The Story
Evan Smith comes back to Decoder sounding less like a founder with a thesis and more like someone whose thesis has been stress-tested by reality. A year and a half ago, he and Nilay were talking about globalization getting harder to manage. Now Smith says that shift is no longer theoretical. Trade is more fractured, rules are changing constantly, and Altana's pitch - software that maps and manages global supply chains - has moved from a smart bet to a practical tool for governments, logistics companies, and major importers trying to keep up.
That leads into the first tension running through the conversation. Nilay pushes on the human cost behind phrases like "an index bet on dislocation." Smith doesn't dodge it. He argues that trade is tied to ordinary life at the most basic level: food, fuel, medicine, prices. His case for Altana is that globalization is not going away, but the old version is. What replaces it will need more verification, more enforcement, and a lot more coordination.
From there the discussion splits in two directions at once. One is about AI and software work itself. Smith says Altana is just under 300 people, only modestly larger than last time, partly because AI is changing how the company builds products. Product managers, designers, and engineers are starting to blur together. Domain experts in customs, procurement, and logistics are getting pulled much closer to product decisions. Smith sounds excited by the speed gains, but also pretty candid about the tradeoff: it is easy to prototype with AI, much harder to ship reliable software for customers who expect near-perfect uptime and are running high-stakes operations.
The other direction is the world Altana is trying to model. Smith says the tariffs meant to reduce dependence on China have mostly rerouted Chinese goods through countries like Vietnam, Mexico, Malaysia, and Canada rather than moving production cleanly into the United States. He says the data shows imports shifting, but not true separation. Manufacturing output in the US may be recovering after an initial hit, yet manufacturing jobs, by his account, are still declining, which points to automation more than some factory-job revival.
That broader point carries into defense and geopolitics. Smith argues that chokepoints - rare earths, shipping lanes, energy routes like the Strait of Hormuz - are now central instruments of power. Economic pressure can turn into military pressure fast. Altana's role, as he sees it, is to help governments and companies identify these weak points before they blow up: trace goods, model dependencies, simulate shocks, and build alternatives.
By the end, Smith brings it back to the architecture of his own company. Altana works by federating data instead of demanding everyone dump sensitive information into one common pool. Governments and companies keep control of their own data, while Altana builds a shared supply-chain graph and improves its models from the patterns it learns. His closing argument is basically that better visibility creates more economic security, and that more economic security lowers the odds that states reach for open conflict.
Main Themes
The episode keeps circling one big idea: globalization did not end, but trust in the old way it worked did. What used to be a mostly invisible system of moving goods is now crowded with tariffs, customs checks, export controls, national-security rules, and outright geopolitical rivalry. Smith's whole argument is that software has become part of the machinery that makes trade possible under those conditions.
AI sits right in the middle of that shift. On one level, it is helping automate the bureaucracy: customs declarations, standard operating procedures, document handling, classification. Nilay is skeptical of the absurdity of using AI to fill out forms created by political decisions that made trade more cumbersome in the first place. Smith's answer is that the forms are not going away, and agent-based systems are getting good enough to handle the mess. On another level, AI is changing the internal shape of software companies, shrinking some boundaries between roles while raising fresh questions about testing, reliability, and cost.
The policy thread is sharper than the usual trade talk. Smith's read is that tariffs alone have not done what their advocates claimed. They changed routing, raised costs, and pushed work into more complicated channels. When industrial policy has had visible effects, he points more to directed demand, bans, subsidies, and procurement - especially in areas like drones and defense supply chains.
Under all of it is a darker point about the future. Supply chains are no longer just commercial systems. They are instruments of state power. Whoever controls the bottlenecks can apply pressure without firing a shot, at least at first. Smith is betting that if governments and companies can see those networks clearly enough, they can build enough redundancy to make the whole system less fragile and a little less likely to tip into war.
Full Transcript
Support for this show comes from Comcast Business. Modern enterprise is a lot of moving parts. Comcast Business helps you orchestrate it all with SD-WAN working at scale to keep 150 hospital locations connected and working as one, plus SASE and zero-trust security protecting financial data across a bank's 2,000 branches, and AI-powered networking that optimizes traffic across five continents. No one does business like Comcast Business. Hello, welcome to Decoder. I'm Eli Patel, editor-in-chief at The Verge, and Decoder is my show about big ideas and other problems. Today I'm talking with Evan Smith, the co-founder and CEO of Altana, a company that develops software tools to manage big, messy supply chain networks around the world. We last had Evan on in early 2025 to talk about how Trump's first few waves of tariffs were starting to affect global trade and what patterns Altana was seeing in all that macro-level data about shipping and trade. It was a very illuminating and occasionally alarming chat. Evan and I got into the existential weeds of international relations and economics almost immediately. It's among my favorite episodes of Decoder, and it's a deep introduction into what Altana does if you're interested. We'll drop a link in the show notes, but now it's a year and a half later, and global trade is somehow even more chaotic than it was the last time Evan and I talked. And, as you'll hear, we jumped right back into the weeds of international relations yet again. On top of that, developments in agentic AI have changed the very nature of what it means to run a software company. It's changed what Altana can do. But like every other software company, it's also changed how Altana can do it, how it builds software. You'll hear Evan describe how AI is changing how the company builds software for a very demanding set of clients, manages billions in international trade, and how AI is also causing internal debates about how that software should be built and tested. And, of course, the things Altana needs to do are also changing more or less daily. Trade policy is changing rapidly around the world, but likely nowhere faster than here in the United States. Between the Trump administration's whack-a-mole tariff policies and the war in Iran, it is pretty hard to keep up with the current rules. That's where software like Altana comes in, and all that data pouring in from around the world gives Evan a very high-level view of what's actually happening. All those tariffs, for example, were supposed to bring manufacturing jobs back to the United States. So I asked Evan directly, did it happen? Spoiler alert, you will not be surprised to hear him say no. Although some of the ways companies and businesses have gotten around those rules are pretty surprising. And while it's clear that the world still relies on global supply chains, the pressure being placed on economic choke points, like the Strait of Hormuz, is going to get higher than ever. There's a lot going on in this episode, as you will quickly be able to tell. Evan and I really enjoy talking to each other. Okay, Altana CEO Evan Smith. Here we go. Evan Smith, you're the co-founder and CEO of Altana. Welcome back to Decoder. Yeah, it's good to be here again. Thanks for having me. Yeah, I was looking over our last interview from about a year and a half ago, and boy, we got straight into the existential weeds of what it means to run the global economy and what was changing. The thing that strikes me, just about the past year and a half, the last time you were on the show, I'm going to stop with theoretical, right? You founded Altana on the idea that globalization as we knew it, what you call globalization 1.0, was going to come