What the Agent Economy Looks Like From Inside Stripe

Transcript

The internet has this new kind of actor on it. Over time, this actor, these agents, will become the predominant actors on the internet. These AI companies are just growing from a revenue perspective faster than any previous cohort we've seen. LLM traffic to Stripe docs is up 10x year over year. And that's just a useful signal that machines are becoming users of developer infrastructure too, including Stripe's developer infrastructure. [SPEAKER_00] Emily, welcome to the show. Thanks so much, Dan. [SPEAKER_00] So really excited to have you. [SPEAKER_00] You are the head of data and AI at Stripe. And I feel like this is such a good time to have someone from Stripe on because you all famously are increasing the GDP of the internet. [SPEAKER_00] And the internet is changing so much right now. And therefore, the economy of the internet is changing from something where humans are buying and selling from each other to an economy where agents are buying and selling from humans and agents are buying and selling from each other. And I feel like, A, I want to know what that means for Stripe. But B, I want to understand, since you have this macro view of the agent economy, what does that even mean? And what are you seeing? [SPEAKER_02] Yeah. [SPEAKER_02] So a big shift I think we're in the midst of is that the internet economy is becoming more autonomous. [SPEAKER_02] Right? [SPEAKER_02] So for a long time, for forever, the internet was built around an extremely simple assumption that the main actor was a person sitting in front of a screen browsing and filling out forms and clicking through checkout. [SPEAKER_02] But also they're writing code and setting up tools. [SPEAKER_02] And that assumption is starting to break in various ways. [SPEAKER_02] Sometimes the human is still totally in control, but they're interacting through an AI interface instead of through a website or a traditional app. [SPEAKER_02] Sometimes the agent is acting on their behalf and then sometimes software is now just interacting directly with other software. [SPEAKER_02] And as all of that starts to happen at all of those layers, a lot of things need to be rethought. So there has been rethinking of how our products are discovered and how our products are bought, but also what should developer tools look like? And in our world of Stripe, what is the underlying economic infrastructure? So the payments and the billing and the fraud detection and the identity layer that's needed in this world where actors are no longer just humans. And so that for me is the larger frame of the moment. It's not just, hey, AI is making search better or AI is helping people code or AI is evolving commerce on the margin. It's really like, actually, the internet has this new kind of actor on it. Over time, this actor, these agents, will become the predominant actors on the internet. And as that's happening, every layer of the stack starts to need an evolution. So for Stripe, it's like, OK, Stripe, how are we getting agent ready? But then also, how are we helping businesses get agent ready? And both of those are happening in a number of ways. Yes, in commerce, but also just in how builders build. [SPEAKER_00] And can you give me some specific examples of the kinds of things you're seeing? [SPEAKER_00] Like, I'm almost wondering, for example, I know at Stripe, one of the things you deal with a ton is fraud. [SPEAKER_00] A, I assume there's a whole new type of fraud happening. [SPEAKER_00] But B, I'm almost wondering what even counts as fraud now in the sense that it's possible my agent could go steal someone's credit card and check out. [SPEAKER_00] I don't think that Claude would, but you never know with Grok. No comment, no comment. But you're right that AI introduces very different fraud problems. You asked what is fraud. We used to think of fraud as payment fraud. Someone was stealing money. Someone was stealing your card credentials. Increasingly, fraudsters are stealing compute. And that's a very different type of problem. So in earlier software models, if you think of traditional SaaS, letting someone into a free tier didn't cost you very much. [SPEAKER_02] And stealing a free tier wasn't very valuable to the fraudsters. [SPEAKER_02] Now, giving someone credits, freemium offering, free trial, letting them rack up a bunch of tokens and pay at end of month, except maybe they choose not to pay, actually is a major fraud vector and an existential risk to a lot of these businesses. [SPEAKER_02] Because every prompt, every image that gets generated, every API request has a very real cost attached to it. [SPEAKER_02] People are talking about intelligence getting cheaper. [SPEAKER_02] Yeah, but it's still very far from free. [SPEAKER_02] And then when you look at the growth model for many of these AI companies, free compute is the new CAC. You used to spend a bunch on paid media for cost of acquisition. Now you spend a bunch on your free trials and your credits and your self-serve onboarding as a major lever for growth. And so the abuse we see in that context where compute is the new CAC and compute is very expensive is threefold. One is multi-account abuse. So bad actors come in and they sign up over and over again and they create a new identity every time on a new email address and they claim their new user credits. And they stay ahead of detection by iterating across a bunch of different aliases. And just to give you a sense of the order of magnitude across the AI companies running on Stripe, about 7% of their signups are these multi-account abusers. So a non-trivial share. The second trend that we see in terms of a new vector of abuse is free trial abuse. And this is often the most urgent issue because the unit economics break really quickly. To give you a sense, we had a large AI company who was seeing only 4% of their free trials convert to paid. And each free trial cost them $25 in LLM spend. And so basically it was costing them $625 per payer before the first dollar of revenue was brought in. And when we double clicked on those free trial folks, the vast majority of them were actually abusers. So they were actually stealing the compute. They never had any intent to pay. These weren't people who were genuinely trying out your service and then chose not to buy. These were people who were literally abusing your systems. And so some companies just dropped free trials altogether. Of course, that's not great because you're throttling growth. Others responded by blocking virtual cards. So I don't know how often you've been marketed virtual cards. And so it was costing them $625 per payer before the first dollar of revenue was brought in. And when we double clicked on those free trial folks, the vast, vast majority of them were actually abusers. So they were actually stealing the compute. They never had any intent to pay. These weren't people who were genuinely trying out your service and then chose not to buy. These were people who were literally abusing your systems. And so, some companies just dropped free trials altogether. Of course, that's not great because you're throttling growth. Others responded by blocking virtual cards. So I don't know how often you've been marketed virtual cards. I'm often marketed virtual cards, right? Get this, you know, one-time use card. It expires after 24 hours. So you never have to pay for the service. You know, in the hands of a good consumer, fine. In the hands of a fraudster, very much not fine. The problem with blocking all virtual cards is for AI companies, about 15% of legitimate card transactions on Stripe are actually virtual cards. So you really don't- [SPEAKER_00] We use that all the time for RAMP, for example. [SPEAKER_00] We have a bunch of virtual cards. So you don't want to be, in the same way you don't want to be turning off free trials, you don't want to be throttling virtual cards either. And order of magnitude, you can think of exponential growth in free trial abuse over the last six months, it's 4x. And for one large AI user on Stripe, we're currently blocking 250,000 fraudulent free trials a week. So the magnitudes here are quite high. That's crazy. And is the volume of fraud constant? [SPEAKER_00] It's just shifting