. How is that possible? Decoder listeners. Every time we do an AI episode, they say the AI should replace the CEO. It is a reflexive comment we get. I'm not there yet. I just, I think that, um, the AI powered CEO is going to be better than the AI CEO. I think there's a magic in terms of teaming up humans with AI and with agents. And based on what I see, that is a superior product than pure play AI or pure play human. You should recuse yourself from this. You have a deep conflict of interest here. Of course I do. I'm hoping the board sees it that way as well. Maybe the board is planning this and I had no idea. I mean, that would be in keeping with the Uber story. That would, that would be there. How is AI changing our board processes? I've got to think about that one. Oh, trust me. I get those pictures. They're very bad. You don't want anything to do with those. Let's talk about robots, actual robots, actual AI in the world. Uber has made a bunch of big investments in robotaxis. I want to start with Rivian. It's over a billion dollars. I think it's $1.2 billion in total commitments to Rivian over some number of years. I just have a really basic question. In that partnership in March, you're going to buy up to 50,000 fully autonomous R2 robotaxi's by 2031. But it's also called an investment. And I'm just doing the math. I'm like, that's at the price of the R2 platform. You're just buying a bunch of cars. Is buying a bunch of cars an investment or are you actually getting equity in Rivian? So we actually invested in Rivian equity. And we've invested in a number of our partners. Usually we will invest in our partners in a Lucid, in a WeRide, in a, in a Avride, for example. So it is an investment and it's a vehicle commitment as well. It's both. And it's based on deliverables. Obviously they've got to deliver and based on everything that we've seen from RJ and team putting together a first, first class AI team. And, and we're confident that they can deliver on those R2s. Yeah. The deliverables are very vague. I'm just gonna read you the press release. Uber will invest up to $1.25 billion in Rivian through 2031, subject to, and I quote, the achievement of certain autonomous milestones by specific dates. Well, they are very specific contractually. I put this into five different AI systems and no one can tell me what they are. What are the, what are the autonomous milestones? I could tell you, but then I'd have to kill you. The reason I'm asking is not, I mean, I desperately want to know the specifics. I'm looking at this industry in total. And I will tell you that we've thrown out whatever autonomous milestones we used to have, the level system that everybody used to talk about. That's all gone. No one cares about this anymore. No one's like, we shouldn't do level four. We're doing it. And I can't quite tell you when a car, what milestone an autonomy platform has to hit before I can say this is a robot Many companies in this industry, they're a great partner of ours in Atlanta and Austin. There are many other companies that are getting to the finish line. WeRide, for example, or a pony.ai or Baidu. These are Chinese companies, are already at the finish line. And we are in market, for example, with WeRide in the Middle East. And there are players like a Neuro or a Wabi or an AvRide or a Wave, all of whom are accelerating to the finish line. And if anything, the speed of getting to the finish line is accelerating. One, model capabilities are much, much better now. Used to be kind of deterministic, you know, kind of code that you had to slog through. Now, obviously, it's learning AI models. SIM capability is much better so that data will go much further in terms of model training. And what we're trying to do with AV solutions is, we're trying to build out the whole necessary ecosystem around these companies so that they can focus on what they do best, which is training these models to get them to be superhuman safety. We can help them get there, for example, with data collect. And we can both kind of then get to market as quickly as possible. So it's not, I would say, a diversification bet. It's a bet that there are going to be many players. And as a platform, we've always been supply-led, which is the way to grow our platform is to build out supply, whether that's more drivers or whether that's more restaurants or more hotels, then we're able to, as we build out liquidity of supply, demand shows up. And just like we want every safe human driver on the platform, we want every safe robot driver on the platform, whether that's a Waymo driver or a Neuro driver or an AvRide or a WeRide. It's a bet that we're making, which is there won't be one physical AI model to rule them all. There's some real confidence in this bet. I've talked to a lot of rideshare CEOs over the years, a lot of autonomy CEOs over the years, and it's always been 10 years away. The confidence I'm hearing from you is, oh, this is happening. We're spending a lot of money to get there faster. All the evidence we see is that that's happening. And, you know, Waymo has shown the way. A lot of Waymo engineers now are working at other companies. For example, the Chinese players have shown the way. And you've seen it, the speed of foundation model development, whether it's digital foundation models or physical foundation models. You know, NVIDIA is betting on this as well. You know, these