to an end, and it was going to get more complicated, and the world needed software to solve it. The rubber has hit the road. It has gotten more complicated. It's getting more complicated by the day. Even as we speak this week, it is getting more complicated. And it feels like it has gone from being a bet to being something very, very practical now, even in the last year and a half. Is that how you see it? Completely. Yeah, one of our investors described Altana as an index bet on global dislocation. That's a lot. Can I just ask you a very, maybe philosophical, emotional question about that? I get a lot of feedback from our audience. It's like, you have CEOs on the show, and they talk about making bets in this way, and on the ground, it's chaos, right? So like an index bet on dislocation, I get it, right? On CNBC, that sounds great. I understand exactly how that plays to that audience. How do you feel about that approach to the world, especially as a software company that kind of just makes a map for people, how it plays out for regular people? Because I think regular people right now are, they're really struggling, and they're really confused. They're very anxious. Well, trade touches virtually every part of our lives, or most of them. And our mission to fix globalization, right? So what we're saying is, we're not retreating from globalization. We're leaning into it, but we believe that globalization needs to be fixed. It needs to be more trusted, more secure, more fair. And that's a recognition that trade will, and it should, continue across borders. And so the kind of, the animating ethos in the company, and, you know, when we work across our customers who, in most respects, are, you know, on the front lines of all this stuff, right? We work with eight of the ten biggest logistics providers. We work with the government agencies that are having to scramble to enforce these laws. And then we work with importers and their supply chains to comply with them. And the stakes are huge. It's like, do medical devices get to the hospital, right? What's the price of fuel and food? So, you know, I guess I couldn't agree with you more that the dislocation ultimately has the most profound consequences for everyday people. But that's the point, right? Like, trade is the lifeblood of growth. This is how we feed ourselves, sustain ourselves, protect ourselves. And so how do you have both at the same time? How do you have more enforcement, more fracturing as the geopolitics play out, and yet have more trade and more growth and more economic security? And I think Altana is the answer to that question. The reason I'm asking that is I worry that maybe there's too many layers of abstraction. Not with you, with everyone, right? Building solutions for our current world where you just acquired a company called SurveyAI, right? I think today, like literally as we're speaking, the press release is dated today. I've had a smile on my face all day, but yeah, it just hit the wire. You know, they make an AI platform to solve customs brokerage, which in an earlier version of globalization was not a problem, right? The trade just was flowing and products were moving across borders. And now all the walls are up and everyone has to do more paperwork. And here's Altana being like, we see an opportunity. We're buying an AI platform that literally fills out paperwork at borders. And I look at that and I'm like, well, that was very smart, but that's the thing that feels like the right answer for one problem. It also, to me, feels like the dumbest problem. Like we're now having robots fill out forms, presumably for other robots to read, just to get back to the kind of trade we had before. And I get it. Like a couple layers of abstraction away, this is the smartest bet. And then down on the ground, I'm like, so it's an AI that fills out forms that we didn't have to fill out before. And the only rational response to that is another AI system on the other side reading the forms. What are we doing here? We do have, just to be cheeky with you for a moment, we do have our own AI agents and our AI systems on one side of the border talking to our own AI systems and agents on the other side of the border. So, look, I do think, you know, it's not just kind of founder bullshit to say that the future is some version of agentic orchestration of the trade network, right? Like that's a sensible statement whether or not there's policy volatility out there or not. And the technological, you know, revolution that enables that is moving at pace. So, like we're surfing that wave. We're applying these technologies. We're in some cases inventing a few. But really, you know, in order to have global commerce, in order to have, you know, strawberries in the wintertime in the United States, you have to somehow solve this border complexity problem. And, you know, your notion of did we just shoot ourselves in the foot is, it's a fair question. And you and I talked about this on the last one, but I think no matter what, the United States, Europe, the West broadly, and even China in its own way, is having to reckon with the new geopolitical calculus and the new economic security calculus. And so in a world of disequilibrium, which we're in, right, you have a rising power and in a world of disequilibrium and in a world where, you know, you don't have a hyperpower that can police the entire world and all the maritime shipping lanes and, you know, and all the rest of it, then there is going to be a whole lot more weight placed on economic security, on national security. You're seeing the weaponization of choke points through the supply chain and global logistics network. So it's not theoretical. Like it's happening. Like we're all reading the same news. And so, you know, back to the border and back to customs, it's like the question again is how collaboration layer on top of that with AI helping all the parties, that's connecting government agencies, like the U.S. Customs and Border Protection agency, with now eight of the world's 10 biggest logistics providers who actually move all these goods around the world. And then Fortune 1000 companies and their suppliers. So all of these parties are, you know, think about it as kind of hooking into a shared view of the world at Google Maps for the supply chain and then transacting with each other to manage trade. And increasingly, and this is where the, you know, the Servo acquisition we were just speaking to comes in. Increasingly, agents are working alongside humans in those interactions within an organization and between organizations. I want to dive into that specifically because I'm really curious about how the data works and I know you have a very unique data model for how people work with Autonic and you have an entire thesis there. But I kind of want to do the decoder questions as a bit of a lightning round just so we can get there quickly. Last time we spoke, you had about 240 people. I'm assuming you're growing. How big is Autonic now and how are you structured? Well, we're actually, I think, benefiting from some of the AI that we're purveying, right? So the company is just under 300 people. We might've just broken 300 with this acquisition. How are we structured? We are trying to run more of the company through an extended leadership team these days. So we're covering an enormous amount of ground. We have, I think, nine governments we work with around the world. We have three product lines that serve different government users. We have this logistics vertical. We work with enterprises the world over and their suppliers. So it's incredibly broad and it's incredibly complex. And the point of saying all that is that within a 300 person company, the communication and coordination challenges are just massive. And one of the things I'm trying to solve is how do we get more of the leaders in the company seeing the whole playing field and having the same debates and synthesizing, you know, the information at the level of the whole company and not just their function? So it's messy and there's, you know, people complain about, oh, we had this two hour meeting. It was very expensive because we weren't talking about my thing, but it's like. My instinct is that it's the least bad way to run the company these days as we gain scale and we kind of grow into the ambition of the business where we're covering so much ground. That I think connects directly to my other decoder question. The last time we on the show, you actually told me your process for making decisions was rapidly evolving. And you said you had moved from a consensus model in areas where you had a lot of expertise to being really decisive, particularly on product and product management, that you were going to be more opinionated