How Stripe Is Building for an Agent-native World

Emily Glassberg Sands leads data and AI at Stripe, which processes roughly 2% of global GDP, giving her a bird’s-eye view into how AI is upending the internet economy. Dan Shipper talked with Glassberg Sands for Every's AI & I about what the data on Stripe's network actually shows: AI companies are scaling three times faster than the top SaaS cohort of 2018, fraud has moved from the checkout to the full funnel, and agents have started buying things, although mostly low-stakes commodities like Halloween costumes. The conversation covers the new fraud types unique to AI companies, the AI-on-AI arms race between bad actors and fraud detectors, where AI revenue growth is actually coming from, and how Stripe is rebuilding the payments infrastructure for a world where the buyer is an agent. If you found this episode interesting, please like, subscribe, comment, and share! To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Head to http://granola.ai/every and get 3 months free with the code EVERY Timestamps 00:00:45 Introduction 00:01:27 New rules for an agent-driven economy 00:03:57 Compute theft is the new payment fraud 00:10:00 How Stripe expanded fraud detection from checkout to the full customer lifecycle 00:19:48 Why AI companies are scaling way faster than top SaaS companies 00:23:27 Outcome-based billing is replacing seat-based pricing 00:29:57 Where AI spending is coming from 00:36:45 How the developer experience changes when agents are the builders 00:41:00 The agentic commerce spectrum, from assisted buying to autonomous purchasing 00:51:06 Meet Link, a consumer wallet for delegated agent purchases Links to resources mentioned in the episode: Emily Glassberg Sands on X: https://x.com/emilygsands Stripe: https://stripe.com Stripe Radar: https://stripe.com/radar Stripe Link: https://link.com Lovable: https://lovable.dev

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  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.

• 0:44Dan Shipper?

  Emily, welcome to the show.

• 0:45Speaker 00

  Thanks so much, Dan.

• 0:47Dan Shipper?

  So, really excited to have you. 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. 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 a thing where, 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?

• 1:26Speaker 00

  Yeah, so a big shift, I think, we're in the midst of is that the internet economy is becoming more autonomous, right? So for a long time, for forever, right? The internet was built around an extremely simple assumption that the main actor was a person. And the person's sitting in front of a screen and they're browsing and they're filling out forms and clicking through checkout. But also, they're writing code and setting up tools. And that assumption is starting to break in various ways, right? 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. Sometimes the agent is acting on their behalf. And then sometimes, software now is just out in.

• 2:10Speaker 00

  Interacting directly with other software. And as all of that starts to happen at all of those layers, a lot of things need to be rethought. So, you know, there has been rethinking of how our products discovered and how our products bought, but also what should developer tools look like? And, you know, in our world of Stripe, like, 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, you know, actors are no longer just humans. And so that, for me, is kind of the larger frame of the moment. It's not just, hey, AI is making search better, or AI is helping people code,

• 2:53Speaker 00

  or AI is, you know, 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, basically, every layer of the stack starts to need an evolution. So for Stripe, it's like, okay, 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.

• 3:26Dan Shipper?

  And can you give me some specific examples of the kinds of things you're seeing? Like, I'm almost wondering, for example, I know at Stripe, one of the things you do a lot of a ton is fraud. A, I assume there's a whole new type of fraud happening. But B, I'm almost wondering what even counts as fraud now? In the sense of, it's possible that my agent could go steal someone's credit card and check out. I don't think that Claude would, but like, you never know with Grok, you know? Check out on-

• 3:55Speaker 00

  No comment, no comment. But you're right that sort of AI introduces very different fraud problems. You asked, what is fraud? We used to think of fraud as sort of payment fraud. Someone was stealing money, someone was stealing your card credentials. Increasingly, actually, and I was in a meeting with one of our very large AI users today, fraudsters are stealing compute. And that's a very different type of problem. So in earlier software models, if you think of like sort of traditional SaaS, letting someone into a free tier didn't cost you very much. And stealing a free tier wasn't very valuable to the fraudsters. Now, giving someone credits, freemium offering, a free trial,

• 4:40Speaker 00

  you know, letting them, you know, 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, right? Because in AI, every prompt, every image that gets generated, every API request has a very real cost attached to it. You know, people are talking about intelligence getting cheaper. Yeah, but it's still like very far from, from free. And then also, when you look at sort of the growth model for many of these AI companies, free compute is kind of the new CAC, right? You used to, cost of acquisition, like you used to spend a bunch on paid media, now you spend a bunch on your free trials and your credits and your self-serve onboarding

• 5:23Speaker 00

  as sort of 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 this is like, bad actors come in and they sign up like 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 like 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, non-trivial share.