shape or is fraud just going up because they're more powerful now because they can just use AI agents to do it? [SPEAKER_02] Fraud's going up because the fraudsters have AI on their side, although it's also on the side of the detectors, but also because the value of the services they can steal is higher. Right? I don't know, you steal traditional SaaS, what good do you get? You steal some inference, you steal some compute, you can resell it, you can do all sorts of stuff. Look, I love a good CRM seat, you know. Don't you? [SPEAKER_02] Who doesn't love a good CRM seat? [SPEAKER_02] Don't tempt me, Emily. [SPEAKER_00] The CRM seat is free. LLMs are for sure more tempting. And by the way, the third type of new abuse we see is this non-payment abuse, right? So you incur an overage or you have 30-day invoicing except you never pay your invoice. And you know, in many cases customers are consuming thousands or tens of thousands of dollars in compute during a month or a day or sometimes an hour. [SPEAKER_02] And by the time they get billed and failed payment, that loss has already happened and these AI companies are left holding the bag. [SPEAKER_02] And so for us, fraud used to be a transaction thing. Now it is a customer thing. It is a full funnel thing. [SPEAKER_02] It starts at the time of sign up. Is this multi-account abuse? Should they get credits? Is this free trial abuse? Should we give them a trial in the first place? And then when they have overages, should we be throttling them? Should we be requiring top up? Should we be blocking service completely? And it's a whole new world because the thing to steal is much more valuable and the cost of having it stolen is much more existential. [SPEAKER_00] How are you guys even able to, so I totally understand how you need to be in that full funnel in order to detect fraud. [SPEAKER_00] But my understanding of, whenever we've integrated Stripe, it's usually at the checkout. [SPEAKER_00] We're not necessarily putting you in there when someone puts in their email address for free. [SPEAKER_00] So have you changed the product to do the full funnel or how does that actually work? Yes. So Radar, which is our fraud protection product used to be at the transaction level, right? At the moment of checkout, as you note. But because so much of the fraud risk was coming up funnel, AI companies are now increasingly integrating Stripe Radar at the time of signup. And so, we see the metadata at the time of signup, we pass back scores at the time of signup and every moment subsequently, because fraud is now a full funnel problem, not a transaction problem alone. If you're asking for a friend, if you're running an AI company and you don't even know what your fraud rate is and you want to protect yourself from this kind of abuse. What are the top things that you need to do in order to make sure that you're reasonably safe? [SPEAKER_02] So I would just adopt our highest tier radar plan, but the actual mechanics of that are at signup, you want to know if your customer's good before you give them any access to any credits. [SPEAKER_02] You want to make sure they're good at the time they pay. You want to make sure that charge is good. And anytime they have an overage, you want to make sure they're good for their money. And you know, there's other stuff around refunds and disputes that we also support. But I think those are the four major moments in the AI companies customer life cycle, where we're maniacally focused on protecting. Because that's where we're seeing the biggest cost and the fastest fraud growth. And at each point, that's just a call to the radar API. Yes, correct. And what if I'm sitting here, which I am doing, millions of dollars a year in Stripe transactions, but I actually have no idea what my fraud rate is other than there's that little thing where it's, it's not even necessarily our fraud rate. [SPEAKER_00] I think it's our card chargeback. [SPEAKER_00] Anyway, our fraud rate is low enough as marked for me to not care about it. [SPEAKER_00] But I guess I don't really know if there's some amount of free trial fraud that I'm not totally understanding right now. [SPEAKER_00] So what are the things I should be looking for to know if I should dig deeper and potentially do some sort of radar integration? So thing one is you can go to your radar dashboard and see if you see anything that looks spurious there. If not, you can also ask the radar assistant, which is in the dashboard. And as you're doing that, you can describe your business model. So you can say, you know, I have a high marginal cost business, in which case you care more about certain types of fraud than others. [SPEAKER_02] But you can also just take a stab at integrating UpFunnel and see how it performs. [SPEAKER_00] So what are the things I should be looking for to know if I should dig deeper and potentially do some sort of, for example, radar integration? [SPEAKER_02] So thing one is you can go to your radar dashboard and see if you see anything that looks spurious there. If not, you can also ask the radar assistant, which is in the dashboard. And as you're doing that, you can describe your business model. So you can say, I have a high marginal cost business, in which case you care more about certain types of fraud than others. But you can also just take a stab at integrating UpFunnel and see how it performs. We can certainly share with you based on back testing what we think the big issues are, but the fastest way to get a clean read is just to integrate. Got it. So I don't think that we're integrated right now. So I would just go look at radar and see, does it say anything? I'm doing that right now. Just to, it'd be really funny if I found that we had a ton of fraud that I didn't know about. We were at 0% fraud. How is that possible? I don't know. 0.02% early fraud warnings, total fraud rate 0.2%. So we're doing pretty good, right? [SPEAKER_00] That's pretty low. Yeah, you're a pretty good human. Maybe the fraudsters don't want to come after you. [SPEAKER_00] That's really interesting. I want to go back a second to the AI economy, because one of the things you said earlier is fraud is increasing overall on the internet. And it's increasing because the fraudsters have AI, but it's also you all and everyone else on the side of good in the AI economy also has AI to defend against these sorts of attacks. I think you're getting an interesting window into the arms race that I think is playing out in lots of different areas that have this kind of threat vector. A really simple one is cybersecurity. Not just for payments, but for hacking and stuff like that. But there's all these other similar types of things where AI makes one part of the process much easier. And then another part of the process has to use AI to compensate and catch up. So how is that race going? What is that like? What are the early reports that you're seeing and feeling being in a race with AI-armed fraudsters? I think the interesting thing about fraudsters is they don't really care about boundaries. They don't care about whether this transaction is processed on Stripe or off Stripe. They don't care about whether this transaction is on Fiat or crypto, whether it's on a card network or a buy now, pay later. They're just going to figure out how to work around the system to get through. And so one of the important levers, and I appreciate you calling us the good guys. One of the important levers I think the good guys have for winning is to be comprehensive. And a simple example in our world, Stripe Radar used to only work for card transactions. And then last year we added ACH and SEPA, right? So other payment methods. But this year we've extended to all payment methods that have disputes. And we added crypto and we added the Radar API. So guess what? You can screen transactions, even ones that aren't processed on Stripe, right? So you can process on WorldPay or Adyen or whomever. And through the Radar API, get the same fraud signals. Similarly, and we haven't talked about agent at commerce yet, but as we built out our agent at commerce suite, one of the new primitives we designed is the shared payment token, which allows agents to safely pass buyer credentials onto merchants for the merchants to process the