there and faster there and leave the other stuff behind. That's kind of what you're describing at scale now. Is that still the framework? Has it evolved more? How are you making decisions? Well, that's definitely stayed true. And then what's happened since since then, I guess this was March of last year. We have we have injected folks into the company that have really, really, really deep domain expertise in some of the areas we're working in. You know, trade, customs compliance, logistics, procurement. And with the advent of agentic design and agentic coding, one of the things we're really leaning into is, OK, how do we get to the right product judgments faster, right? So whereas it took kind of founder level conviction and synthesis to make some of these big bets before. That's still true. But what's been really cool over the last six months is, as we've brought in these like really deep domain experts, is we can take kind of a traditional product design, product management, discovery function, pair it with deep domain expertise, including with customers, but but get to the right product judgments so much faster. And then, you know, the execution of that workflow or, you know, the kind of build out of the of the the modeling steps is also much faster in this kind of new way of coding and developing. We have to move fast because the world's changing really fast. So that's going to that is true and it's probably going to stay true. And what's different from a year and a half ago is you now have this agentic product development lifecycle that just gives you so much more velocity and the ability to get to the right place faster. Talk about that a little bit more. I have talked to, you know, bigger company CEOs who are much more stable, much older companies. And the idea that there is some kind of grand shakeup between what a product manager does, what a designer does, what an engineer does. And everyone's going to get the same skills. And maybe that classic trio doesn't have to exist anymore. The bigger companies, they've got to manage that pretty carefully, right? They're architected around those roles in very specific ways. I think it's fair to say Alton is still a startup, right? You're still operating a bit like a startup. It sounds like you don't have any of that baggage. You can just start over and say my domain experts are now going to be product designers in whatever way that works. Are the tools good enough for you to do that as a software CEO? Or do you still have the other roles kind of backstopping everything? Yeah, it's getting pretty psychedelic. It's all blending together. You know, my favorite has been watching some of our engineers lean in on design. And you're seeing it kind of in all directions. But yeah, there's, there's definitely a convergence of those functions where a designer can ship code. A product manager can design and prototype. A PM can ship code, just hand all tickets themselves. Engineers can get on a design game. So I'd be lying if I said we had the end state fully realized, but this is an active conversation that we're having out loud with all these stakeholders in the company. It's like, okay, these roles are converging. And like, what are the new ways of working and how are you going to expand your skillset and kind of push into this new, this new horizon? And, you know, I think most everybody's been excited and along for that ride and trying to surf the wave, but you know, it does, it does. It does threaten certain egos. You know, if you've come up as a, as a close to the metal engineer, this is threatening. If you've come up as a really principled user experience researcher and product designer, you know, this could be threatening and end to end. So, you know, just like anything else changes changes hard and you got to manage it through you know, a cultural transformation of the organization. Alton is not that old. Like how much transformation are we talking about here? Plenty. It's I think we're coming up on eight years now, but it's, I would say that the difference is we've, we've got a team that's pretty mature for a tech company because of the, you know, the scale of what we've taken on, the ambition of what we've taken on the complexity. We tend to hire just later in careers. I mean, obviously there's a spectrum, but I think, you know, on the, on the engineering side, especially we've got, we've got some really, really seasoned people in the company. Same is true in commercial. So it's, it's not just about, you know, how old is the organization? It's, it's like how long have folks built mastery in these domains? I was going to ask you about that. Your clients are, they're not lax customers. They have opinions that, as you said, the stakes are very high. You're not building productivity software. How do you manage the stakes of building that software against the pull to re-architect how software is built? Because I know you could manage the stakes with the old way. Those old ways are proven and tested. You have a lot of people at your company that it sounds like they know those ways. And then there's the pull to build companies around new ways of making software, you know, far less tested. You're probably putting your finger on the, on the raw nerve between me and our engineering team. So yeah, look, it's getting incredibly easy to prototype and get an MVP out there. It's still hard to get a highly functional, highly performant at scale software deployed with SLAs, you know, service level agreements that include like 99.999% uptime for some of these workloads that some of the most important organizations in the world. So it's a tension. I don't think that we certainly haven't solved it. We're starting to chip away at the edges of some of these things where I'm sure you've heard of and you've had conversations around harnesses. Yeah. So, you know, putting real like scaffolding around the code base and you know how these systems interact with each other and, you know, follow rules and test themselves. And so that's getting better and better. And it's giving it's getting more degrees of freedom to ship quickly and run those tests and make sure things aren't breaking. But it's not a panacea and we're not in the promised land of just like, you know, infinite coding and infinite roadmap as much as, as much as the hype would say otherwise. Boy, does the hype say otherwise? The entire, there's like the global economy you and I are going to talk about. And there's the global economy right next to it that is entirely built in some of that hype. You have a bunch of talented people who know what they're doing. And then there's your customers. And I'm guessing your customers are very conscious of their margins, right? I'm guessing they push you on cost because you are just added cost to getting the good to the end user and selling it for whatever money you're going to sell it for. How are you managing your token costs, right? The idea that you're The cost per token are just getting crazy. And what are we going to do to get observability and controls? And should we flip the permissioning model where you have to get permissioned into Fable and not the other way around? And everyone's having the conversation at the same time, but it's like $20, $50 a million tokens. So it's, you know, their economics are kind of forcing the conversation. That being said, we've really not seen, we've really not seen tokens spend impact our bottom line in a material way, right? Like sure, on the very margin, has it gone up? Yes. But I think we're shipping faster, we're being more productive, and it's sort of a no-brainer ROI. Like it hasn't even gotten to my consciousness where, you know, but for, like I said a few weeks ago with Fable. In terms of flowing through cost to customers, so we have a different set of products. You know, some of them are scaling on the dimension of the products under management, so the physical goods under management. So if you're on the Eltona network, you're managing your products, their parts, the value chain networks associated with them, and you can share those product passports with your customers, with your freight forwarder, with your regulator, right? So that's the network we built. And the more products, you know, physical goods that you manage on the Eltona network, the more we charge you. That's one dimension of it. And that doesn't necessarily scale with like AI compute. It does in a little way, but not from our pricing standpoint. What we're now reckoning with with this Servo acquisition and some more of our agentic workflows that we built ourselves is having agents do work. And agents can run up a lot of compute, right? And so that is a gross margin question that you have to really manage carefully. And then