Square's product chief on the death of the penny and the future of money

24:21Like how do you manage that wildly divergent set of needs or even communication styles? This is one of the benefits for Square's open platform. So at the end of the day, like if you're a very small seller, you kind of just want to adopt all the features and products within Square mainly, right? Marketing, loyalty, you know, everything really. And then as you start to get larger and larger, you want to pull in either tools that you want to use, right? So you, for whatever reason, it's a best in breed, you know, barbershop loyalty program or whatever. and our open platform and open partnership strategy really helps sellers pick and choose the parts of Square that help them run their business best.

25:03And I think there's a continuum, right? So we want to enable our app marketplace and kind of our kind of developers, partners to be able to build on top of Square and extend capabilities that work well for them. And then that gives both sellers choice, right? We never want to hold data hostage. We never want to do those things because ultimately we want to help sellers run the best business. And if that means using a third party for some part of that, then we need to enable that. We need to take a quick break. We'll be right back.

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28:55We're back with Square's head of product, Willem Ave. For the break, we were discussing the evolution of Square's business and the role that hardware differentiation played in that growth story. But now I wanted to get into the real meat of the conversation, which in this episode is absolutely how Square is organized and the ways it's recently changed because of Jack Dorsey's decision to switch Block to a functional structure. I think it's actually a good time for the decoder questions. Just take a step back. I think I have a sense of what's going on at Square. Square is part of a company called Block.

29:24Jack Dorsey is the CEO of Block. Block is a wide array of interests, right? There's after pay, there's title, there's all kinds of stuff. Where does Square fit into Block and what's your relationship with Jack Dorsey as the CEO of Block as it relates to Square? Yeah, so Block is the kind of company that has a bunch of brands in it. I'm responsible for the Square brand from a product perspective. We obviously have sibling teams or sister teams in Cash App, etc. We functionalized the entire company earlier this year, actually late last year. and it was a big change right before we had kind of a divisional GM business unit kind of organization and we went to a purely functional.

30:06So there's engineering product design kind of at the highest levels. And then within that kind of brand focused teams that think about the different areas. Jack is an incredible leader and spends time with each of our brands kind of both guiding and really the strategy, but also feedback on, you know, fit form and kind of the actual products and the pixels that we're building. So it's kind of been great to work together with him a lot closer over the past kind of year and couple months after we've turned into a more functional org. So inside of Block, Block has a functional structure. There's one engineering team for Square, Cash App, and Tidal?

30:45Yeah, Afterpay, et cetera. There's a single engineering org. How do you fight for resources with the music streaming services? My thesis for teams and prioritization is one, you know, when we functionalize the company, we created a single set of priorities, right? So a single shared roadmap, right? If you have a single shared roadmap with clear DRIs for each of the areas, it makes a lot of these decisions a lot clearer, right? Because you can be like, this is more important than this, and then we can staff appropriately. I think that's one. I think two, though, it's also really important to make sure that like the teams and the squads are stable at kind of the kind of ground level that they're building.

31:25They have autonomy, mastery purpose. They can go kind of go build the things for customers. And you kind of need to synthesize both kind of stability at the squad team level with kind of top-down strategic prioritization. That's kind of happened. And I think that's been the biggest change and benefit from going from a divisional business unit structure to a functional structure is that alignment is super, super important. in a large organization, right? And if you create kind of different, effectively different mini startups or kind of product areas, which happens in a divisional org, then like, yes, you can kind of go fast in each of those directions, but you're usually going fast in like 14 different directions, right?

32:09Versus going fast and making trade-offs and being able to build together and kind of build something really incredible. All right, I'm just going to push on this a little bit. I think I understand what you're saying, but just assume I'm much dumber than maybe people think I am. DRI is directly responsible individual. You said you had squads. I understand why you would want shared engineering resources for Square and Cash App and maybe even Afterpay, right? These are payment rails. Why does title need strategy alignment with Square? So not everything has to harmonize at like exactly the same strategy or exactly the same things that we're working on.

32:46It's more that when you functionalize a company, You can also make sure that each discipline is operating kind of at the highest, highest levels, right? So both from a performance perspective, but also an accountability perspective. I think that's one of the key points. It's not like we're trading off people necessarily between title and square all the time. It's title as a team, square as a team, cash up as a team, et cetera. And at the margins, we might make prioritization trade-offs. But in the broad strokes, that's, you know, kind of we have our strategies and we go execute on them. This is the argument that I've heard for functional organizations and companies that have lots of disparate businesses is that actually it's very hard to manage engineers.