transaction. And as part of those shared payment tokens, we pass over the Radar fraud scores so that the merchant, again, whether or not they're processing on Stripe, can action them appropriately. You know, when it comes to fraud, we really see fraud defenses, fraud mitigation as a public good. And that allows us to invest disproportionately above and beyond the direct value to Stripe because protecting the internet is important for growing the internet economy. So I would say, overall, yes, fraudsters have AI in their favor. Stripe looks at 2% of global GDP and is growing 34% year on year and sees a broader swath through our multiprocessor solutions like the Radar API. And so luckily, not only do we have AI on our side, just like they do, but we also have data on our side. And the more comprehensive we've gone in our fraud protections, I think the more we've been able to eek ahead. Now, that's not to say that we're not constantly surprised by the new creative vectors they come up with. But you can have an agent every day or every hour taking a look at anomalous patterns on the Stripe network and identifying new vectors that are popping up across processors, across payment methods, across merchants and burn them down pretty quickly. So I'm overall bullish, but certainly not complacent. [SPEAKER_00] What about other parts of the AI or agent economy? So we've talked a lot about fraud. What are the other things that you see as sort of having this bird's eye view of what's going on that people might not realize? I mean, I think the AI economy is broad. I think there is a set of horizontal model providers that have a very interesting view into where is AI being adopted and with what intensity throughout the economy. There's a number of vertical AI solutions. People like to call them wrappers. And I say that not condescendingly, just as in it's not their models, it's someone else's models, but they have domain specific data and relationships and context and they're solving problems in healthcare or architecture or whatever, who have a pretty unique view into vertical level adoption of AI. But I guess I'd be curious, what you have in mind on who has the best horizontal view. You're asking me? Yeah. Well, I want to know what it looks like on the payment side, but I imagine the model companies have the best one overall, because that's where all the tokens are going. [SPEAKER_02] Yeah. Yeah. [SPEAKER_02] I think they see a lot of the tokens. [SPEAKER_02] But I'd be curious what you have in mind on who has the best horizontal view. [SPEAKER_02] You're asking me? [SPEAKER_02] Yeah. Well, I want to know what it looks like on the payment side, but I imagine the model companies have the best one overall, because that's where all the tokens are going. [SPEAKER_02] Yeah. Yeah. I think they see a lot of the tokens. I think the AI gateways also have a pretty unique perspective on who's buying what from whom. As I step back and look at the AI economy from the Stripe vantage point, we see who's buying what from whom for how much, who's retaining and churning their subscriptions. And there's a few themes that stand out. I think people feel this intuitively, but not everyone has seen it in the data. I think people are looking at the top 100 AI companies on Stripe and the ones that reach 30 million in ARR get there in about 18 months. [SPEAKER_02] So a year and a half. [SPEAKER_02] Wow. [SPEAKER_02] And if you go into 5 million ARR, they are scaling orders of magnitude faster than high performing SaaS companies from less than a decade ago. [SPEAKER_02] So the second meta trend is this, and you probably feel it as a consumer, I know I do, this very fast iteration across monetization models, right? [SPEAKER_02] So traditional SaaS had a lot of seat-based usage, fixed monthly subscriptions. [SPEAKER_02] That made sense for them because they were being used by humans primarily and their marginal costs were basically zero. [SPEAKER_02] But we've talked about the very real inference costs in the context of fraud. [SPEAKER_02] Those also have very real implications for how you price. [SPEAKER_02] And so usage-based billing has become very important very quickly. [SPEAKER_02] Companies are metering tokens and API calls, but they're also metering workflows and they're metering outcomes, whatever unit best reflects both the customer value and the cost structure. [SPEAKER_02] And then they're charging with very high precision, right? [SPEAKER_02] They literally want to know every event. [SPEAKER_02] How is it rated and what's all the metadata that sits on that rated event? [SPEAKER_02] Way more hybrid monetization models, right? [SPEAKER_02] So I talked about subscriptions, but subscriptions aren't dead. [SPEAKER_02] They're subscriptions with usage overages or prepaid credits that burn down or real-time top-ups, which gets to my comment earlier on this non-payment abuse issue. [SPEAKER_02] And very multi-dimensional pricing and monetization. [SPEAKER_02] Lovable is a really good example, right? [SPEAKER_02] So they used Stripe Billing for their initial launch, which was fairly simple subscriptions, more traditional pricing and allowed them to monetize very quickly. [SPEAKER_02] And then they added a bunch of products like Lovable Cloud or Lovable AI, and they moved with those into usage-based billing, right? [SPEAKER_02] So customers are actually charged based on token consumption, but it's a hybrid model, so above a certain threshold. And that just helps companies like Lovable align revenue with usage and value and the actual cost of running the models. And in the limit, we actually have a solution called token billing, which is underlying model costs change a lot, sometimes very quickly. And if you are a wrapper on top of someone else's LLM and your pricing doesn't keep pace, then your margins can disappear, right? So costs go up and your price stays where it is, then you're in the red. And so token billing is, let's in real time track and price to the costs of the underlying tokens with some markup as set by the business. So MISA and SHIP and Lovable are all examples of this infrastructure. I love all of these points. I want to go through them one by one. [SPEAKER_00] So a big one that you're talking about is fast iteration across monetization. [SPEAKER_00] And it feels there's this hyper experimentation going on right now where people are thinking, well, we could charge per token. [SPEAKER_00] We charge on a token basis. [SPEAKER_00] We could charge per completed request. [SPEAKER_00] I think FIN, the customer service platform charges per case resolved, which has been a thing in customer service for a long time. [SPEAKER_00] But it feels that could come for a lot more types of software as LLMs are making it easy to tell, did we actually do the work to get paid? [SPEAKER_00] What do you think is the, if we're going to pick one, there's a whole range of exploration going on. [SPEAKER_00] But if we're going to pick one new pricing model, if last year's pricing model or last decade's pricing model was straight up per seat. [SPEAKER_00] What do you think is the new standard pricing model that is starting to emerge from the Stripe customers that you see? [SPEAKER_00] If you are buying the model. So if you're primarily a model provider, your customers are primarily buying the model. I think you're metering tokens in an API, OpenAI API, cloud API. Yeah, exactly. [SPEAKER_00] For these vertical solutions. [SPEAKER_00] I think in steady state, you are metering outcomes, but it's going to take time to get there, not because of the billing infrastructure. Actually, that's totally ready. You mentioned the Fin example. Intercom does the same thing. Actually, on Stripe Billing, they have an outcome-based meter for support tickets resolved. Why do I say for vertical solutions it's going to be on outcomes? Because I think end users are going to want to hold those vertical solutions accountable for outcomes, and they're going to want to know that they have positive ROI on their spend. [SPEAKER_02] Now, when you and I buy a model, we feel we ourselves are accountable for the ROI that we get on the whole range of applications we might have for that LLM. [SPEAKER_02] But if you're a vertical provider, if you're really focused