you get into pricing dynamics with customers where it's like, well, what's the value of the work, right? So charging for tokens is kind of silly. Charging for outcomes and charging for units of work where there's some alignment around the value of work is where we're going. And in customs brokerage, to kind of bring it back to the acquisition we're announcing today, in customs brokerage, you have an existing pricing model where these logistics providers are charging the businesses whose goods they move on a per customs declaration basis. So it's anywhere from $20 in the very low end to $200, $250 on the high end for more complex customs entries. And you do that, you know, day after day after day, shipment after shipment after shipment, and it kind of runs the cash register. And with agentic AI being able to do, you know, most of that work now, it puts you in some really interesting places, you know, as Altana to experiment with pricing, but also as a global logistics provider. You know, does it make sense to have a $200 per entry pricing model, or, you know, can we kind of shift the value creation left and say, hey, you know, we, global freight forwarder, are going to help you manage your supply chain network to be more compliant, to be more resilient. We're going to help orchestrate your supply chain. And we're going to stop billing you transactionally to clear goods across the border. We have to take a short break here. We'll be back in just a minute. Support for this show comes from Comcast Business. Modern enterprise. It's a lot of moving parts, multiple locations, a constant flow of data, endless applications, critical systems that can't go wrong. Comcast Business helps you orchestrate it all. With SD-WAN working at scale to keep 150 hospital locations connected and working as one, so patient data flows securely and care is delivered without interruption. That's a healthy approach. Plus SASE and zero-trust security protecting financial data across a bank's 2,000 branches. That means identity is verified, transactions secure, threats blocked, nest eggs safe and sound in the best of hands. And AI-powered networking that optimizes traffic across five continents. So yeah, modern enterprise is complex. Comcast Business makes it simple. When you add it all up, no one does business like Comcast Business. Welcome back. I'm talking with Altana CEO Evan Smith about what automation does to the entire customs process. It strikes me just with this acquisition in particular, the governments of the world, the people of the world, we're putting up a lot of trade barriers for a lot of reasons. And you have a view of what you might call the path of least resistance. How do I get this object from here to there with the fewest amount of forms? And it's funny because the forms represent one kind of friction. And you can just point the gun at it. You can just point the agent at it and overcome the friction. Do you find that the AI systems are getting more efficient at that? Or my criticism of AI in general is like, they're not actually learning. If you fill out the form one time and you run the agent again, it, in many ways, is starting over from scratch. And you're going to burn all the same tokens again. And maybe the inference in general will get more efficient, but the compute task itself, even though it's been repeated so many times, does not get optimized. And like, is there efficiency there for you? Yeah, there is. I think in the world of just LLMs predicting the next token, you're right. In a world of agents that follow SOPs, I think you're wrong. And what I mean, and I'll narrow it specifically to where I know what I'm talking about, which is this trade and customs and supply chain world. So the Servo platform, and now as part of Altana, you can go as a logistics provider, you can say, I'm going to create standard operating procedures for every one of my customers and their data pathologies. So I'm bringing in, you know, I've got PDFs with these data fields in them with these like weird numerical formats. I've got, you know, Chinese script coming in alongside English script. And here's how to handle these weird edge cases that would break earlier systems. And you can feed the machine a document to distill rules like standard operating procedures to handle that, just like a human would follow those rules. They also have the user experience where as the broker interacts with the customs entries and with the data coming from the supply chain on a customer by customer basis, they have a workflow where as the user, you know, modifies something here or there, the platform auto-suggests an update to that standard operating procedure. And then you can go and kind of key in an SOP from scratch. And so it's learning SOPs, it's codifying SOPs, and it follows SOPs. And, you know, is there like a theoretical way that those SOPs could be kind of broken or, you know, where there's a fail case? Surely, but in general, it's amazing. And this is why agentic AI in the logistics space generally is having its moment. Like there's like every fifth company in Y Combinator is doing something around logistics automation where it's like, oh yeah, I can take all these kind of unstructured and semi-structured data inputs and reason, like extract information from them, reason about them on a customer or trade lane or kind of outcome specific basis, and then orchestrate a workflow. And that just wasn't technically possible until like January. I do love the phrase data pathologies. I like the idea that a company's structured data is actually like diseased in some way and only AI can solve it. It's very good. I guess I hear you that I'm wrong, right? That you can build around the models, a system that gets more intelligent over time and maybe gets more efficient on a timescale, right? I'm just asking about like literally burning tokens, like using the intelligence of the models. Is that getting more efficient or is it the deterministic systems around it that help the users update these standard operating procedures? I'm probably the wrong person to be highly opinionated about this, but my co-founder, who is entitled to this opinion, has observed that there's no real ROI on Fable right now. Okay, so the more intelligent model is not like helping you out. I'm curious about this because Altana as a software platform solves a lot of very bureaucratic challenges as trade barriers go up. There's another set of challenges I want to ask you about, which are essentially military challenges. We'll come to that. But it just seems like it's a bit of a cat and mouse game between the amount of bureaucratic trade barriers we can put up and the amount of software we can deploy at those barriers to just overcome them. And at some point, like the cost curve might bend and the bureaucracy might win. Well, I'll tell you our product strategy and just our overall thesis on flipping the script. So right now, every time a shipment arrives at the border, it's as though it's the first time the government has ever seen that shipment of goods. This is an abstract government or hard government. Every government in the world. Okay. And what I'm saying is true. So the customs process has been built up for millennia to scrutinize a shipment and to levy the goods and then let it through the border. Right. And it used to be the case that when it was kind of cuneiform tablets and, you know, sailboats going up the Tigris or Euphrates River and transporting goods, somebody could look at each of the things in there and issue a levy. And that was it. Right. And as container shipping. Came about and the scale of goods being entered at a port just exploded. And then with, you know, air cargo and then just the velocity, right? It became impossible to look at all the shipments and to look at all the goods in the shipments. And so for decades, the whole concept was, all right, we'll do random sampling, random targeting, and we'll let the kind of intuition of the port officers dictate, you know, what they're going to go look at. After 9/11, that was no longer okay. And so then a whole kind of technology and policy framework arose in the post-9/11 world, where it was risk-based targeting and segmentation. So the idea was, we're going to try to pick needles out of the haystack using analytics. And, you know, with the systems that existed at the time, those are pretty crappy. I'm not going to name names, but one major government I know intimately well has a 0.5% targeting hit rate in their customs targeting system. So, you know, these are like rules-based systems where it's like, if a container of frozen squid comes in, you know, search it for cocaine. That's a real example. That's great. Yeah, they found cocaine one time in the box of frozen