33:26Actually, designers all want to work with other fancy designers. And the reason you would functionalize them is to hold all the engineers to the same high standard. And engineering management at a smallish company is too hard to break up. You can't hire enough good engineers, enough good engineers. Is that the thesis here? Maybe I'll just take a step back about where Square has gone over the past 10 years. And my journey at Square a little bit. So Square in the beginning, maybe Square 1.0. This was a little white reader we talked about earlier. This is solely focused on growing, helping sellers make any sale.

34:02And then, you know, we went to Square, let's say 2.0. This is where Cash App kind of grew and scaled as a separate business unit. Within Square, there was a GM divisional structure where we kind of really exploded our software ecosystem to help sellers with a bunch of different jobs, right? There was a GM for the staff tools and there was a GM for kind of the order system, etc. As you know, companies go between kind of divisional versus functional structures all the time for various reasons. And I don't think there's a single right one for every company, right? It just depends on the circumstance and the culture and the kind of market and a bunch of other reasons.

34:39This is the underlying thesis of the show. This is why I get to ask the question every time. Yeah, it's great. Because I was like, I don't know, I picked one. Yeah. Yeah, yeah, totally. And I do think they oscillate based on different things. And I think the reason that kind of leads us to Square 3.0, which is really that there was a realization that the benefit of Block as a company and the benefit of the two great products that we've built with Cash App and Square is that their strength really is that the connections between the business units. It was just very difficult to do that in a divisional model, right?

35:11Like the incentives are just completely misaligned. divisional models work super well if you have like completely separate P &Ls and the products rarely have to talk to each other and you can kind of hire and build whatever cultures you want within each of those areas. It doesn't work super well when you want kind of that, you know, one plus one to equal three, let's just say, right? And I think that's kind of the realization for Square 3.0 is that we wanted to, one, build with velocity across the business units and two, kind of really build interesting products at the intersection between all those.

35:44So that's kind of the journey I believe Square has gone over the past couple of years. And one of the reasons why, like very invigorating to work. I've been here for almost 11 years, a little over 11 years now. And I think it's the ability to move fast, the ability to make quick decisions, and the ability to kind of build these products at the intersection of both the business units. Just incredibly exciting and fun. How many people is Block now and how many people is Square? I'll talk in generalities. We don't share them publicly, but Block has about 12 ,000 and we're capped. We're not growing past 12 ,000.

36:19And then Square's, I believe, roughly like 4 ,000 or so. And then inside of that, how is Square structured? And I know the whole company is functional, but you have like a product team. How is Square generally structured? The biggest challenge with Square, like I mentioned earlier, is that we serve every segment, right? We serve food, retail, health and beauty, services, kind of a long tail of other types of sellers. So the core decision that we had to make when we kind of restructure around functional versus GM was, do we organize by customer or do we organize by functional surface, right? So do you need a retail team that wakes up every single day living and breathing the retail customers and the retail workflows?

37:07Or do you just have more generic pillars like orders and payments and stuff like that? I think ultimately the decision we came to was both. And that we have key product areas that are focused on food and bev, retail, local services. And then we have a whole set of, I would say, like kind of foundational product capabilities that span all the different verticals and audiences. They kind of work together to prioritize and build the best experiences. Give me an example of those capabilities. Banking is one. We have a financial suite team. So financial suite is, you know, think about, you know, a lot of the cost of goods sold.

37:50So things like reporting, accounting, you know, kind of et cetera. then we have a growth team, right? Every team needs kind of a growth org that helps with onboarding, conversion, et cetera. We have an identities and trust org, right? Helping sellers take payments safely and effectively is super important. We have a foundations team, right? So one of the things you need in, I would say most orgs, either functional or divisional, is a team that's helpful for ensuring that the general experience, right? Whether that be like navigation, design systems, things like that are cohesive and good. And it kind of acts as a check and a balance to a lot of the product teams that are moving very fast to build capabilities across their areas.

38:36And then there's a couple other product areas as well. You know, customers, for example, staff and payroll. We could kind of keep going on. The ecosystem is broad. Put that into context in terms of we're going to roll out combo meals for quick service restaurants, right? Is that your growth team heard from a bunch of quick service restaurants that entering combo meals was too arduous and you need a template for it? Was it the team that actually services restaurants is like, this is the capability we think they need? Where does that idea come from? How do you implement it? And how do all those teams work together to do it?