on solving a concrete need in a given business domain on top of someone else's LLMs, it seems the core value is on you to ensure the ROI is there. [SPEAKER_02] And I think outcome-based pricing is the most efficient way to hit that. Now, I don't think all outcomes are created equal, and so you could imagine these complex objective functions where it's not just did you resolve the support case, but how complicated was it and with what quality and what was your CSAT? And how expensive was the person that you were automating in that task? And so that's why I say in the limit, I think it'll take time for us to be very crisp on the outcomes we care about and how we measure those outcomes. And those outcomes will be multidimensional. But I just have a hard time imagining a year from now, most vertical providers are literally charging on tokens. That's really interesting. [SPEAKER_02] And how expensive was the person that you were automating in that task? And so that's why I say in the limit, I think it'll take time for us to be very crisp on the outcomes we care about and how we measure those outcomes. [SPEAKER_02] And those outcomes will be multidimensional. But I just have a hard time imagining a year from now most vertical providers are literally charging on tokens. That's really interesting. I'm very curious to see that because what I felt, so I think you can see this a little bit in the example, in the lovable example you gave, but also in the Claude and ChatGPT examples and some of the pricing that we've ended up doing is it's per seat, it's per user. [SPEAKER_00] With overages. [SPEAKER_00] With overages. [SPEAKER_00] Because we've started to exist in this world where we used to charge per seat, so people know how to model it, it's pretty easy to figure out how much I'm going to pay. [SPEAKER_00] But software used to be free to run. [SPEAKER_00] And now it's not. [SPEAKER_00] And so we have to cover our margin by adding the overage so that customers know what they're going to pay unless there's some sort of special circumstance. [SPEAKER_00] Do you see that? [SPEAKER_00] Where do you see that fitting in the examples that you gave? [SPEAKER_00] And I guess you would say eventually that might go away. [SPEAKER_00] I'm curious why. [SPEAKER_00] I think the world isn't perceived as silly to do seat based usage of developer tools, but I think it's a fair question since November or December to say, wait, why isn't that silly? That seems a little silly because if what these agents are doing is making every developer, I don't know, 10 X more productive at some point, then don't you need one tenth the developers? And why would you want your revenue pegged to the count of developer as the base price? So I suspect that we will see seat based disappear. Now, in the enterprise context. Now, I think it's quite different in the consumer individual context, I think with the exception of maybe some nerds on the call, most people are actually pretty uncomfortable as individual consumers with anything but a fixed fee monthly, maybe with some overages if they want to spend crazy. But in businesses, I would be super surprised if six months from now we have half of the seat based licenses that we have today. That is fascinating. Well, we will have to have you on again to talk about that one. [SPEAKER_00] I'm so curious to see and I would love to see more Stripe data coming out about that. [SPEAKER_00] One other thing that you brought up before this was you're also seeing these companies scale faster. [SPEAKER_00] You said that the time to get to 30 million in ARR is 18 months, which is significantly faster than any other cohort of companies you've seen. [SPEAKER_00] I'm curious, where is that coming from? [SPEAKER_00] Presumably the spend or the growth from their customers is coming from somewhere. [SPEAKER_00] Either it's spend that people weren't spending before, it was on a company balance sheet, just waiting to be deployed, or they're pulling it from another provider and going really rapidly into these new ones. [SPEAKER_00] Do you have a sense for what's happening here? [SPEAKER_00] Where's all the money coming from? [SPEAKER_00] Why are they growing so much faster and where's all the money coming from? [SPEAKER_00] Yeah. So I think a lot of the AI growth that we've seen is actually net new spend being pumped into the economy. I think it has largely not been a substitute for traditional SaaS or for headcount OPEX because it's been experimental because people are still learning because organizations are somewhat slow to drop existing licenses often because they're contracted into longer durations. But also because AI was starting not literally at zero, but at near zero. [SPEAKER_02] So there weren't other AI companies to soak up the spend from. [SPEAKER_02] Low market share from. Yeah. [SPEAKER_02] I would say now going forward, I don't have a crystal ball. I can't tell you exactly what the dynamics will be, but I expect that some of it will be a substitute away from traditional SaaS and by the way, I don't say that in an old company and new company sense. [SPEAKER_02] Like some SaaS companies are doing an amazing job reinventing themselves as AI first. [SPEAKER_02] And so you will have AI arms of traditional SaaS companies that are eating some of the revenue from the traditional version of the same company, but some will come from SaaS. [SPEAKER_02] I think some will come from. [SPEAKER_02] I think some of the things that are going to be a little bit more about. [SPEAKER_02] It is very hard to believe that companies will start spending single digit, sometimes double digit percentages of their headcount OPEX in LLMs and not step back and say okay, well, my headcount OPEX, my headcount cost just changed. [SPEAKER_02] You know, it used to cost me $300,000 for an engineer and now it costs me $330,000 for an engineer because $300,000 of them is salary and equity and $30K is LLMs. [SPEAKER_02] And so I better reason about my budget on a plus 10% basis and make headcount decisions accordingly. And by the way, ROI decisions as well. And then some of what we are seeing is definitely substitution now across AI providers. So I was looking at retention rates for AI companies. [SPEAKER_02] And what you see is actually the within the domain. [SPEAKER_02] So for example, within AI dev tools or AI coding tools or AI model providers, the retention rate, both B2C and B2B, is higher than it was for SaaS. Interesting. [SPEAKER_00] I'm shocked. [SPEAKER_00] But within. [SPEAKER_00] Okay, got it. [SPEAKER_00] Got it. [SPEAKER_00] Yeah. [SPEAKER_00] But for the individual provider, it's slightly lower. Yeah. Right. Which is intuitive. Once you start, which is ex post intuitive, although ex ante, I actually literally didn't know and needed to query the data. But ex post it's intuitive. It's once you start using an AI dev tool, a coding assistant, you love it, you're not going to stop using it, but you very well may iterate across providers as models vary in their quality or anytime a new model comes out, you're just like, I got to try this. [SPEAKER_00] Yes. [SPEAKER_00] And there's a high percentage of curious travelers basically hopping from one thing to the next within a category. [SPEAKER_00] But they're definitely going to stick using a tool like that for a long time. [SPEAKER_00] Yes, exactly. [SPEAKER_02] And so I would say a lot of the crazy fast AI growth we've seen is net new dollars spent. [SPEAKER_02] But I think businesses are going to start to reason about that as a substitute for SaaS or that as a substitute for headcount OpEx or that as a substitute for other AI companies. [SPEAKER_02] Anytime a new model comes out, you're just like, I got to try this. [SPEAKER_02] Yes. And there's a high percentage of curious travelers hopping from one thing to the next within a category. But they're definitely going to stick using a tool like that for a long time. Yes, exactly. And so I would say a lot of the crazy fast AI growth we've seen is net new dollars spent. [SPEAKER_02] But I think businesses are going to start to reason about that as a substitute for SaaS or that as a substitute for headcount OpEx or that as a substitute for other AI companies. And it will be less purely additive in the go forward