squid, and every single shipment of frozen squid thereafter has been opened, and guess how many times they've found cocaine in the box? I'm going to say zero. Zero. Yeah, so that's kind of, that's been the state of the art for the last 20 years. And now our point of view is that with AI, two things are possible. One is that you can continuously monitor and screen everything. You don't have to selectively target. And two is that, you know, as these trade policies are increasingly focused on the goods and their provenance, I'm sure we'll get to that in the conversation, but like network shape, supply chain network is kind of the dimension of trade analysis. It becomes imperative to have a sense of product identity. So instead of just like transaction by transaction by transaction at the border, it's Groundhog Day and like I've never seen this before. I have to reason about, you know, whether this is the right customs codes and the right duties and did the Food and Drug Administration get their permit to release these, you know, pharmaceuticals or whatever. We ought to just have a library of trusted goods in the same way that we have a register of trusted travelers. And that's what we're building. So our Inotana product passport for the U.S. government is becoming a library of known and continuously monitored and vetted goods and their production pathways where you can, in one shot, you can look at the compliance attributes. You can look at the national security dimensions of it. You can look at the safety dimensions of it. You can look at the tariff dimensions of it and have that all continuously reviewed and monitored. And the benefit to the importer is like, do it once. And, right? So, and, you know, I remember going through the airport in the early days of like Trusted Traveler programs and thinking there's no way in hell I'm going to give the government any information about, you know, my travel, my personal life, any of that, that I don't have to. And then you kind of see the benefit of the, you know, security facilitation, the travel facilitation. And it's like, well, I think I'll make that trade. And that's where we're enabling the private sector to engage in a new way with government agencies around the world. So we're doing this now at scale in the United States. We're doing it at scale in the context of defense procurement. And we're going to be doing this in a pilot context in Europe and I think the UK in the coming months. There's a lot to unpack there. I'm curious about, you know, the product passports. Again, this strikes me as a solution to an administrative problem, a political problem, right? That we want to, the Trump administration particularly wants to move manufacturing out of China, wants to reduce the dependency on China. A lot of companies, big companies want to move their supply chains to get them out of those risky parts of the world. Maybe they want to clean up the environmental impacts or the labor impacts of their supply chains. You provide all that to them, right? We can vet this product is going to show up. Like I said at the top of the conversation, the rubber has really hit the road on all of that, on all those policy goals. Are you seeing manufacturing move out of China into the United States? You've got these passports. Are you seeing the origins of those passports change in meaningful ways? Yes, although probably not exactly in line with the policy objectives of the administration. So without getting into like political commentary, which I'll mostly skip, I'll just kind of, I'll tell you, you know, as a reader of the news and of the data, and then as an observer of the supply chain network itself through our own platform, I can give you some points of view. So, you know, one question is, are we reduced, is the United States reducing its dependency on China as a source of manufacturing? And I think the answer, probably controversially, is no. So what's happened? And we see this in our data. We see this in the macro statistics as well. Since these trade barriers, in particular the liberation day tariffs and everything since, you've seen a proportionate decrease in Chinese exports to the United States with a proportionate increase in U.S. imports from third-party countries. Think, you know, Vietnam, Mexico, Canada, Malaysia. And we can see through our own platform where those input flows of goods are coming from, and the answer is China. So basically, we've just sort of rerouted Chinese goods through third-party countries where they're undergoing some amount of transformation or not on their way to the same end market destination at a higher cost. And we can say that numerically, right? Now, that's part of the dynamic between or behind the renegotiation of the USMCA, for example. So I'm sure we'll talk about that, but, you know, this notion of supply chain traceability as becoming the kind of buzzword in all of these industrial policy initiatives and trade policy initiatives, that's at the core of it, you know? Like, what's the actual provenance of the goods? What's that multi-tier value chain network of the goods? And we have to know that if we're going to have policies that, you know, try to reshape the network itself. So that's one dimension of the China question. I think another one is, like, have we created more jobs? Have we created more manufacturing in America? There, I think it's kind of a mixed picture. The PMI, which is an index of manufacturing output in the United States, it went down after the tariffs. So we were declining following the big wave of tariffs last year as an economy in terms of our manufacturing output. And in the last, you know, five, six months, that number has actually trended above, you know, 50% or scale 1 to 100, but it's, you know, above the neutral level and it's now actually increasing and it has been increasing. So one way you might think about that, I don't know that this is true, but one way you might observe that is in the initial shock, you had U.S. manufacturers who are importers of stuff in order to make more stuff. And if the input cost of those things or the input availability of those things is highly disrupted, then so are their supply chains and their own output, right? So I think, and I know anecdotally from our own customer base, that was absolutely the case. So the first impact of the tariffs was actually negative on U.S. manufacturing. And what might be playing out that we should be open-minded about is that, you know, as the network adapts to the new tariff environment, you're seeing a general tilting of the scales in favor of U.S. manufacturing and therefore an increase in the PMI and the rest of it. What might also be playing out is that the AI data center thing is peanut buttering over everything. So, and then the other, just the last thing on manufacturing is, are we or are we not creating a bunch of manufacturing jobs in America? On a net basis, again, no political statement here, just kind of observing the data. On a net basis, the answer is no. So manufacturing jobs continue to decline. And then how do you square this increase in manufacturing output that we just talked about with the decline in manufacturing jobs? And the answer there must be industrial automation. And, you know, I think it was always kind of naive to imagine that we're going back to the assembly lines of the 1920s in America. So, you know, is it important to have economic security for a country? Yes. Is it important to have the manufacturing capacity to make very important things, you know, on your own soil or with trusted allies? Yes, it is. Are those efforts going to lead to an explosion in blue collar, well-paying jobs? That is a question that, you know, has not been answered. I do think we can leave the political question of who in the administration sold a very naive vision of what would happen after these tariffs and who didn't aside. But on a policy basis, the goal of the tariffs was to increase costs on goods made out of the country so that we would manufacture them here. So it would become economically viable to manufacture things here. And you're saying that basically has not happened. And if it does happen, those factories will be automated anyway. We had the CEO of Siemens on the show who builds factories for people. He was straight up like, yeah, I'm going to put robots in Kansas. Like that's the way we're going to do it if we do it at all. Are you seeing that kind of explosion of interest? Are you seeing that kind Well, yeah, I think at the macro level, it seems clear that manufacturing is generally going up after going down at first. Manufacturing jobs are not, and that industrial automation would explain that. I have a front-row seat into a few different industries, just given the work we do, where I'd say, you know, there's evidence of the industrial policy working. I'll give you one, drones, autonomy more generally. So the Chinese control roughly 90% of the relevant value chain components for autonomous systems. So even if you have a U.S. startup that's saying, hey, we're making everything here in America, no, you're not. You're assembling component parts to make an air or land-based drone, and, you know, you're saying made in America. But... I just want to say, we had Adam Reed from Skydio on the show just a few weeks ago. Like, legitimately the conversation he and I had. It was, where does it come from? And, you know, we are helping that industry with this question and with that problem statement, but it's not going to happen overnight. But what I will say is, so a couple policies actually came together in a coordinated way to create a real U.S. market for not just the end platforms, but the components themselves. So on the one hand, you had a bunch of FCC restrictions and import restrictions generally that said, like, you know, none of the logic, none of the system controls can come from China. And, you know, they have to be U.S.