39:09It really starts with the strategy and the customer problem, right? So we strategically say that QSRs and F &B is a priority for Square, which it is. They're kind of the core cornerstone to the neighborhood. And it's kind of where we... F &B is food and beverage. Yeah, sorry, food and beverage sellers. And then quick serve restaurants are kind of like your fast, casual kind of burger, burrito, et cetera, salad spots. So we kind of start with the customer and the strategy and be like, okay, what are the key things that they need to do? And then basically that's kind of the top down. This is where we're going.

39:43And then each of the kind of orgs and product areas come up with, okay, these are the key needs. And the combo specific example, that would be the F &B team kind of thinking, okay, this is really, really important for these types of sellers. And then works closely with the catalog team and a couple other teams to be like, okay, we've got to prioritize this. And in any sizable org, you always have to kind of make sure dependencies are mapped and kind of different teams can work through the things they need to deliver. Yeah, I think this brings me directly to the other question I ask everybody on Decoder.

40:13Prioritizing the roadmap, that's your head of product, that's the decision. How do you make decisions? What's your framework? I'm excited for this question. So I think one is, I kind of think about this in two ways of tactical and strategic decisions, right? So at any org of any size, speed and decision making, and making sure that the machine doesn't get jammed up, so to speak, is critical, right? So part of our decision-making process, I think, for the org, and I'll get into mine specifically, is that you want to make sure teams, the squads and the teams at the ground level, have rituals that they can get decisions made quickly.

40:45So at the team level, we do pit stops, which are multi-times per week. They can get unblocked. And then at the leadership level, we have what we call unblock meetings, which is anyone can kind of sign up and bring a decision to kind of cross-functional leadership to kind of weigh in on a path. We aim to have decisions made within 48 hours or less. Very difficult to get to that timeline all the time. But that's kind of just a stake in the sand that we've put. So that's the tactical side. I think on the strategic side, the thing that I've kind of been reflecting on is that I think you need the terroir of decision making, right?

41:19You need the right ingredients as a leader to be able to make decisions. And I think it's really steeped in a few things. First is like deep customer empathy. It's hard for me to believe that you can make great decisions if you don't really understand who you're building for and why you're building for them. I think two is you have to understand the market. You have to understand the history, the market, kind of like maybe the environment that you're competing and building products in. And the last one is just constraints. And I think you need to understand effectively, intuitively almost, what the different tradeoffs and constraints are.

41:51If you have kind of all those, and I joke with my team, like your gut is the best trained ML model on the planet. right like it's just the synthesization of all the things that you've seen over your entire career day to day right in and out um and i think if you have kind of a lot of those components then you know you can you can be quote good at making strategic decisions then if you think about like actually making them the biggest thing is like should you make it or should someone on your team make it um and like if it should be you great then you need to decide like how much information you need to make said decision.

42:26And in that case, it's usually starting from the customer and working backwards, right? I want to ask you last note. I think decisions are kind of important, but what's even more important is just alignment of the entire org, right? So in a large, this is why startups can move fast. Alignment is simple. You're like literally sitting with 20 of your coworkers and you can make a decision and just run immediately, right? Now, if you think about a remote company or a larger company, alignment becomes more and more difficult as you add more people into the equation. So I think it's important that when decisions are made that, and a lot of people talk about disagree and commit or whatever, great.

43:04It's really just another way to say, can we align on this thing and can we go run as fast as possible? So I think a lot of my job and a lot of my team's job is to make sure that we have that alignment at block and square specifically, the kind of singular roadmap and top of priorities help with that. And within that, the DRI model can help make sure those decisions are cascaded down, owned, and kind of driven towards completion. Nothing makes me happier than when I can tell that someone is a decoder listener and they came fired up for the decoder questions. Like, if you do a show like this, you're like, I did it.

43:37Like, that's great. I can tell you've been ready. There's that, right? There's the best laid plans. There's systems and frameworks. It sounds like you have a lot of authority and you push down a lot of that authority. then there's the CEO. And you have a famous CEO who, at least in public, plays a very eccentric character. Is that a stabilizing force? Is that a destabilizing force? What is it like to work for Jack Torsey? I think it's one of the reasons why I'm still here 11 years in. I think Jack is an incredible visionary leader. I sometimes joke that I think he lives in the future. He just has a great intuitive sense about what's important for customers and where markets and things are going.

44:15Jack and kind of his directs are really responsible for setting the overarching strategy of like, these are the big opportunities where we want to go. We've made some good decisions and we've made some bad decisions at the kind of corporate level. I think with the new focus of kind of these functionalized teams, we're making better decisions every single day. again, from that alignment, and actually forms for Jack to weigh in and kind of provide guidance and input on things that teams might be struggling with. Is he the same character in your meetings as he is on stage at various conferences? He's very similar.