year than it was in the past year when people were really just starting to ramp up on their AI spend. [SPEAKER_02] Does that imply anything to you about the valuations of current hot AI companies? Let's accept from this the OpenAI's and Anthropics of the world, but the 30 million cohort from this cohort and the coming up ones, does that say anything to you about their prospects or their growth rates or their valuation? Well, if you look at the top hundred on Stripe, there are little pockets of twos and threes that are directly competitive, but a bunch of them are solving totally disjoint vertical problems with no competitor yet in the space. And so I do think there's enough blue ocean vertical solutions that I think overall AI valuations are probably okay. [SPEAKER_02] I think there's a couple of crowded spaces that you and I could intuitively reason about where you might think it would be a little frothy. And by the way, you see this in the macro view, but you see this in the micro view too. If you look at sales-led growth contracts, when you are the first AI dev tool, you basically charge people sticker and you do very little negotiations and enterprise pay you sticker. And then all of a sudden you have to have much more complex sales. I mean, you hire a bunch of sellers and you have your CPQ configure price quote system and you have this nuanced billing because you're competing against two or three other providers who have competitive-looking monetization models and you're reacting to that. And so on the micro, you start to see some of those competitive reactions creeping in as well. But I think the overarching next year will continue to have a bunch of blue ocean vertical stuff that didn't exist before. But there will be some pockets where it's a little more heated. [SPEAKER_02] Fascinating. I feel like I'm learning so much. This is amazing. I want to go into Stripe instead of talking about the AI economy. I want to go into Stripe a little bit. But specifically, Stripe serves developers and you're built for a world where humans are the ones buying and selling and also humans are the ones making the software. Now agents are buyers, they're sellers, they're builders. And you have to serve agents. And I'm curious how that has changed how you think about the products that you offer and moving from just thinking about developer experience to agent experience. Do you want to start with agent experience or agent.com? I think they're both different, but they're both really interesting. Which one are you most excited to talk about? [SPEAKER_00] Maybe agent experience and then we can work backwards to agent.com. [SPEAKER_00] Yeah. Let's talk about agent experience. [SPEAKER_00] Okay. So the developer story—well, the whole idea of developer experience is changing. Historically, when I said developer experience, you thought, "Hey, making it easier for a human engineer who's at a keyboard." So you need clear APIs and you need better docs and you need less setup work. And all of that still matters. It's not going anywhere. But I think that the developer is now a broader swath of persona. It could be a non-technical founder who's just in Vercel or Replit describing an app in plain language. Or it could be a coding assistant scaffolding an integration, or it could be an agent out trying to provision infrastructure on a human's behalf. And so I think it's less about just, "How do we help a human developer write code?" and more about, "How do we have a coherent and trustworthy product experience end to end that acknowledges that at some moments the actor is a human, at some moments the actor is an agent, and at some moments the actor is a human working through an agent?" [SPEAKER_00] And so you see this shift in some really concrete ways. Very simple example: LLM traffic to Stripe docs is up 10X year over year. And that's just a useful signal that machines are becoming users of developer infrastructure too, including Stripe's developer infrastructure. What about human use of Stripe docs? [SPEAKER_02] So human use of Stripe docs is actually flat to climbing. It's not like a straight substitute. I think there is just more developer activity happening and LLMs are growing dramatically within that share. [SPEAKER_02] That makes sense. Cool. [SPEAKER_02] I would also say humans continue to check on the docs to sanity check what the agent is coming up with, because your payments integration is actually a pretty big decision that you're making. [SPEAKER_02] I would say better humans than I are sanity checking, but I'm glad that someone is sanity checking. [SPEAKER_02] Are you YOLOing it? [SPEAKER_02] I'm YOLO vibe coding my payment infrastructure. [SPEAKER_02] Okay. Amazing. So maybe you're YOLO vibe coding, but even if you're vibe coding, there's still an important step around provisioning your modern software stack. And that is still very manual. So you as a human are still creating accounts across multiple services, you're managing credentials, you're clicking through to do a lot of setup. You're probably bouncing between dashboards. And so the coding is getting easier a lot faster than the setup is getting easier. And that's actually the idea of Stripe Projects, which we launched maybe two weeks ago. It's basically— [SPEAKER_02] It looks amazing. Tell people what that was. [SPEAKER_02] Okay. If you want in, let me know. We can get to it. I want in. I absolutely want it. You're in. Check. I won't Slack right now, but I'll Slack right after this and get it. And that's actually the idea of Stripe projects, which we launched, I don't know, maybe two weeks ago. [SPEAKER_00] It looks amazing. Tell people what that was. [SPEAKER_02] Okay. If you want in, let me know. We can get to it. I want in. I absolutely want it. [SPEAKER_02] You're in. Check. I won't Slack right now, but I'll Slack right after this and get to it. But basically the idea of Stripe projects for those who haven't explored it, it's just like you or your agents can go create and manage parts of your software stack right from the command line. And so resources are provisioned in accounts you own and credentials sync back to your environment and so on. [SPEAKER_00] One of the things that stood out besides your enthusiasm for it, which I appreciate, is just how overwhelming the interest has been in general from the ecosystem. So we launched with Four Cell and Supabase, Post Hogs there, Neon, Runloop. There's a bunch of great companies involved, but then immediately after launch over a hundred other great companies reached out wanting to join, which I just think reinforces that the friction is real. And you talked earlier about some things get easier with AI, but there's a counter effect. You know, I think coding gets easier, but code reviews become more burdensome because who's reviewing all the AI code. This is another example of building gets easier, but you still have to provision everything. And so that's just an example of how we're building for this world where the developer is no longer just a human. [SPEAKER_00] Got it. And then tell me about agentic commerce. Okay, so agentic commerce is a bit of an overloaded term. And I think a mistake that people make with agentic commerce is they jump straight to the most extreme version. So they hear the phrase and they think some system that knows everything about me and decides what I need and goes off and buys it for me. And then they're underwhelmed with the world we're actually in. Maybe we get to that extreme eventually in some form, but we're not there yet. I prefer to think about it as a spectrum. And the economic infrastructure you need is actually pretty similar no matter where you are in the spectrum. But the spectrum also brings some realism to it. So at the first level, AI is just removing friction from the Internet we already have. Right. So it helps you research and compare options and fill out forms and narrow down your choices. But you, the human, are still making the decision. The agent is just making that experience easier. And then you move to descriptive search. Right. No more blunt keywords and filters. It's like I have little kids and I need a summer camp for my kids with this budget on these dates with this driving radius. And that's already a better commerce