• 6:05Speaker 00

  The second trend that we see in sort of new vector of abuse is free trial abuse. And this is often sort of 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.

• 6:30Speaker 00

  Um, you know, 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 sort of 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 abusing your systems. Um, and so, you know, some companies uh just dropped free trials altogether. Of course, that's not great because you're throttling growth. Um, others responded by blocking virtual cards. So, um, I don't know how often you've been marketed virtual cards.

• 7:14Speaker 00

  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. Um, you know, in the hands of a good consumer, fine. In the hands of a fraudster, like 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.

• 7:39Dan Shipper?

  We use that all the time for ramp, for example, like we have a bunch of virtual cards.

• 7:42Speaker 00

  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 um virtual card um virtual cards either. Um, and sort of order of magnitude, you can think of like exponential growth in free trial abuse over the last six months. It's four Xed. Um, and uh for um one large AI user on Stripe, we're currently blocking 250,000 fraudulent free trials a week. Um, so the magnitudes here are quite high.

• 8:14Dan Shipper?

  And is the, is it, is the, the volume of fraud constant? It's just, it's shifting shape or it's just fraud going up because they're more powerful now because they can just use AI agents to do it?

• 8:26Speaker 00

  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? Like, I don't know, you steal traditional SaaS, like, what good do you get? Like, you steal some inference, you steal some compute, you can resell it, you can do all sorts of stuff.

• 8:46Dan Shipper?

  Look, I love a good CRM seat, you know?

• 8:49Speaker 00

  Don't you? Who doesn't love a good CRM?

• 8:51Dan Shipper?

  Don't tempt me, Emily.

• 8:52Speaker 00

  I don't think a good CRM seat is. Real LM's are for sure more tempting. And by the way, the third type of sort of new abuse we see is this non-payment abuse, right? So like, you incur an overage or you have like, you know, 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. And by the time they get billed and fail payment, you know, that loss has already happened. And these AI companies are left holding the bag. And so for us, like, fraud used to be a transaction thing. Now it is a customer thing. It is a full funnel thing. It starts at the time of signup.

• 9:37Speaker 00

  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-ups? Should we be blocking service completely? And it's just kind of, it's kind of a whole new world because the thing to steal is much more valuable and the cost of having it stolen is much more existential.

• 9:59Dan Shipper?

  How are you guys even able to? I saw, so I totally understand how you need to be in that full funnel in order to detect fraud. But my understanding of, you know, whenever we've integrated Stripe, it's usually like on the checkout. We're not necessarily putting you in there when someone puts in their email address for free. So have you changed the product to do the full funnel? Or how does that actually work?

• 10:22Speaker 00

  Yes, so Radar, which is our fraud protection product, used to be at the transaction level, right? So at the moment of checkout, as you note. But because so much of the fraud risk was coming up funnel, you know, AI companies are now increasingly integrating Stripe Radar at the time of signup. And so, you know, we see the metadata at the time of signup. We pass back scores at the time of signup. And every moment subsequently, again, because fraud is...

• 10:52Speaker 00

  Now a full funnel problem, not a transaction problem alone.

• 10:55Dan Shipper?

  If you're, you know, asking for a friend, if you're in, running an AI company and you are, you don't even know what your fraud rate is and you're, you want to protect yourself from this kind of abuse. What are the like top things you need to do in order to make sure that you're reasonably safe?