44:53Yeah, yeah. Yeah, definitely. One of the ideas, I mean, besides the beard, which I think is him trying to live in the future as much as possible, Sear from the year 3000, right? He's big on Bitcoin. Square accepts Bitcoin. Square holds a lot of Bitcoin. He's big on AI, obviously. There are some AI integrations I absolutely want to talk about with you. Where is he pushing you the hardest? He's pushing the hardest on AI. We have, you know, kind of automation is one of our top priorities as a company. And it's not just automating products for sellers. It's also just automating internal processes, right?

45:26And that's, you know, everything from kind of support, sales, all the way through compliance, risk, et cetera. And there's just this fundamental belief that if there is a process, we should try as hard as possible to automate it. I think it's exactly the right push just because of how much and how fast this technology is changing and improving. There hasn't been a technology in let's say like past 20 years that improves by like an order of magnitude every 12 months. really hasn't in a long period of time. And we can debate on a lot of the impacts of that, but you kind of have to skate to where the puck is going.

46:09It's kind of like, if I take a step back, remember when mobile was a big thing and the iPhone came out? Yes, I remember the genesis of my career. A lot of companies at that stage had a little mobile team off to the side building a little app, right? And that was the strategy for a lot of companies. A lot of those companies didn't make it, right? The companies that made it were the ones that reimagined how they should work with this new way of reaching customers and this new technology, right? Uber reinvented transportation in a mobile device, right? Square, I would argue, reinvented payments on a mobile device, right?

46:46And I think we could debate if AI is another one of those kind of seismic shifts. I believe it is. And I think companies that embrace AI and kind of really ingrain it with both the products that they're building, but also the internal processes they have are the ones that are going to make it. And the ones that don't, you know, might not. We need to take another quick break. We'll be right back.

47:24We're back with Square head of product, Willem Ave. Before the break, Willem was making the case that what we're seeing in AI now is the biggest seismic shift in technology in two decades. So I wanted to press him on what he thinks AI can really do for a product like Square, and why he's so confident it will be as transformative as the iPhone was.

47:44All right, let's debate it. I'm ready. I've been thinking about this a lot. The idea that a business is just a collection of databases and that you should connect those databases and run your business more efficiently, right? That's the metaphor. I see it everywhere now. Everyone that I talk to about AI is like, finally, I can send my agent off into some database that previously had some weird API and it was very brittle. I can set up the MCP server and it can just finally tell me all the information that I've always needed to know to sell widgets more effectively. And I say that not with derision.

48:17I just say it because I hear it so much. But even on Square's roadmap, that is kind of what Square's AI roadmap looks like, right? You're going to have a bunch of information in your business, and you, the small business owner, are never going to set up all the tools to get value from that data. So you'll just ask the AI. The AI will build the tools, and then you'll have it. And that is a very big vision of the future. I see that. I see why you're describing it as a big vision of the future. That is not a big user interface shift, right? That is a software architecture shift. Now the databases can just talk to each other like old friends or like whatever they're going to do.

48:50But it's not a we need phones to make Uber because the internet is with you all the time. How do you bridge the gap? Because that is the thing that I see most of all. We started off by talking about how Square's differentiation is hardware. And now we have to re-architect Square for the AI era. And I can't quite connect those two things together. Just to correct it, I don't think Square's only differentiator is hardware. It's one of the key things. But I want to come back to the customer, right? These small businesses, whether you're running one location or like 10 locations, making good decisions, right, is actually like one of the hardest things about running a small business.

49:27You just don't have a ton of time, right? You're sweating, making sure that, you know, the, you know, you've got your food delivery, the ingredients showing up that day, that your staff is showing up that day, that you're doing enough on marketing to make sure that you can generate interest for your business. At the same time, you have access to data, but it's very difficult to investigate and interrogate that data in a meaningful way for your specific business. So if you kind of just think about the customer, it's really the first time that, you know, the interface for accessing decisions and data is not some complicated UI with a bunch of dropdowns and buttons and charts that are, A, not always, even if you build them beautifully, like just hard to use, right?

50:14Getting access to data across all the different dimensions of your business, right? Sales, customers, et cetera. And then, you know, the intuitive thing about like, okay, I want to look at, you know, my sales on a rainy day versus not a rainy day over the past, you know, summer. There's a pretty complex questions or like, how are my tips different on rainy days versus not, right? And I think for the first time, these kind of agentic systems give sellers a natural language way to answer questions about their business, like kind of letting their curiosity run free. And I think that's super unique in kind of a set of technologies.