-made, have to have U.S. parts or at least non-Chinese in some of the fine print. And then what that did is it effectively turned off the supply chain for these platforms, and it made everything more expensive. Okay, so to pair alongside that, what they did was they created a large source of demand and revenue. And so in the Department of Defense, Department of War, there's now this program called drone dominance. And it's billions of dollars of committed capital, so there's a strong market signal. And actually, Autonoms is playing a role in certifying the value chain. So, you know, how do you have component parts that are trusted and where there's real provenance? And it's pretty wild. I mean, you're seeing, like, a little Shenzhen forum in El Segundo around all these, like, defense tech bros who are building autonomous systems. And, you know, that's kind of what it takes, is you have to shape the market sufficiently to achieve your policy objective. And some of it is, like, putting up barriers. Some of it's putting up outright bans, in this case. And some of it's subsidies, and some of it's directed investment. And that's the other piece of it, which is, you know, the administration over the last 15 months has gotten incredibly aggressive on the, you know, not just throwing up barriers, but actually making offensive moves. So, you know, it's grants, it's equity investments, it's loans with warrants, choosing winners in the private sector, and then just, like, plowing capital and procurement into them. You know, we're in the process of creating a national stockpile of critical minerals and magnets. So, you know, methods aside, like, is that the right kind of policy outcome to aim at? Yeah, I think so. I think, you know, we learned over the last year and a half that you don't have economic security if you don't control critical minerals. So you got to do something. We're going to pause here for another quick break. We'll be right back. This is advertiser content from Comcast Business. As cyber threats become more and more machine-based and driven by AI agents, those of us in the cyber defense space, we're having to invest at the same pace. Hi, I'm Chris McFarland, Chief Development Officer at Comcast Business. So when we think about the threat of cybersecurity attacks to businesses, they're just a lot more automated. They have the ability to think. They could scale literally anywhere from a hundred to thousands of times faster than a human can. The reality is that today you need to protect every device, every endpoint, every workload that's running on a server, whether it's your own server or in the cloud. This is an area that Comcast Business excels at. We're enabling intelligence-driven defense with integrated visibility, AI-powered threat detection, and automated response capabilities that prioritize, correlate, and contain risks before they escalate. And so it doesn't matter whether you're a small business or a medium-sized business or a really large enterprise. We've got this incredible portfolio of cybersecurity solutions and services to really enhance your cybersecurity posture. To learn more about how Comcast Business can help protect your business today, visit comcastbusiness.com slash cybersecurity. Welcome back, I'm talking with Autonics CEO, Evan Smith, about North American trade and Canada. Last time we were on the show, the idea that a bunch of warehouses would pop up in Canada and Mexico to import almost complete products from China so you could get them over the border inside the USMCA. It was, I would say it was like a hack. Like you knew that was going to happen. You could see it beginning to happen. You could see it happening. Yeah, and it has just like happened. Like this has happened. The other thing that, and just along that exact same line is, is in September, the United States ended the customs de minimis exemption for low-value imports. So there used to be a threshold of $800. You didn't have to pay duties. There was no customs declaration note. And in order to exploit that, you had those like, you know, Mexican distribution centers, Canadian distribution centers where, you know, containers full of stuff were coming in, but then being drop shipped one by one across the border to U.S. consumers. So the same has been true in Europe and the U.K., and they too just ended their de minimis exemptions. So like that, it's not just the United States adding all this complexity and, you know, friction to businesses and in consumers. This is happening everywhere. Sorry, let's go to Canada, which you're surely going to ask me about. It is the next question. Just this week, you know, President Trump announced new tariffs on Canada, maybe because he's mad about wildfire smoke. Maybe just because he's mad that Spain won the World Cup. Like it's unclear exactly what happened to provoke a new round of tariffs. Jameson Greer, who's the United States trade representative, just did an interview with the New York Times, and he's like, we're gonna run it back on tariffs. Like we got smacked down at the Supreme Court, but we take that as an invitation to find a new legal mechanism to do tariffs the way the administration wants, the way that President Trump wants. It is unclear to me what legal foundation the new tariffs against Canada are resting on, whether they will be upheld. Just based on what we have been talking about here, politics aside, policy outcomes, it feels like the tariffs broadly did not do the things that the administration wanted. There are some things that worked better, particularly plowing capital into markets, picking winners and losers, which is not a thing that people generally love when the United States government does, but it has worked in some cases. And yet we're gonna do tariffs again. I'm curious for your view on how trade with Canada will change now that we've announced some tariffs that may or may not exist, that may or may not get rebated over time, and more particularly with your view of the network, how you see the network adapting to them. Here's my take on Canada. This is gonna be the greatest TikTok clip of all time. Here's my take on Canada. All right, I better be careful. So, look, the Canadians have not come to the table on renegotiating the trading relationship with the United States. And I kind of know that from some of the behind-the-scenes stuff I'm exposed to, but I also know it because it's reported. Whereas Mexico and the United States have been very constructively working on what will become the new rules of the USMCA and in particular, supply chain traceability, which is kind of the linchpin of the new framework that the United States is going to. The way I see this latest round of Canadian tariffs, so this is section 338, which I admittedly hadn't heard of until a couple days ago. So with, you know, 48 hours to consider it, I actually think 338 has a really strong legal foundation for the specific complaint in this case. So 338 gives the president the authority to implement counteractive measures when a trading partner is selectively biasing or penalizing U.S. trade relative to other countries. And what the Canadians did in the last year and a half was just that on autos, on dairy products, on alcohol, you know, like there's no U.S. alcohol on the same shelves that there's European alcohol. So there's plenty of legal authority for the claims themselves. Where it's going to get interesting is the remedy. So it says that, you know, the remedies have to be proportionate to the damages. So, you know, did the tariffs that we, the 50% across this peanut butter