are big bets made by capable companies and we think we're on the right track here. In the context of our conversation, I'm going to bring up the trade-off. Sure. By saying it's going to be more real, you no longer get to kick the can on, we're not going to have drivers in the cars, which famously got Travis Kalanick in a lot of trouble by saying, I want to get the driver out of the car long, long ago because autonomy was so far away. We just didn't have to solve this problem. You have been on podcasts recently saying, oh, this problem is here. I don't know what's going to happen to 9.5 million Uber drivers when autonomy comes. You literally said, I don't know, to Stephen Bartlett. Well, if you don't know, you should say it. You know, it's now, here's what I know. 10 years from now, I am 90% certain that we're going to have more drivers on our overall platform than we do today. Now, I don't know if that's going to be true in San Francisco, but with the way that the business is growing and the capability of building these cars at the right bill of materials in all the markets that we operate in, not just the high cost markets, we're going to have plenty of drivers and we also are actively looking to build out more use cases for drivers that are more complex. You know, one of the announcements that we made was personal shopper, right? It was courier. People started hacking courier, asking Uber couriers to go shop for them. So we decided to productize that as well. That's a very, very complicated interaction. It's a random store. Take a picture of the goods. This is what I want. So we're building out much more complex use cases for humans to migrate onto as more of the work is being automated. 20 years from now, I don't know what that's going to look like because then you really start increasing capabilities. And I think these are big societal questions. It's going to be true of white collar workers and it's going to be true of certain kinds of blue collar work as well. And, you know, I think CEOs should talk about this, not in a way to like scare people, but we should also be honest about it, which is I've never seen a wave of technology that has direct impact on how companies work and how people have worked with the accelerated pace that I'm seeing today. Doesn't mean that society can't adjust, but the pace of change here, it's pretty remarkable. One of my theories about the extremely negative polling on AI is that it's fundamentally an enterprise technology. You described this even in this conversation. The frontier models, those companies are moving to enterprise use cases. You at Uber are using them in enterprise context. And there are not great consumer products in front of people. Not yet. Yeah. I haven't seen them. Maybe they're coming. I mean, listen, we're trying to do that. And it's these moments of surprise and delight where, you know, you can talk to your Uber to get an Uber, lots of complex situations. You can transcript a shopping list, take a picture. Sure, but I don't think that stuff is going to change the overall polling on this is a threat that will take my job away. Listen, if it's your job, I think you're right. Yeah. And so this dynamic of everybody is showing up saying the jobs are going away. And mostly because it's so good at writing code, right? Like this is a weird kind of disconnected dynamic for regular people. Uber needs customers. You need people with money to want to ride around. Like, how do you see that economy playing around? So I think that it, right now, the talk is louder than what we see in the market, right? The economy remains robust. The consumer remains robust. We don't see white collar people out of work at this point. So I, I just don't see it in market. Now, the fear that you see might be a leading indicator of what's to come. But at this point, I see no signal in our actual business that it's having any impact on consumers at large. What do you ascribe the extremely negative polling on AI to? Um, I do think that it's some fear mongering from the press. They love the drama. Are you part of the press or no? A little bit. Can I call this, can I put this at your here? If I had this level of influence, you can put it at me all you want. But listen, it's, it's a conversation that people are constantly having. It's a dramatic conversation. And I do think like machines replacing humans has been a theme for eons, right? And, and what you do see in manufacturing, for example, with automation is that machines compliment humans. And then there are other capabilities that humans always adjust to. It's just things are moving so fast now that I think the fear is, it's out there. My, I've got 14 year old twin boys and two other older kids. My 14 year old kid is like, dad, why should I study? I'm not going to be able to have a job. Like we had a, and I was just blown away. My 14 year old is asking me now, maybe he don't want to study. So that's why. Does that feel like the main thing 14 year olds say? Yeah, exactly. So it's, it's in the ether. You see signal. There are some companies like you mentioned who are acting on it. We'll see when the, what happens in the next two years, but I don't see how it's going to reverse once we get more data, maybe societal will, maybe the reality will be less dramatic than some make it out to be. And then we'll see, we'll do our best. I mean, I would love for it. I