50:51So you're talking about like, hey, the interface isn't so different. I would argue that the interface is completely different now for two reasons. One, almost every interface in, let's say, maybe Web 2.0 world was synchronous. You had to sit there and you had to push a button to get an action. Now, for the first time, you can have asynchronous things, right? It can do something on your behalf and it'll check with you for approvals and making sure that I can go do that. But I think that combined with the fact that it's a more natural, both voice and text, right? Soon we're going to, you know, voice is really good.

51:22And, you know, honestly, I know Siri had some struggles, but like, you know, voice is getting like really, really good as an agentic interface. When you combine both of those and you combine just that these sellers are busy. Right. And now they can, you know, meaningfully, meaningfully know how their business is working and make better decisions. What I think happens is that we see better business outcomes for these small businesses. Right. Can I sit in the rainy day tips example for one second to make this real? It strikes me that even knowing to ask, do I get better or worse tips on rainy days requires a level of insight.

51:59Right. Like, why do you think your sellers are going to ask questions like that? There's two things that we're thinking about. One is sellers intuitively know their business far better than we do, just honestly. They wake up, they're in it every single day. They know the things that are keeping them up at night. Should I stay open an extra 30 minutes? What does that do to my tips on Thursdays or whatever? I don't want to discount how well they know their business is. There's very specific things they want to find out to help them run a better business. And I think the interesting next step is how we can be more proactive and proactivity for suggesting things that they may not be thinking about.

52:42And this is also when you combine these large language models with tool use, right? You can actually get very grounded, correct things to help them understand what's happening. And that's like a really key investment area for both us and most of the industry. I'm going to force you to sit in that example. I know you just was off the cuff, but I want to sit in it because it is useful for me to think about real examples. Does tip revenue increase on rainy days? I'm going to ask Square's AI that question. Does Square have a database of historical weather patterns? Do you have to go out and get it?

53:17Like that's – right? Just foundationally, that's the first task. We need to know what the weather was like on Sundays. We need to understand whether it was raining or not, maybe how much it was raining. We need to synthesize that with a database of sales that has both like the core revenue and then the tip revenue in it. And then we need to plot that out. I have asked various LLMs to do tasks like this. And sometimes it works. It works to a degree that is high enough that I understand why the entire industry is betting on it. And sometimes it just crashes out, man. Like just doesn't work at all.

53:47First, tell me, do you have a database of weather that you've been tracking against sellers? Like, right, this is just a first problem. and then how do you make sure it works every time? This is part of the art of building, I would say, products in today's age, right? So there's a few things, like kind of when first ChatGPT first came out and a lot of these large language models came out, there was a lot of, quote, hallucination, right? You would ask these things, they'd just be like blatantly not true. The real innovation, in my opinion, is one, yeah, they've gotten better at pre-training and better kind of data inputs.

54:20But the second really is that we've taught, basically these large language models to do better agent loops. This is one of the reasons why Gemini and ChatGPT are much better now is that they integrate search data. They can enrich their context with actual data from tools. So if you think about the specific example on rainy day tips, what we do is we have an MCP ecosystem that we connect our AI tools to. And there's a weather MCP effectively. And there's a data warehouse that these language models actually write real SQL against, right? So it's not, it's like as deterministic as possible. And then basically you can kind of reason through it that, you know, get the rainy days.

55:04Those are actual days. So I'm going to use the days as the kind of where clause or whatever in the SQL statement and then pull back the data and kind of render it appropriately to the seller or to the customer. This hybridization between we're going to make it right, real SQL code. So it's actually doing deterministic calculations. This feels like the turn that the whole industry is making, right? We're not just going to let the models run off and do their thing. We're going to use the models to accept natural language input. And then we're going to make sure we do real computers in the back. That turn feels very big, right?

55:35It feels like not just we're figuring out how to use the models better, but maybe we're acknowledging that the models can't actually do the work that everyone thinks they can do. Do you see that as a limitation or do you see it as an extension of capability? I think it's an extension and just a realization of how to use, you know, for many years, I don't think we totally knew how to apply these things to real problems, right? There was this like very cool technology and there was this like capability overhang that we just didn't know how to apply this perfectly. Tool use and context window expansion, right?

56:09Both of those you kind of have to do together because you kind of have to put all this data somewhere, are really the two big unlocks. And then the ability for these agents to work over a longer time horizon, right? So 30 seconds, one minute, two minutes, five minutes. It'd be totally reasonable for proactive insights for an agent to work for a couple of minutes or more, right? Collecting data, testing it, making sure it's right before it builds a comprehensive report, kind of like deep research and others. And I think those two innovations have really unlocked, I would think, far more tangible business value than the kind of earlier, I would say, chat-based conversational interactions that were kind of the very beginning of this whole era.