of Canadian imports, was that proportionate to the three or four industries that were called out? Probably not. But how long is it going to take to adjudicate that? It's going to be a long time. And in the meantime, everyone's working to put something new in place for the USMCA as the U.S. opted out of the agreement and there's kind of a shot clock to get to some new rules. So I kind of see the whole thing in the context of they're trying to force the Canadians to the table around the USMCA renegotiation. I can see that in, you know, in the abstract of we're doing geopolitics, we're having a good time, right? We're all playing risks together, all the blues. But from a policy perspective, the liberation day happened, you're saying it may or may not have had the numeric effects that we wanted it to have. Some other policies had good effects, and then we ended up paying a lot of rebates because the legal foundation wasn't solid, and Donald Trump and John Roberts are going to be in a fight that is very interesting to legal academics a hundred years from now. But right now on the ground, well, we're just about to have that fight again, and we might rebate all those tariffs again, right? That happened with the liberation day tariffs at high rates. It's certainly could play out that way. You run the software to manage all this administrative and bureaucratic complexity. How do you see the tariff rebates playing out inside your system? And does that tell us anything about how companies and markets might react to this new round of tariffs? We're certainly helping our customers with the rebates. We can kind of calculate duties at any point in time of the then applicable law and do that over a bunch of complexity, like you said. I think this has been the new normal. And again, it's not just the United States. The Chinese have put in place kind of the mirror image of the United States from an export licensing standpoint, and they're compelling the private sector to get certificates and permits and permission from the Chinese to take critical minerals, battery technologies, a whole set of things, and trace those all the way through the end uses and then market through a big global network. The Europeans are doing the same thing. The Europeans just gave themselves the legal authorities to do a whole lot more on the trade barrier, trade enforcement standpoint as a unified customs authority. So I just I don't see the world going any other way than unilateral behavior where geo-economics is kind of part and parcel with geopolitics, and it's getting expressed as these mostly trade policies, but economic security more broadly. No, I think that brings us sort of inexorably to the next turn, which is the military, the warfare turn. We can see it playing out today in a straight-up form of this, right? The United States launched an attack on Iran. Iran shut down the Strait. We brought global shipping in that area to basically a dead halt. We're now maybe in a much longer war about who will control the Strait, what those tolls will be. Altana has a role to play there, too, right? You can obviously watch goods move around area. You can reroute the goods. Put that into context for us. That is the next turn. It feels like, yep, we can play a lot of economic games. We can play a lot of policy games. But when we start firing bullets, like everything changes in very dramatic ways that are hard to deescalate. Describe what you're seeing there and what the pathways out of it might be. That's a big question. I think the lesson that everyone is learning in Hormuz is that economic chokepoints can and will be wielded against adversaries, and that they can and will lead to kinetic or live physical warfare kinds of outcomes. So it's no longer theoretical. It's no longer, hey, I'm sanctioning these banks, which is kind of what you and I grew up with. And it's any of these economic chokepoints, supply chain chokepoints, especially if they're asymmetric, meaning it's more painful for you when I turn you off than it is for me to lose you. So a great example of this is rare earths and critical minerals in China. Like the dollars that U.S. and markets generate for Chinese critical minerals providers, they're a rounding error. Nobody cares. But when they turn those off, they can shut down the United States' ability to make a weapon. So it's highly asymmetric. And those can and will be exploited. And those can and will turn kinetic. I think that's the world we're entering. Literally, the last time I was on the show, you and I talked about John Mearsheimer, who spent his entire career predicting that we will go to war with China. He was my professor at the University of Chicago in the late 90s. Do you think that's inevitable? I mean, the promise of Altana is we're going to fix globalization. We're going to make this, we're going to make trade easier. And the promise of trade, particularly global trade, is you will have so many economic interdependencies that war will be unprofitable. Look, I think the extent to which you can delever to those asymmetric chokepoints and kind of economic weapons, the more likely it becomes that there will be peace. So if the U.S. and the E.U. can make semiconductors and have supply chain and economic security in the realm of advanced electronics in the event of a Chinese blockade in Taiwan, for example, then there's a much lower probability of war if and when that occurred. And I think you can kind of apply that same argument across all these chokepoints. So, yeah, I think supply chain resilience, redundancy, having that kind of network capability to see and then manage through that and, you know, simulate and design more resilient systems, like that is the best path to sort of, you know, controlling the switch yourself as a president. But that's the best path to creating a world that's more likely to be peaceful. The Strait of Hormuz in particular is fascinating because of its oil. Right. And we can see what's happening to energy prices around the country and the world as that conflict waxes and wanes and the ways it only, only appears to be waxing. There are moments of waning, but like, you know, it's like one of those iPhone charts like cumulative sales always go up like that's what appears to be happening there. Do you see that in the data that energy prices are affected by literally the number of ships day to day? Or is that more of, is the system responding to the shock? Both are true. And you're seeing, what's so cool about Altana is like, you can get so many layers beyond the headline. So, you know, how, how is the shock to the helium supply out of the Gulf cascading through semiconductor value chains and pushing on costs there? Like we can actually give you numerical answers to that and we can show you the dependencies and the pathways. So, yeah, look, I think in, in general, we, we tend to, when I say we, I guess it's, you know, pundits and policymakers and people who play risk. I think we tend to both over and underestimate the substitutability of goods. And that's been super interesting. It's like, well, oh, gee whiz, these things are going to turn off. And then there's lots of examples where they were much more substitutable than, than folks knew. And, and, or, you know, the trade routes could, could lengthen and you had 40 days to a voyage and you know, still supply chains flow. In other cases, you're learning about chokepoints that are, you know, not at all substitutable. And, and you know, those kind of Achilles heels reveal themselves. So, you know, Altana has kind of like a bingo board of these things. But what, what I'm really interested in is like, how can we get to a world where you're not discovering those the hard way? And how do you get to a world where you can detect them, you can simulate them, you can build constructs like scenarios that actually shape either policy or capital allocation. And like that is the world. We've got a whole product R and D area where we're enabling policymakers and kind of firms to simulate these things and build those plans and do kind of long range almost network architecture would be the way to think about it. I want to end here because you have a lot of thoughts about network architecture and federating data, which is maybe the most pure decoder bait of all Altana is a system. It works best if everyone participates in the system. You obviously spend a lot of time convincing people to participate in the system. That means they have to offer you some data. They have to obviously have to get some data out of the system in return to be valuable. There's a lot, you're talking about AI quite a bit in this conversation. There's a lot of concern about the AI just hoovering up all of the data and using it for whatever purposes