• 11:15Speaker 00

  Yeah, so I would just adopt our highest tier radar plan, but, but the actual mechanics of that are at signup, you want to know if your customer is good. Before you give them any access to any credits, 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 that, and you know, there, there's other stuff around refunds and disputes that we also support. But I think those are the four kind of major moments in the AI company's customer lifecycle. Where we're just maniacally focused on protecting because that's where we're seeing the biggest cost and, and the fastest fraud growth.

• 11:58Dan Shipper?

  And at each point, that's just a call to the radar API?

• 12:01Speaker 00

  Yes, correct.

• 12:03Dan Shipper?

  And what if I'm sitting here, which I am doing, you know, millions of dollars a year in Stripe transactions, but I actually have no idea what my fraud rate is other than there's like that little, there's that little thing where it's, it's not even, I don't even know if it's necessarily our fraud rate. I think it's our, our card charge back. Anyway, our fraud rate is low enough as marked for me to not care about it. 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. So what are the things I should be looking for? To, uh, to know if I should dig deeper and potentially do some sort of, for example, radar integration?

• 12:40Speaker 00

  Yeah. So, 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 like, you know, I have a high marginal cost business, in which case, you know, you, you care more about certain types of fraud than others. But you can also just take a stab at integrating a funnel and, and see how it performs. We, we can certainly.

• 13:09Speaker 00

  You know, share with you based on backtesting what we think the big issues are. But the but the fastest way to get a clean read is is just to integrate.

• 13:17Dan Shipper?

  Got it. So I would so I don't think that we're integrated right now. So I would just go look at go look at radar and see does it doesn't 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 are at zero percent fraud. How is that possible?

• 13:35Speaker 00

  I don't know.

• 13:37Dan Shipper?

  Uh, point zero two percent early fraud warnings, total fraud rate point two percent. So we're I, you know, we're doing pretty good, right?

• 13:43Speaker 00

  That's pretty low. That's pretty low. I mean, yeah, you're a pretty good human. Maybe the fraudsters don't want to come after you. And then they'll be like, yeah.

• 13:54Dan Shipper?

  Okay, that's really interesting. Okay, so that's that's fascinating. I want to go back a second to the to the AI economy because one of the

• 14:03Dan Shipper?

  one of the things you said earlier is fraud is increasing overall on the internet. And that it's also it's increasing because the fraudsters have AI. But that it's also you all and everyone else on the side of good in the in the AI economy also has AI to defend against these sorts of attacks.

• 14:20Dan Shipper?

  I think you're getting a you're getting an interesting window into the arms race that I think is playing out in lots in in lots of different areas that have this kind of threat vector. A really simple one is cybersecurity. Not just for like payments, but for hacking and stuff like that. But there's 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 to to to catch up. So how is that race going? What is that like? What are the early reports that you're that you're seeing and feeling? Being in being in a race with AI armed fraudsters?

• 14:59Speaker 00

  I think the interesting thing about fraudsters is they don't really care about boundaries. They don't care about, you know, whether this transaction is processed on Stripe or off Stripe. They don't care about whether this transaction is on, you know, fiat or crypto, whether it's on a card network or a buy now, pay later. They're just going to figure out sort of 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, you know, a simple example in our world,

• 15:39Speaker 00

  sort of Stripe Radar used to only work for cards 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

• 16:08Speaker 00

  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

• 16:47Speaker 00

  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, like, overall, like, yes, fraudsters have AI in their favor. Stripe looks at Two percent of global GDP and is growing thirty four percent year on year and sees a broader swath through our multi processor 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 kind of eke ahead.

• 17:31Speaker 00

  Now, that's not to say that we're not constantly surprised by the new creative vectors they come up with. But, you know, 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.

• 17:58Dan Shipper?

  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?

• 18:12Speaker 00

  I mean, I think, you know, the AI economy is 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 sort of vertical AI solutions. People like to call them wrappers and I say that not condescendingly, just as in like, 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,

• 18:50Speaker 00

  you know, healthcare or architecture or whatever, who have a pretty unique view into vertical level adoption of of AI.

• 19:02Speaker 00

  But I guess I'd be curious like what you have in mind on who has the best, the best horizontal view?

• 19:09Dan Shipper?

  You're asking me?

• 19:10Speaker 00

  Yeah.