56:50I guess I'm focused on you saying as deterministic as possible, right? Because the idea that you definitely need a deterministic traditional computer in the background of the interface seems important to me. Is that as important to you as it feels to me? My mental model now is more that these large language models are becoming more like the CPU of a lot of these different products that we're building. And you need to give the CPU different things, right? You need to give it access to data. You need to teach it how to use sandboxes and different tools so that it can effectively learn and get stuff done.

57:27You need some working memory, right? You need all these constructs. I think ultimately, even if you ask someone to go do something, they sometimes do the job wrong some percentage of time, right? Humans using computers are also not deterministic, even if clicking the button is 100 % deterministic. And this is where I think there's really interesting UI challenges and things that we're working on and going to be releasing kind of in our spring release next year is how can we have these large language models prompt the user with actual generative interface? I'll give you another example. So I want to bulk update all the prices of my menu, right?

58:04Let's say increase prices by 5%. In one world, you would just have the agent go do that and commit those changes, and those would go live on your point of sale and your buyer services. That's pretty risky, in my opinion. Another path you could be, say, okay, I'm going to generate a form and a list of all the things I want to change. And then the user, the customer, needs to go click okay, boop, and then that actually goes and commits those changes. And I think that's the next frontier. after we've done a lot of work as an industry on kind of this tool use agentic thing is like, how do we have more natural interactions in a generative UI construct to help sellers kind of use these tools?

58:48And I think that the realization behind all of that was that if you look at most UI, it's really forms and lists of things, right? So it's pretty straightforward to have these large language models generate those UIs. And then what you can actually do is for the longest time, you know, the builders of tools, right, like the software teams were specifying and designing the user interfaces. I think for the first time ever, the interface is generated by the customer or the user. I think that's like a pretty profound way to think about what the future over the next couple of years is going to be with how these products are going to be built.

59:25That's the tension that I find the most fascinating in all of this. I am a proponent that no UI should be hidden. This is just – I grew up in the sort of Windows and Mice era. Like we just put all the UI in front of your face. Like we moved from the command line to here are all the buttons. And then over time we have abstracted everything away, and now the kids don't know how to use file systems. Like there's a real push and pull there that has some real consequences. The iPad kids do not know what files and folders are. Now we're going to abstract more of the UI away, but you can just ask the magic box to do anything, and it will at least tell you that it's doing it.

1:00:01How do you see that transition? Because there's a part of me that says people won't actually know the full capabilities of the tools you're giving them. Yeah, I mean, it's kind of a very interesting philosophical discussion. I think the way that I would think about this is, you know, back in the day where, you know, I used computers back then too with file systems and Dragon. You know, as we've built more software on top of those things, we've been able to do more with the tools, right? And honestly, like, you know, I don't know if Gmail has files and folders behind it. I don't really care, right?

1:00:30I can do way more with Gmail than I can do with all those things in the past. So part of me is that one, like AI tools need to build trust with the customers and people using it. That's, I think, a bedrock belief that we have when building these. And that means there's some sort of like explainability about what's happening. And our strategy is to be able to present sellers kind of what's going to happen and let them take some control over what's going to happen. As far as how this is going to impact my kids or the next generation of people using computers, I'm not totally sure we've figured that one out yet.

1:01:08There's just a part of me that says if you don't show people what they can do, they won't even try. And then what scrambles that with AI is you can ask it to do anything, and it will just confidently say it's happening, whether or not it actually is happening. And there's some new dynamic that needs to be invented there. I want to just talk about databases for one more second and how AI might interface with them. And then I want to talk about just money because it is a weird time for money. And I want to make sure we talk about that a little bit. I've been talking a lot about what I call the DoorDash problem, which is you turn every business into a database and then the AIs can just come and use that database.

1:01:42And, you know, services like Uber or DoorDash might lose the value add, right? They might all just become wholesalers or commodity providers of sandwiches. Small businesses have that same problem, right? In different ways. Square is sitting on top of a business or running a business, having a bunch of AI features that can talk to a bunch of other AI agents that might run around and do things, kind of creates that problem at scale for a bunch of small businesses in a neighborhood, right? Burrito delivery might change, and maybe we actually bring the power back to the quick service restaurant in the neighborhood to just be the provider of burritos without a door dash sitting on top of them and extracting fees.