experience than search plus filter, which is blunt. And then you get to real delegation. And I think this is what most people would consider the minimum viable bar for saying agentic commerce. So I give some constraints, some camps, some budget, some dates, some category, maybe a few preferences. And then the system goes and makes the purchases on my behalf. But then there's the further out version, which is the ambient version. Right. I don't prompt anything. And the system knows me and it knows my seasonal needs and it knows summer camp planning is happening. That would be music to my ears. And that's the most futuristic thing. I think the point is that no matter where you are on that spectrum, what the Internet needs for economic infrastructure starts to change. Right. Even the earlier stages force a redesign of payments infrastructure in particular, because the today model, the old model, human sitting in front of browser, creating account, choosing plan, filling out forms, clicking purchase, entering card details. Not all those steps are happening anymore. And so I think there's two worlds that I reason about. One is agent-assisted buying. So I'm ultimately in charge. But the discovery and checkout and payment happen inside interfaces instead of on a merchant website. So I'm not going to Nordstrom. I'm buying within Gemini or ChatGPT or Meta like Facebook ads. Whatever. And what's challenging here is two things. One, the agent needs to be able to understand the merchant's products and prices and checkout flow so that they can act on behalf of the consumer. And two, as you and I talked about at the top, trust can break down. Right. As a consumer, I don't want to hand off my credentials to an agent. As a merchant, I don't want to let just every bot through. I want to know if it's a good bot acting on behalf of a legitimate customer. So the agent to commerce protocol, which we co-created with OpenAI, is just the shared technical language between AI systems and businesses. And it shows up across a lot of surfaces. Again, we built it with OpenAI, but Microsoft Copilot uses it. Meta's in-ad shopping experience uses it. And how it works is the merchant only has to integrate once with Stripe for their product catalogs, their prices, their checkout flows. And then they can literally from the dashboard turn themselves on through a whole host of agents and be exposed through those shopping experiences. Importantly, the merchant remains the merchant of record. And that part really matters. Businesses want access to these new storefronts, these new channels, but they don't want to give up the customer relationship. They don't want to give up control over trust or fraud. So kind of category one is the human is still sort of leading the buying, but the agent is facilitating the transaction. You could call it agent of commerce. You could call it facilitated commerce. And how does that actually work? So is the experience something like I'm in ChatGPT and it says, hey, here's a thing you might want to buy. And I can click checkout from OpenAI. And that's using that protocol to then go send my information to the merchant and then send me back, hey, here's your things on the way. That's what you're talking about. Exactly. So it's one click checkout. Yeah. Same thing. You're in Facebook, you get an ad in Meta. You do one click checkout. And one of the primitives that we built for this is the shared payment token or SPT. And it's basically just letting your payment credentials be passed securely from the AI agent to the merchant. Hey, here's your things on the way. That's what you're talking about. Exactly. So it's one click checkout. Yeah. Same thing. You're in Facebook, you get an ad in meta. Let's say you do one click checkout. And one of the primitives that we built for this is the shared payment token or SPT. And it just lets your payment credentials be passed securely from the AI agent to the merchant. [SPEAKER_02] So the merchant can process the transaction and the merchant processing the transaction is important because that allows the merchant to remain the merchant of record. [SPEAKER_02] But you don't want your credentials viewed by the agent, which is why it's a token and not your actual payment credentials. [SPEAKER_02] And the merchant needs to know that you and the agent are good, which is why as part of the shared payment token, we pass over a whole host of fraud scores. [SPEAKER_02] And can I integrate this? So we have a CLI, we have a bunch of software. Can I offer agentic checkout easily? Or does it have to go through the open AIs and the Facebooks of the world? [SPEAKER_02] So yes, you can. And I think one of the premises here is just like to date, we haven't seen one model provider to rule them all or one model to rule them all. [SPEAKER_02] We don't think there's going to be one agentic shopping experience to rule them all. And merchants will literally break if they have to integrate with every single potential new storefront, right? [SPEAKER_02] When they integrated with the internet, they built their own storefront and they iterated on it, but they built it once. But if you tell them, hey, you need to build your storefront for agent startup shopping startup X and Fia and open AI and Meta, their eyes are going to get bigger than their heads and they're not going to be able to handle it. And so we really want to abstract away that complexity for businesses. We spent the last decade plus helping businesses sell wherever their customers are. And first that was on their websites and then it was in apps and then it was through platforms and marketplaces and actually some in person too with our terminal product. [SPEAKER_00] But now where are the consumers, where are they wanting to buy increasingly through AI tools and agentic flows? [SPEAKER_00] And so similarly, we just want to make it really easy for merchants to agnostically participate in those different storefronts. [SPEAKER_00] And you can choose where they want to sell, they can turn it on, a little toggle in the dashboard, but it's not a different integration, which is the whole idea of the protocol. [SPEAKER_00] And then how often is this happening? What's the volume of agentic commerce right now? The volume of consumer commerce is still relatively small, relatively small as a percentage of all of the commerce we see. But it is growing quickly, particularly for what I would think of as commodities, right? [SPEAKER_02] So what is the first thing that people are comfortable buying through agents? It's things that are reasonably known, reasonably observable, not super high priced. [SPEAKER_02] You know, when people started buying online, you didn't imagine that they were going to go online and buy a $2,000 couch, right? [SPEAKER_02] Wasn't the couch a thing? You really want to know the quality and you want to sit in it. A mattress. [SPEAKER_02] Oh my God, these mattress companies that have blown up, and it took time for them to build comfort, making higher price purchases, making more quality dependent purchases. And so today it's predominantly commodities. In a similar vein, I've tried to book a whole summer trip using an agent. And I wasn't sufficiently satisfied with the family of four choice of flights and hotels and transportation and itinerary to be willing to one click buy it. But the models will get better. The interfaces will get better. The experiences will get better. We're pretty agnostic to those. We trust that they will evolve in different and interesting ways and the primitives that are needed underneath—the ability to expose your catalog, the shared payment token, the fraud protections—are pretty agnostic to those experiences. [SPEAKER_02] And so that's where we're hyper-focused for merchants. [SPEAKER_02] Give me an example of one of these commodities and also what the order of magnitude we're talking about when we say it's relatively small. An example of a commodity would be a Halloween costume. Got it. Agents are buying Halloween costumes for themselves? [SPEAKER_00] Agents are buying Halloween costumes. [SPEAKER_00] That's really funny. [SPEAKER_00] How many lazy parents there are in the world? [SPEAKER_00] I mean, I think the consumer side is interesting too, right? Because we talked about what