• 19:11Dan Shipper?

  Well, I'm, I, you know, I want to know what it, what it looks like on the payment side, but.

• 19:19Dan Shipper?

  I imagine, I imagine the model companies have, have the best one overall because they're, that's where all the tokens are going.

• 19:27Speaker 00

  Yeah, yeah, I think they see a lot of the tokens. I think the AI gateways also have a pretty unique perspective into, you know, who's buying what from whom. You know, as I step back and look at the AI economy from the Stripe vantage point and, and we see, you know, who's buying what from whom for how much, who's retaining and churning their subscriptions. There's a few, a few themes that stand out. One is just, and I think people feel this intuitively, but not everyone has like seen it in the data. These AI companies are just growing from a revenue perspective faster than any previous cohort we've seen. I was looking at the top 100 AI companies on Stripe and the

• 20:09Speaker 00

  ones that reached 30 million in ARR get there in about 18 months, so a year and a half. And, and that is like three times faster than the top 100 SaaS companies from 2018. And, and by the way, that's the 30 million number. But even if you look like, how fast do they make it to 1 million ARR or 5 million ARR, they are scaling like orders of magnitude faster than high performing SaaS companies from less than a decade ago. The second kind of meta trend is this like, and you probably feel it as a consumer, I know I do, this like very fast iteration across monetization models, right? So traditional SaaS had a lot of, you mentioned

• 20:51Speaker 00

  the seat, had a lot of seat based usage, you know, fixed monthly subscriptions. That made sense for them because they were being used by humans primarily and their marginal costs were basically zero. But, you know, we've talked about the very real inference costs in the context of fraud. Those also have very real implications for how you price. And so, usage based billing has become very important, very quickly. Companies are metering, you know, tokens and API calls, but they're also metering workflows and they're metering outcomes, kind of like whatever unit best Reflects both the the customer value and the cost structure.

• 21:34Speaker 00

  And then they're charging with like very high precision, right? They literally want to know every event. How was it rated? And what's all the metadata that sits on that rated event? Way more hybrid monetization models, right? So I talked about subscriptions, but subscriptions aren't dead. They're just subscriptions with like usage overages or like prepaid credits that burn down or real time top ups, which gets to my comment earlier on this non-payment abuse issue. And very kind of multi-dimensional pricing and monetization. Lovable is a really good example, right? So they they use Stripe billing for their initial launch, which was fairly simple subscriptions,

• 22:18Speaker 00

  sort of more traditional pricing and allowed them to monetize very quickly. And then they added a bunch of products like Lovable Cloud or Lovable AI. And they moved with those into usage based billing, right? So customers are actually charged based on token consumption. But it's a hybrid model, so it's above a certain threshold. And that just, you know, helps companies like Lovable align revenue with usage and value and the actual cost of running the models. And in the limit, you know, we actually have a solution called token billing, which is underlying model costs change a lot, sometimes very quickly. And if you are a rapper on top of someone else's LM and your pricing doesn't keep pace, then basically your margins can disappear, right?

• 23:03Speaker 00

  So, you know, costs go up and your price stays where it is, then you're in the red. And so token billing is just, hey, let's in real time track and price to the costs of the underlying tokens with some markup as set by the business. And so, you know, Misa and Ship and Lovable are all examples of this kind of kind of infrastructure.

• 23:24Dan Shipper?

  I love all of these points. I want to go through them one by one. So a big one that you're talking about is fast iteration across monetization. And it feels like there's this hyper experimentation going on right now where people are like, well, we could charge, we could charge per token, we could charge on a token basis, we could charge per completed request, like I think Finn, the customer service platform charges per case resolved, which has been a thing in customer service for a long time, but it feels like that it that could come for a lot more types of software as LMs make it easy to tell, did we actually do the work to get paid? What do you think is the? If we're, if we're gonna pick one, there's a whole range of exploration going on, but if we're gonna pick one

• 24:05Dan Shipper?

  new pricing model as the like, you know, if, if last year's pricing model or last decade's pricing model was just straight up per seat. What do you think is the new standard pricing model that, that is starting to emerge from, from the Stripe customers that you, that you see?