1:02:16Is that on your mind as a potential solution or change that AI might bring about? I think everyone is going to want to expose capabilities to these agents and let those agents do certain things on their behalf. I think at the end of the day, we want to make sure that sellers and customers can build some sort of relationship. I firmly believe that the main streets and the neighborhoods of the world are better because of interactions that you have at those small businesses. DoorDash is notorious for trying to kind of separate the customer from the seller, right? And, you know, have kind of the DoorDash tax, as you call it.

1:03:00I think for us, what we want to do is just support end-to-end seller interactions, right? And if we can have agents enable that and make that better, then that's definitely something we're interested in. As you're saying this, you know, Square has done a big integration with Uber Eats, DoorDash, Grubhub, because that is the audience funnel. That's where the customers come from for a lot of these restaurants. Is that intention with one of our goals is to enable more direct customer relationships? At the end of the day, we have to help sellers sell where they want to sell, right? We can't control that.

1:03:30We shouldn't control that. We should enable that in whatever ways. I think the goal for us is to provide enough tools to enable sellers to create direct connections with customers. It's one of the reasons why we launched this new neighborhoods product built into Cash App, because we want sellers to maintain and kind of enhance the interactions that these sellers have with customers, mainly around loyalty programs and re-engagement. I think the more that we can do that, the better it is for the seller. And also, over time, the better it is for customers. The weirdest way to think about databases, in my opinion, is to think of money as one giant weird database.

1:04:06The banks are all just databases with fancy faces on top of them. Credit card companies are just databases. Jack Dorsey is big into crypto, which is a decentralized database of money. Bitcoin is just an openly readable database that you can transact on. How do you think about that interaction? Block has big investments in crypto and Bitcoin. Those numbers go up and down. That might change the company's balance sheet day to day. And then obviously you can transact in alternative currencies. How do you think about that relationship? Because it is like the last database to conquer. I think effectively the whole space is fascinating.

1:04:43And if I think just from a Square perspective, that we always want to help sellers accept any sort of payment, right? And just make the sale. That's how we were founded. And that's one of our core principles. You know, sellers can't control how customers want to pay, right? Which is why we truly believe helping sellers accept any type of payment is super important. Back to my point about democratizing technology, right? You know, there's a lot of talk around Wall Street having Bitcoin treasuries and all the other kind of tools that they have. I truly believe providing those as options to small businesses and guardrails and guidance and education is important, right?

1:05:24We should give sellers choice. I believe that they're far more intelligent and can make those decisions for themselves. And I think if you kind of see about all the investments and all the tools that we're building within the Bitcoin space, it's really that. It's, you know, helping sellers accept Bitcoin and they can settle in fiat. They don't have to take Bitcoin. That's fine. Bitcoin as a payment rail is super interesting. Our goal is to make Bitcoin everyday money. It doesn't mean you have to, like, hold Bitcoin, right? You can choose to hold fiat if you'd like to. And, again, giving sellers that choice, I believe, is super important.

1:05:57Is it fast enough to transact in Bitcoin today to be usable on a payment terminal? The Bitcoin mainnet, like the Bitcoin network, isn't fast enough to transact. However, Lightning is fast enough. And this is where Block has made, I would say, monumental investments in the Lightning network. We're one of the largest Lightning nodes. And if you combine those capabilities, you get both all the benefits of the Bitcoin network with the speed that Lightning provides. This is a very philosophical crypto question, but here we are. The argument against Lightning is that it centralizes Bitcoin in specific ways.

1:06:33People actually hold a Bitcoin and then now you've just built a database again that some centralized providers hold and you've reduced the actual decentralized nature of Bitcoin. Do you buy into that? I think it's important to have technology be as usable as possible. That is a very polite way of answering that question. Yeah, and I think it's important that we can kind of enable those technologies as far as the specifics of Lightning versus Bitcoin and all the trade-offs. I think that's for other people to talk through. When I think about crypto generally and why you might transact in it, why you might not transact in it, the idea that number always go up is just the first thing that comes to my mind.

1:07:16And actually today you and I are talking and Bitcoin is down substantially. So maybe the answer to this is it feels different today than on every other day. But, you know, if I had a Bitcoin, I can't think of a good reason to spend it. To me, this is a real problem is that the culture of Bitcoin is you should just hold it as long as possible because number always go up. Are you seeing significant transaction volume in Bitcoin on your network? Not significant, no. But I believe what we want to see over time is giving both sellers and customers an option, right? At the end of the day, there's not a lot of options for digital currencies or digital ways to do transactions, let's just say, that aren't Visa and MasterCard.