do businesses need, right? They need a fast, easy way to safely expose their products, their prices, their inventory, their checkouts, understand fraud and be in control of the relationship. From the consumer angle, the question's a little different, right? Even if I'm a lazy parent, I'm not so lazy that I'm willing to give someone my payment credentials and let it rip. So the question for me is how do I safely let an agent buy on my behalf? And have you heard of Link? [SPEAKER_02] Yeah, I've used Link. [SPEAKER_02] Okay. [SPEAKER_02] Amazing. [SPEAKER_02] So Link is our consumer wallet. [SPEAKER_02] What did you use it for? [SPEAKER_02] Do you remember the first thing you used it for? I mean, I use it all the time. It's everywhere. [SPEAKER_02] So. Amazing. Yeah. [SPEAKER_02] It's everywhere, right? I was getting soccer lessons for one of my kids from a local guy. [SPEAKER_02] And I was on their website and they only accepted Visa and MasterCard, neither of which I had on me or direct debit from my bank account, which I wasn't going to put in this very janky website or Link. [SPEAKER_02] And I was like, Oh, amazing. Link is here. Anyway, a lot of people know about Link as our consumer wallet for buying soccer classes. It speeds up checkout, but it's also used by about a quarter of a billion consumers. So it's not a small network, but what I think is most interesting about Link is it's a very dense network when it comes to AI. So Lovable is an interesting example. 58% of their payment volume runs through Link. You are hyper AI pilled. It is not surprising that everywhere you are, Link is. And so what's changing now is that we're evolving Link for the AI economy because so many of the Link consumers are already AI consumers and acknowledging that agents themselves are becoming economic actors. And so the model isn't give a random agent your card and hope for the best. [SPEAKER_00] Instead, it's delegated authority with guardrails. So it's not a small network, but what I think is most interesting about Link is it's a very dense network when it comes to AI. Lovable is an interesting example. 58% of their payment volume runs through Link. [SPEAKER_02] You are hyper AI pilled. It is not surprising that everywhere you are, Link is. And so what's changing now is that we're evolving Link for the AI economy because so many of the Link consumers are already AI consumers and acknowledging that agents themselves are becoming economic actors. And so the model isn't give a random agent your card and hope for the best. Instead, it's delegated authority with guardrails. [SPEAKER_02] So you as a consumer decide which agents are allowed to request credentials and under what conditions and with what limits and whether those purchases require approvals before they go through. [SPEAKER_00] And you do all of that through Link. [SPEAKER_00] And it's just a much more sensible model for delegated purchases. [SPEAKER_02] That makes sense. [SPEAKER_00] Emily, this was a fantastic conversation. [SPEAKER_02] I learned so much. Awesome. Thank you for having me. Thank you. Thank you. I want in. I absolutely want it. You're in. Check. I won't Slack right now, but I'll Slack right after this and get to it. But, but basically the idea of Stripe projects for those who haven't explored it, it's just like you or your agents can go create and manage parts of your stuff, software stack right from the command line. And so, you know, resources are provisioned in accounts you own and credentials sync back to your environment and so on. And one of the things that stood out besides your enthusiasm for it, which I appreciate, is just how sort of overwhelming the interest has been in general from the ecosystem. So we launched with like for cell and Supabase, Post Hogs there, Neon, Runloop. There's a bunch of great companies involved, but then immediately after launch over a hundred other great companies reached out wanting to join, which I just think reinforces that like the friction is real. And you talked earlier about like, you know, some things get easier with AI, but there's like some counter effect. You know, I think coding gets easier, but like code reviews become more burdensome because who's reviewing all the AI code. This is another example of like building gets easier, but you still kind of have to like provision everything. And so that's just an example of how we're building for this world of like the developer is no longer just a human. Got it. And then tell me about agentic commerce. Okay, so agentic commerce is a bit of an overloaded term. And I think a mistake that people make with agentic commerce is they jump straight to kind of the most extreme version. So they hear the phrase and they think like some system that knows everything about me and decides what I need and like goes off and buys it for me. And then they're underwhelmed with the world we're actually in. Like maybe we get to that extreme eventually in some form, but we're not we're not there yet. I prefer to think about it as a spectrum. And, you know, I think that the economic infrastructure you need is actually pretty similar no matter where you are in the spectrum. But the spectrum also like bring some realism to it. So at the first level, which is like, AI is just removing friction from the Internet we already have. Right. So it helps you research and compare options and fill out some forms and narrow down your choices. But you, the human are still making the decision. We're just making, you know, the agent is just making that that experience easier. And then you move to like, okay, search is descriptive. Right. No more like blunt keywords and filters and such. It's like I got little kids like I need a summer camp for my kids and this budget on these dates with this driving radius. And that's already a better commerce experience than like search plus filter, which is like, you know, knowably blunt. And then you get to sort of real delegation. And I think this is what most people would consider like the minimum viable bar for saying agentic commerce. So like I give some constraints, like I give some for camps, like some budget, some dates, some category, maybe a few preferences. And then the system goes and makes the purchases on my behalf. But then there's the further out version, which is like the ambient version. Right. I don't prompt anything. And the system knows me and it knows my seasonal needs and it knows, you know, summer camp planning is happening. That would be music to my ears. And sort of that's the that's the most futuristic thing. I think the point is that no matter where you are on that, like what the Internet needs for economic infrastructure starts to change. Right. Even the earlier stages force a redesign of payments infrastructure in particular, because the today model, the old model, again, human sitting in front of browser, creating account, choosing plan, filling out the forms, clicking purchase, entering card details. Not all those steps are happening anymore. And so, you know, I think there's sort of two worlds that I reason about preparing for one is agent assisted buying. So I'm ultimately in charge. But the discovery and checkout and payment happen inside interfaces instead of on a merchant website. So I'm not going to Nordstrom. I'm buying within Gemini or ChatGPT or, you know, meta like Facebook ads. Whatever. And what's challenging here is two things. One, the agent needs to be able to understand the merchants products and prices and checkout flow so that they can act on behalf of the consumer. And two, as you and I talked about a bit at the top, trust can break down. Right. As a consumer, I don't want to hand off my credentials to an agent. As a merchant, I don't want to let just every like bot through. I want to know, is it like a good bot acting on behalf of a legitimate customer? So the agent to commerce protocol, which we we co-created with OpenAI is just the shared technical language between AI systems and businesses. And it shows up across a lot of surfaces. Again, we built it with OpenAI, but Microsoft Copilot uses it. Meta's in-ad shopping experience uses it. And how it works is is basically the merchant only has to integrate once with Stripe for their product catalogs, their prices, their checkout