the labs want to use them for eating businesses like yours, or maybe not even just protecting that data at a base level. That is the architecture of your product, right? You gave a keynote presentation about federating data. I want you to end by just talking about that. There was, there was a version of the world. I think you and I grew up in, in which I don't know, multipolar multiparty like organizations across the world would just show up and share data and make everything easy. And they were geared towards cooperation. You have been describing like unipolar actions over and over and over again in this conversation. And Altana is supposed to make that a little bit easier, right? It's a system that will connect a bunch of individual rational actors and the data has to connect in a way that everyone is comfortable with. That seems very hard. Can you just describe that at the end? How are you going to ever participate in this? Because it feels like a software solution to a politics problem. It is a software solution. And the other way I'd describe it is it's a market making solution. So a lot of our, a lot of our calories are spent from a government affairs standpoint or from a sales standpoint, bringing parties together that have aligned interests in these novel ways of working to solve a network shaped problem. So Altana at the highest level, we're a network. You join a network, you benefit from what the network provides. So that's the connectivity to other parties in the network. It's the intelligence and visibility that's revealed in the network. And as you connect to the network, you are contributing Data with each other. And that was the point. So, you know, there's no world. There certainly wasn't back then when we started the company, and it's become even more true that you're not going to reach this nirvana, you know, data commons where everyone's just kind of pooling data in one place. So how do you have shared visibility? How do you have interoperability across global commerce in a world where sovereignty is ever increasingly important? And our answer to that is federation. You've got to put the software and the data in the hands of or in the control of the actors that require it. And especially at the scale of like working with a customs agency or a defense agency, you know, it's non-negotiable. So we're architected in this kind of hub and spoke model where the spokes are customers with very large sensitive data sets that, you know, need us behind a firewall or even in front of a firewall, but with, you know, kill switches and corporate governance and so on. And what we're doing is we're bringing the platform to their data. We have very specific rights to the learnings. So as we connect to the data, as we process it, we have the rights to build out the supply chain network view. So we're not taking pricing. We're not taking like a detailed bill of materials, but the supply chain connections themselves are revealed from the data as we, you know, connect this supply chain graph. And then the other bucket of rights are around learning with pre-trained models. So what we can't do is memorize our customer's data. What we can do is take a pre-trained model. For example, we have systems that detect risky shipments in global trade, or we, you know, predict the valuation of goods or the customs classification of goods. And those models are pre-trained. They're learning across the network. And as we learn from any given customer's data, those model weights and configurations can, can be kind of lifted off for the benefit of the network. And that is the quid pro quo. It's like you give a little and you get a lot. And, and, you know, like I said, the the go to market and the government affairs is increasingly putting together these parties at the highest level. I'll tell you a couple of vignettes. We're very proud of our platform in the UK. We provide the underlying infrastructure for what they call their global supply chain intelligence program. And it's this whole of government, United Kingdom supply chain and economic security control tower. So it's, I think there's 10 agencies that are all part of this. They're pouring their data into the platform. We bring the global picture. We bring the software, the models, and they're reaching these kinds of supply chain resilience and economic security policy outcomes that are, I think, world leading. And they're doing this on this intelligence platform that underpins it. We've been pairing them. We've been putting them in the room with, with senior folks in the United States, in Australia, in the Netherlands, and we're, we're helping them learn from each other on the art of the possible. And we're helping them imagine ways of potentially coordinating policy responses across these agencies and collaborating on some of the actual interventions themselves in the supply chain. Like what if we all collaborated on traceability in the critical minerals context? So, you know, I don't think it's unnatural for these parties to join the platform. I do think it's novel for them to imagine some of these new ways of working. And that's kind of the friction in the sale. And I'm, I'm proud of the progress we're making. And it's like any other network business, you know, the more mass it, it, it builds, the more inevitable and the more valuable it becomes. Let's end by just zooming out a little bit. We've described sort of a world in which we inevitably move towards more war, right? We're just going to go to war to get it in China because there's choke points and people are going to squeeze them. Then there's kind of your vision, right? We're going to imagine new ways of working together in which maybe we're not in part in big NGO organizations that manage trade globally, but everyone's acting in their rational interest. And we have a view of the network that makes it easier to imagine new ways of working with all kinds of supply chain traceability. Tell me where we are in the journey of those two things, like end there, put it to make it not abstract, to bring it all the way down to people on the ground who are feeling anxious about the state of the world today. Which way is it going? Which way do people want? I think we're going toward a world that is more economically secure and therefore more physically secure. So by knowing the provenance of goods, by designing supply chain networks and actually getting like cutting through the fog and being able to make these decisions proactively, by helping the public and private sectors engage with each other constructively and collaboratively on these dimensions, the arc of history is moving toward more economic security and therefore less motivation to need to go to outright war in the event that those economic dependencies are weaponized. So, you know, will there be flashpoints? Of course there will. Is there going to be a world of friction? Of course there will. You know, I think at the end of the day, everyone wants to be safe. They want their kids to be safe. They want their wealth to grow. They want to spend time with people they care about and not have to sweat this stuff. And in a world that's transitioning from one equilibrium to the next, I'm optimistic about the direction of travel here, even though it's going to be messy. Evan, it is always a pleasure to have you on the show. We're going to have to have you back faster than a year and a half. Thank you so much for being on Decoder. Anytime. I'd like to thank Evan for taking the time to join Decoder. And thank you for listening. I hope you enjoyed it. Please let us know what you thought about this episode or really anything else at all. Drop us a line. You can email us at decoder@theverge.com. We really do read all the emails. Or you can hit me up directly on threads or blue sky. We're also on YouTube. You can watch full episodes at DecoderPod. We also have a TikTok and an Instagram at DecoderPod as well. They're a lot of fun. If you like Decoder, please share with your friends and subscribe wherever you get your podcasts. Decoder is produced on The Verge and part of the Vox Media Podcast Network. The show's producers are Kate Cox and Kat Vis episode. It was edited by Kabir Chopra. Our editorial director is Kevin McShane. The Decoder music is by Breakmaster Cylinder. We'll see you next time. Support for this show comes from Comcast Business. Modern enterprise is a lot of moving parts. Comcast Business helps you orchestrate it all with SD-WAN working at scale to keep 150 hospital locations connected and working as one. Plus SASE and Zero Trust Security protecting financial data across a bank's 2,000 branches. And AI-powered networking that optimizes traffic across five continents. No one does business like Comcast Business.