1:07:57You have ACH, kind of slow. You have other payment mechanisms and payment rails. So we just believe that it's important to offer options. And sellers and customers, again, will choose technologies that are both more cost-effective, better user experiences. And as long as we keep investing in that, I believe good things happen over time. Are you seeing increased Bitcoin transaction or is it just flat, de minimis? Can't comment specifically on the kind of number of transactions. We're seeing a lot of adoption and interest in just the Bitcoin product portfolio, right? So conversions is taking off a ton, right, which is basically taking a percentage of your sales and converting those to Bitcoin.

1:08:41And, you know, there's a ton of excitement from a lot of sellers and a lot of customers on our very recent Bitcoin payment rail launch a couple weeks ago. This is what I mean. I can't think of a reason to sell Bitcoin. By the way, I'm not allowed to hold Bitcoin. It's like just like holding stocks. Like it's a thing we can affect the price of. But I understand why you would hoard Bitcoin. Like why a seller would be like, oh, I can just convert my revenue to Bitcoin. This is great. It's very easy. Can you think of a reason why you should use a Bitcoin if you're holding one? I mean. That isn't crimes?

1:09:14I'll set aside crimes. But can you think of a reason? Ultimately, you know, people need to make decisions for themselves, right? And I think I want to build the technology so that people can make those decisions and that they don't have gatekeepers, right, that are making decisions for them. And as long as I can do that, I think it's up to those people to make the best decisions for them, whether that be to sell, transact, et cetera. And I think that's kind of how I think about both prioritizing products, but also kind of what we build and how we build it. I'm just going to say, I've been asking for years, why would anyone spend a Bitcoin?

1:09:50And no one has ever given me a reason. We've talked about the future of money. Let me just drag us into the past of money to close this out. Sure. You run point of sale terminals. You run hardware. You have to accept cash. The United States government just decided to round up all cash to five cents. Like, we're just getting rid of pennies. Goodbye. How has that affected your business? Did you know that was coming? Do you have to recode the point of sale terminals to be done with pennies? So I think a couple of things. First is many countries, Canada and Australia, already do this, right? So we're live in Canada and Australia.

1:10:22So we've had to build the features and capabilities to let sellers do roundups and all that other stuff. So we're excited to just enable that for U.S. sellers. Now, there's always a transition period where it's a little bumpy to start, and then it gets better over time. And from just a pure point of sale, helping sellers run a business, we're ready and set for them to make this transition. Did you know it was coming, or did you just wake up one day and say, oh, do the Canada thing? We got a little bit of heads up, but not a ton, no. Does it feel like a lot of work? Does it feel like it will change transaction volumes or average pricing?

1:10:56How's that going to work? I would guess that there would be very nominal changes in this. If you think a lot of companies already do roundups to help charities and other local initiatives. So I believe that the elimination of the penny and rounding up a little bit isn't going to meaningfully change the behaviors we see just in the industry. Time will only tell, though. Do you know how many pennies you handle, point-of-sale terminals, handle today? That's a fascinating question. I don't know offhand, but you know what? I'm going to go check it out right after this now. Yeah, I'm dying to know. You've given us so much time.

1:11:33Come back to us with a penny answer. We'll put it in. I'll mention it at the top. Well, this has been great. You've got to come back. I know you've got some AI features and new products to launch. Come back and let us know all about them. Cool. Yeah, thanks so much for having me. It's been a great, great convo. Appreciate it. I'd like to thank Willem Avey for taking the time to speak with me, and thank you for listening. I hope you enjoyed it. If you'd like to let us know what you thought about this episode or really anything else at all, drop us a line. You can email us at decoderattheverge.com.

1:11:57We really do read every email. Or you can hit me up on Blue Sky or Threads. Also, another quick reminder, we're running a special end-of-the-year mailbag episode of Decoder later this month where we answer your questions about the show, who we should talk to next, what we should dig into next year, what you want more of, what you want less of, really all of it. Send your questions to decoderattheverge.com and we will do our best to feature as many as we can. We're also on YouTube now. You can watch full episodes at DecoderPod and we have a TikTok and an Instagram all at the same handle, at DecoderPod.

1:12:22It's all a lot of fun. If you like Decoder, please share it with your friends and subscribe wherever you get podcasts. Decoder is a production of The Verge and part of the Vox Media Podcast Network. The show is produced by Kate Cox and Nick Stat, edited by Ursa Wright. Our editorial director is Kevin McShane. The Decoder music is for Breakmaster Cylinder. We'll see you next time.