flows. And then they can literally from the dashboard, turn themselves on through a whole host of agents and be exposed through those through those shopping experiences. Importantly, the merchant remains the merchant of record. And that part really matters, like businesses want access to these new storefronts, these new channels, but they don't want to give up the customer relationship. They don't want to give up control over trust or fraud. So kind of category one is the human is still sort of leading the buying, but the agent is like facilitating the transaction. You could call it agent of commerce. You could call it facilitated commerce. And how does that actually work? So is the experience something like I'm in ChatTBT and it says, hey, here's like a thing you might want to buy. And I can click checkout from OpenAI. And that's using that protocol to then go send my information to the merchant and then send me back. Hey, like here, here's your, your, your things on the way. That's kind of, that's what you're talking about. Exactly. So it's like one click checkout. Yeah. Same thing. Like you're in Facebook, you get an ad in meta. Let's say you do like a one click checkout. And, you know, one of the primitives that we built for this is the shared payment token or SPT. And it's basically just, it just lets your payment credentials be passed securely from the AI agent to the merchant. So the merchant can process the transaction and the merchant processing the transaction is important because that allows the merchant to remain the merchant of record. But, you know, you don't want your credentials viewed by the agent, which is, you know, why it's, why it's a token and not your actual payment credentials. And the merchant needs to know that you and the agent are good, which is why as part of the shared payment token, we pass over a whole host of, of fraud scores. And can I integrate this? Like, so we have a CLI, we have a bunch of software. Can I offer a agentic checkout easily? Or does it have to go through the open AIs and the Facebooks of the world? So, yes, you can. And I think one of the, one of the premises here is, you know, just like to date, we haven't seen one model provider to rule them all or one model to rule them all. We don't think there's going to be one agentic shopping experience to rule them all. And merchants will literally break if they have to integrate with every single potential new storefront, right? When they integrated with the internet, they built their own storefront and yeah, they iterated on it, but basically they built it once. But if you tell them, hey, you need to build your storefront for, you know, agent startup, shopping startup X and FIA and open AI and Meta, like their eyes are going to get, you know, bigger than their heads and they're not going to be able to handle it. And so we really want to abstract away that complexity for businesses. Like we spent the last decade plus helping businesses sell wherever their customers are. And first that was like on their websites and then it was in apps and then it was through platforms and marketplaces and actually some in person too with our terminal product. But now like, you know, where are the consumers, where are they wanting to buy increasingly through sort of AI tools and agentic flows? And so similarly, we just want to make it really easy for merchants to agnostically participate in those different storefronts. And again, you can choose where they want to sell, they can turn it on, little toggle in the dashboard, but it's not a different integration, which is the whole idea of the protocol. And then how often is this happening? Like what, what's the volume of agent com, agentic commerce right now? The volume of consumer commerce is still relatively small, relatively small, relatively small as a percentage of all of the commerce we see. But it is growing quickly, particularly for, you know, what I would think of as commodities, right? So what is the first thing that people are comfortable buying through agents? It's like things that are reasonably known, reasonably observable, not super high priced. You know, I think when, when people started buying online, like, you didn't imagine that they were going to go online and buy like a $2,000 couch, right? Oh, wasn't the couch a thing? You really want to know the quality and you want to sit in it. A mattress. Oh my God, these mattress companies that have blown up, you know, and it took time for them to build comfort, you know, making higher price purchases, making more quality dependent purchases. And so today it's, it's, it's, it's predominantly commodities, you know, in a similar vein, I've tried, you know, to, to book a whole summer trip using, using an agent. And I wasn't sufficiently satisfied with, you know, the family of four choice of flights and hotels and transportation and itinerary to be willing to, to one click buy it. But the models will get better. The interfaces will get better. The experiences will get better. We're pretty agnostic to those. Like we trust that they will evolve in a bunch of different and interesting ways and sort of the, the primitives that are needed underneath the ability to expose your catalog, the shared payment token, the fraud protections are pretty agnostic to those experiences. And so that's where we're, we're hyper-focused for merchants. Give me an example of one of these commodities and also what the order of magnitude we're talking about when we say it's relatively small. An example of a commodity would be like a Halloween costume. Got it. Agents are buying Halloween costumes for themselves? Agents are buying Halloween costumes. That's really funny. How many lazy parents there are in the world? I mean, I think the consumer side is interesting too, right? Because we talked about what do businesses need, right? They need a, they need a fast, easy way to safely expose their products, their prices, their inventory, their checkouts, understand fraud and be in control of the relationship. From the consumer angle, the question's a little different, right? Like even if I'm a lazy parent, I'm not so lazy that I'm willing to give someone my payment credentials and, you know, let it rip. So like the question for me is how do I safely let an agent buy on my behalf? And have you heard of Link? Yeah, I've used Link. Okay. Amazing. So Link is our consumer wallet. What did you use it for? Do you remember the first thing you used it for? I mean, I use it all the time. It's like everywhere. So. Amazing. Yeah. It's everywhere, right? It's because you wouldn't believe where it, I was like, I was getting soccer lessons for one of my kids, like, you know, from a local guy. And I was on their website and they, they only accepted Visa and MasterCard, neither of which I had, you know, on me or, you know, direct debit from my bank account, which I wasn't going to put in this very janky website or Link. And I was like, Oh, amazing. Link is here. Anyway, a lot of people know about Link as our consumer wallet for buying soccer classes. It speeds up checkout, but it's also so, and, and it's already used by about a quarter of a billion consumers. So it's not a small network, but what I think is most interesting about Link is it's a very dense network when it comes to AI. So lovable is an interesting example. 58% of their payment volume runs through Link. You are hyper AI pilled. It is not surprising that everywhere you are, Link is. And so what's changing now is that we're evolving Link for the AI economy because so many of the Link consumers are already AI consumers and acknowledging that like agents themselves are becoming economic actors. And so the model isn't, you know, give a random agent your card and hope for the best. Instead, it's delegated authority with guardrails. So, you know, you as a consumer decide which agents are allowed to request credentials and under what conditions and with what limits and whether those purchases require approvals before they go through. And you do all of that through Link. And it's just a much more sensible model for, for delegated, for delegated purchases. That makes sense. Emily, this was a fantastic conversation. I learned so much. Awesome. Thank you for having me. Thank you. Thank you.