• 24:20Speaker 00

  If you are buying the model, so i- if you're primarily a model provider, or let's say your customers primarily buying the model. I think you're metering tokens.

• 24:32Dan Shipper?

  Like in an API, like OpenAI API, Cloud API, yeah.

• 24:36Speaker 00

  Exactly. For these vertical solutions.

• 24:42Speaker 00

  I think in steady state, you are metering outcomes. But it's gonna take us some time to get there, not because of the billing infrastructure. Actually, that's totally ready. You mentioned the Finn example. Intercom does the same thing. Actually, on Stripe Billing, they, they have an outcome based meter for, for support tickets resolved.

• 25:03Speaker 00

  Why do I say for vertical solutions, it's gonna be on outcomes? Because I think end users are gonna wanna hold those vertical solutions accountable for outcomes. And they're gonna wanna know that they have positive ROI on their spend. Now, when you and I buy a model, we feel like we ourselves are accountable for the ROI that we get on the whole plethora, wide range of applications we might have for that LLM. But if you're a vertical provider, if you're really focused on like solving a concrete need in a given business domain on top of someone else's LLMs, it seems like the core value, it's sort of, it's sort of on you

• 25:44Speaker 00

  to ensure the ROI is there. And I think outcome based pricing is, is the most efficient way to hit that. Now, I don't think all outcomes are created equal. And so you could imagine these like, I'm an economist by training, so I'll be a little nerdy, but like you could imagine these like complex objective functions where it's not just, did you resolve the sport case, but how complicated was it? And with what quality? And like, what was your CSAT? And you know, how expensive was the person that you were automating in that task? And so that's why I say in the limit, like 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 multi-dimensional. But I just have a hard time imagining. You know, a year from now, most vertical providers are literally charging on tokens.

• 26:29Dan Shipper?

  That's really interesting. I'm, I'm very curious to see that because what, what I felt, so I think you can see this a little bit in, in the example, in the level example you gave, but also in the Claude and chat GPT examples. And, and some of the pricing that we've ended up doing is it's per seat, it's per user with overages. Because we're, 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 kind of figure out how much I'm going to pay. But software used to be free to run and now it's not. And so we have to cover our butts basically and protect our margin by adding the, like the overage. So that customers basically know what they're going to pay unless there's some sort of spec, special circumstance.

• 27:14Dan Shipper?

  Do you see that? Where do you see that fitting in the examples that you gave? And, and, and I guess, I guess you would, you would say eventually that might go away. I'm curious why.

• 27:24Speaker 00

  So I don't think the, the charging for user, charging for overages will go away for like most of like the model providers. If anything, I think that will dominate and the seat based billing will go away. Like, you know, we can go back to like the Fin or Intercom example, like you, like you, well, you and I would think it's silly to charge based on number of customer service reps that we're using the tool. Because obviously a lot of what the tool is doing is automating customer service reps. In today's world, it isn't perceived as silly to do seat based usage of developer tools. But I think it's a fair question since basically November or December to say, wait, why isn't that silly?

• 28:02Speaker 00

  That seems a little silly because you know, if what these agents are doing is, um, you know, making every developer. Let's say, you know, I don't know, 10x 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 sort of the base price? So I suspect that we will see, uh, seat based disappear. Now, the, in, in the enterprise context. Now I think it's quite different in the, in the consumer individual context, I think.

• 28:41Speaker 00

  You know, 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 like crazy. But in businesses, I just, I would be super surprised if six months from now, we have half of the seat-based licenses that we have today.

• 29:03Dan Shipper?

  That is fascinating. Well, we will have to have you on again to talk about that one. I'm so curious to see, and I would love to see more Stripe data coming out about that. One other thing that you brought up before this was you're also seeing these companies scale faster. Like you said, that the time to get to 30 million in ARR is like 18 months, which is significantly faster than any other cohort of companies you've seen. I'm curious, where is that coming? Like presumably, the spend or the growth from their customers is coming from somewhere. Either it's spend that people weren't spending before it was like, you know, on their, on a company balance sheet just waiting to be deployed, or they're pulling it from another provider and then going really rapidly into these new ones.