would love for the press, to be real that it's the press. I just, the media industry is not at a moment of intense strength right now, right? It is contracting in major ways. But, you know, there, there has been some, some I do think that the media is incentivized sometimes to overdramatize these things. Could be real. Maybe it's not. I do think that that there is a reality in it. The question is how quickly is a good change going to happen and will we be able to, will society be able to adjust fast enough? Look, I get all my news from X. The everything app, which assures me on the daily that AGI is just around the corner. Um, I want to ask you the, the, the question I ask every time I talk to you, uh, I always take an Uber to come see you. It's just my little tradition. And I always ask the driver. Thank you. Uh, the drivers always have the same question. So the same question every year. Sure. And then this time I actually got a very detailed follow-up question to ask you. Oh, cool. All right. Uh, the drivers all want to know, how are they going to get paid more? Well, uh, they are going to get paid more by some of the newer jobs that we're giving them. You know, shopping, for example, on a per hour basis can pay more, but I do think that driver pay isn't, Westchester. So they lose, it's an hour. They literally lose one utilized hour. So I've been directly requested that you go and lobby the city and state so that they can go home with a utilized hour instead of an empty run. We have already been lobbying. Some of these regulations have unintended consequences. New York is unfortunately one of the most highly regulated markets out there, a significant amount of your fare goes to the city, et cetera. I think Ubers are too expensive here, and I think regulation sometimes goes over the top. It's something that I will absolutely take to the powers that be. The powers that be in this city is Zaron Mondami. Have you met with Zaron Mondami? I have seen him speak. I have not met him one-on-one yet, but I look forward to that dialogue. Well, here's my tips. One, say you love New York City. He loves it when you say you love New York City. Cool. I do. Two, tell him the drivers want the return trips from both the airports and the city. I will absolutely relay that to him. Maybe he listens to your podcast. You never know. We know some people. The same thing. I can't tell you. I can't tell you what the milestones are. All right, cool. Dara, this is always a pleasure. Thank you so much. Thank you. Really appreciate it. I'd like to thank Dara for taking the time to join me on Decoder, and thank you for listening. I hope you enjoyed it. To let us know what you thought about this episode or really anything else at all, drop us a line. You can email us at decoder at theverge.com. We really do read all the emails. Or you can hit me up directly on Threads or Blue Sky. We're also on YouTube. You can check out full episodes at DecoderPod. It's the same handle on TikTok and Instagram. If you like Decoder, please share it with your friends and subscribe wherever you get podcasts. Decoder is a production of The Verge and part of the Vox Media Podcast Network. The show is produced by Kate Cox and Nick Stat. This episode was edited by Xander Adams. Our editorial director is Kevin McShane. The Decoder music is by Breakmaster Cylinder. We'll see you next time. Sometimes good business is about the things you don't do. Like not paying annual fees, not wasting time on reimbursements, and not leaving rewards on the table. With EngineX, get more for doing less. It's the business card that gets you up to 10% back on travel and 1.5% back on everything else. EngineX, going up. Engine is a financial technology company, not a bank. The EngineX Visa commercial card is issued by Fifth Third Bank, NA, member FDIC, pursuant to a license from Visa USA Inc. Terms and conditions apply. All applications are subject to credit approval. Actual reward rates vary by reward tier and purchase category and may change. Points have no cash value and are redeemable for rewards through our program. Rewards are subject to terms and conditions. Employees filing for reimbursements is the latest in spend technology. Oh, wait, that was the script from 1986. In 2026, there's EngineX, the business card that centralizes your spend so you can simplify, save, and earn big with every swipe. EngineX, going up. Engine is a financial technology company, not a bank. The EngineX Visa commercial card is issued by Fifth Third Bank, NA, member FDIC, pursuant to a license from Visa USA Inc. Terms and conditions apply. All applications are subject to credit approval. Actual reward rates vary by reward tier and purchase category and may change. Points have no cash value and are redeemable for rewards through our program. Rewards are subject to terms and conditions. Ryan Reynolds here for Mint Mobile. I don't know if you knew this, but anyone can get the same premium wireless for $15 a month plan that I've been enjoying. It's not just for celebrities. So do like I did and have one of your assistants assistants switch you to Mint Mobile today. I'm told it's super easy to do at mintmobile.com slash switch. Upfront payment of $45 for three-month plan, equivalent to $15 per month required. Intro rate first three months only. Then full price plan options available. Taxes and fees extra. See full terms at mintmobile.com.