• 29:49Dan Shipper?

  Do you have a sense for what's happening here? And where's all the, why are they growing so much faster? And where's all the money coming from?

• 29:55Speaker 00

  Yeah, so I think a lot of the AI growth that we've seen is actually like net new spend being pumped into the economy. I think it has largely not been a substitute for traditional SaaS or for sort of 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. So like, there weren't other AI companies to, to sort of

• 30:38Dan Shipper?

  Soak up the spend.

• 30:39Speaker 00

  Market share from. Um, I would say now going forward, um, I, I, 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. Just and, and by the way, I, I don't say that in a, you know, old company and new company sense. Like some SaaS companies are doing an amazing job reinventing themselves as AI first. 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. I think some will come from headcount OpEx. Like I, I, I is, it is very hard to believe that companies will start spending

• 31:21Speaker 00

  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. You know, it used to cost me $300,000 for an engineer and now it costs me $330,000 for an engineer because 300 of them is salary inequity and 30K is LLMs. And so I better reason about my budget on the, you know, plus 10% basis and make headcount decisions accordingly. Um, and by the way, ROI decisions as well. Um, and then some of what we are seeing is definitely substitution now across AI providers. So I was looking at, um, retention rates for AI companies.

• 32:06Speaker 00

  And what you see is actually the, within the domain, so for example, within AI dev tools or AI coding tools or AI model providers. Um, the retention rate, both B to C and B to B is higher than it was for SaaS.

• 32:23Dan Shipper?

  Um, interesting. I'm shocked.

• 32:25Speaker 00

  But, but.

• 32:26Dan Shipper?

  Within, okay, got it. Yeah.

• 32:28Speaker 00

  But for the individual provider, it's slightly lower.

• 32:32Dan Shipper?

  Yeah.

• 32:32Speaker 00

  Right? Which is intuitive. Like, once you start. Which is X post intuitive, although X ante I actually literally didn't know and needed to query the data. But X post is intuitive. It's like, once you start using, you know, AI dev tool, like a coding assistant, like you love it, you're not going to stop using it, but you very well may iterate across providers as, you know, models vary in their quality or.

• 32:56Dan Shipper?

  Anytime a new model comes out, you're just like, I gotta try this. And there's a, there's a high percentage of curious travelers, basically just 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.

• 33:13Speaker 00

  Yes, exactly. And so I would say like, a lot of the sort of crazy fast AI growth we've seen is like, net new dollars spent. 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, you know, people were really just starting to ramp up on, on their AI spend.

• 33:39Dan Shipper?

  Does that imply anything to you about the valuations of current, you know, hot AI companies? Like, let's, let's, let's accept from this, like the OpenAI is an anthropics of the world, but like the, in the 30 million cohort from, of this cohort and the coming, and the coming up ones, does that say anything to you about their prospects, or their growth rates, or their valuation?

• 33:59Speaker 00

  Well, so actually, if you look at like, the top 100 on Stripe, like, there are little pockets of twos and threes that are directly competitive, but a bunch of them are like, solving totally disjointed vertical problems with no competitor yet in the space. And so I do think there's like enough blue ocean sort of vertical solutions that I think overall AI valuations are probably okay. I think there's like, a couple of crowded spaces that you and I could intuitively reason about, where, you know,

• 34:35Speaker 00

  You might think it would be a little frothy. And by the way, you see this, that's sort of the macro view, but you see this in the micro view too. Like if you look at sort of the the sales led growth contracts, right? Like when there's a new, you know, 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 whatever. And then all of a sudden, you have to have these like much more complex. I mean, you hire a bunch of sellers and you have your, you know, CPQ configure price quote system and you have this nuanced billing because you're competing against two or three other providers who have like, you know,

• 35:19Speaker 00

  competitive looking monetization models and you're reacting to that. And so on the micro, you start to see some of those, some of those competitive reactions creeping in as well. But I think the I think the overarching kind of next year will continue to have a bunch of sort of blue ocean vertical stuff that didn't exist before. But there will be some pockets where it's it's a little more, it's a little more heated.

• 35:44Dan Shipper?

  Fascinating. I feel like I'm learning so much. This is amazing. I want to go into Stripe. Instead of talking about the AI kind of, I want to go into Stripe a little bit. Specifically Stripe is, you know, it serves, you serve developers and you're built for a world where humans are the ones buying and selling and also humans, humans are the ones making the software.

• 36:08Dan Shipper?

  Now agents are buyers, they're sellers, they're builders. And you're, so you have to sort of serve agents and I'm curious how that has changed. How you think about the products that you offer and the, you know, moving maybe from just thinking about developer experience to agent experience, all that kind of stuff.

• 36:30Speaker 00

  Do you want to start with agent experience or?

• 36:32Dan Shipper?

  I'll do it.

• 36:33Speaker 00

  I think they're both, they're they're kind of different, but they're they're both really interesting.

• 36:36Dan Shipper?

  Which one are you most excited to talk about?

• 36:40Speaker 00

  Maybe agent experience and then we can work backwards to

• 36:42Dan Shipper?

  Yeah, let's talk about agent experience.

• 36:45Speaker 00

  Okay, so you know, the developer story, well, so the the whole idea of developer experience is changing. And historically, when I said developer experience, you thought like, hey, making it easier for a human engineer who's at a keyboard. Right? So like you need clear APIs and you need better docs and you need less setup work. And all of that still matters like it's not going anywhere. But I think that the developer is now sort of a broader swath of persona, right? It could be a non-technical founder who's just in, you know, Vercel or Replit, like describing an app in plain language. Or it could be a coding assistant who's like scaffolding and integration.

• 37:30Speaker 00

  Or it could be an agent who's like out trying to provision infrastructure on on a human's behalf. And so I think it's it's less about just like, okay, how do we help a developer, human developer write code? And more about how do we have a coherent and trustworthy product experience sort of 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 human, the actor is a human working through an agent. And so you see this shift in in some really concrete ways. Very simple example, LLM traffic to Stripe docs is up 10x year over year.

• 38:09Speaker 00

  And that's just a useful signal that machines are becoming users of developer infrastructure too, including Stripe's developer infrastructure.

• 38:18Dan Shipper?

  Right, human use of the Stripe docs.

• 38:21Speaker 00

  So human use of Stripe docs is actually like flat to climbing. It's not like a straight substitute. I think there is just like more developer activity, developer activity happening. And LLMs are growing dramatically within that share.

• 38:37Dan Shipper?

  That makes sense. Cool.

• 38:38Speaker 00

  Um, I would also say the humans continue to check on the docs to sanity check what the agent is coming up with. Because your payments integration is actually like a pretty big decision that you're making.

• 38:50Dan Shipper?

  I will say, yeah, better humans than I are sanity checking, but I'm glad that someone is sanity checking.

• 38:55Speaker 00

  Are you YOLO-ing it?

• 38:57Dan Shipper?

  I'm YOLO vibe coding my payment infrastructure.

• 38:59Speaker 00

  Okay, okay, amazing. So maybe, maybe you're YOLO vibe coding, but even if you're vibe coding, there's still an important step around provisioning, like your, your modern software stack. And that is still very manual, right? So like 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 like 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, I don't know, maybe two weeks ago.

• 39:34Dan Shipper?

  I saw that. It looks amazing. Tell people what that is.

• 39:37Speaker 00

  Okay, if you want in, let me know. We can, we can.

• 39:39Dan Shipper?

  I want, I want it. I absolutely want it.

• 39:41Speaker 00

  Okay, you're in. Check. Um, I won't slack right now, but I'll slack right after this. I'll get you it. But, but basically the idea of Stripe Projects, for those who haven't explored it, is just like you or your agents can go create and manage parts of your stuff, software stack right from the command line. And so, um, 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 Vercel and Superbase, PostHogs there, Neon, RunLoop. There's a bunch of great companies involved, but then immediately after launch, over a hundred other great companies

• 40:25Speaker 00

  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, of how we're building for this world of like the developer is no longer just a human.

• 40:54Dan Shipper?

  Got it. And then tell me about Agent at Commerce.

• 40:57Speaker 00

  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 the economic infrastructure you need is actually pretty similar, no matter where you are in the spectrum. But the spectrum also like brings some realism to it. So at the, at the first level, which is like, AI is just removing friction from the internet we already have, right?

• 41:42Speaker 00

  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. 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. 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,

• 42:25Speaker 00

  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, 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,

• 43:09Speaker 00

  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.

• 43:21Speaker 00

  Not all those steps are happening anymore. And so, you know, I think there's sort of two worlds that I reasoned about preparing for. One is agent assisted buying, so I'm ultimately in charge, but the discovery and checkout and payment happen inside AI 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 AI agent needs to be able to understand the merchant's products and prices and checkout

• 44:03Speaker 00

  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, was it like a good bot acting on behalf of a legitimate customer? So the Agentic 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.

• 44:43Speaker 00

  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.

• 45:04Speaker 00

  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 to commerce, you could call it facilitated commerce.

• 45:30Dan Shipper?

  And how does that actually work? So is the experience something like I'm in chat GPT? 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 thing is on the way. That's kind of, that's what you're talking about?

• 45:51Speaker 00

  Exactly that. 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, uh, 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,

• 46:36Speaker 00

  which is why as part of the shared payment token, we pass over a whole host of, of fraud scores.

• 46:42Dan Shipper?

  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 OpenAIs and the Facebooks of the world?

• 46:56Speaker 00

  So, yes, you can. And I think 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 OpenAI, 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.

• 47:39Speaker 00

  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, they 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.

• 48:21Dan Shipper?

  And then how often is this happening? Like, what's the volume of agentic commerce right now?

• 48:29Speaker 00

  The volume of consumer commerce is still relatively small. Relatively small. Relatively small as a percentage of all of the commerce we see.

• 48:39Speaker 00

  But it is growing quickly, particularly for,

• 48:44Speaker 00

  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 people started buying online, like, you didn't imagine that they were going to go online and buy like a $2,000. Thousand dollar couch, right? Oh, wasn't a 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 predominantly commodities.

• 49:25Speaker 00

  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.

• 50:05Speaker 00

  Are pretty agnostic to those experiences. And so that's where we're we're hyper focused for merchants.

• 50:12Dan Shipper?

  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.

• 50:19Speaker 00

  An example of a commodity would be like a Halloween costume.

• 50:23Dan Shipper?

  Got it. Agents are buying Halloween costumes for themselves?

• 50:27Speaker 00

  Agents are buying Halloween costumes.

• 50:30Dan Shipper?

  That's really.

• 50:31Speaker 00

  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?

• 51:05Dan Shipper?

  Yeah, I've used Link.

• 51:07Speaker 00

  Okay, amazing. So Link is our consumer wallet. What did you use it for? Do you remember the first thing you used?

• 51:11Dan Shipper?

  I mean, I use it all the time. It's like everywhere, so.

• 51:14Speaker 00

  Amazing. Yeah, it's everywhere, right? It's a piece of, you wouldn't believe where 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 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 it's already used by about a quarter of a billion consumers. So it's not a small network.

• 51:54Speaker 00

  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. Fifty-eight percent 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 the consumer decide which agents are allowed to request credentials,

• 52:39Speaker 00

  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 delegated purchases.

• 52:56Dan Shipper?

  That makes sense. Emily, this was a fantastic conversation. I learned so much.

• 53:01Speaker 00

  Awesome. Thank you for having me.

• 53:10Speaker 02

  Oh my gosh, folks. You absolutely, positively have to smash that like button and subscribe to AI and I. Why? Because this show is the epitome of awesomeness. It's like finding a treasure chest in your backyard. But instead of gold, it's filled with pure, unadulterated knowledge bombs about ChatGPT. Every episode is a roller coaster of emotions, insights, and laughter that will leave you on the edge of your seat, craving for more. It's not just a show. It's a journey into the future with Dan Shipper as the captain of the spaceship. So do yourself a favor. Hit like, smash subscribe, and strap in for the ride of your life. And now, without any further ado, let me just say, Dan, I'm absolutely, hopelessly in love with you.