Chat is Dead: OpenAI's Radical ChatGPT Overhaul

Alex Shannon: The company that made chatbots mainstream is reportedly about to kill the chat interface entirely. Like, I’m staring at headlines that literally say ‘Chat Is Dead’ from OpenAI’s biggest ChatGPT overhaul since launch.

Sam Hinton: Dude, the irony is incredible. They spent two years training the entire world to talk to AI through chat, got everyone comfortable with that back-and-forth conversation model, and now they’re basically saying ‘actually, nevermind, we’re doing something completely different.’

Alex Shannon: It’s like if Facebook suddenly announced they were getting rid of the news feed. You don’t just casually overhaul the core interaction model that defines your entire product.

Sam Hinton: Right, and this isn’t some minor UI update we’re talking about. If they’re really moving away from chat, that suggests they’ve figured out something fundamentally better about how humans should interact with AI. The question is: what the hell is it?

Alex Shannon: And here’s what’s really wild - this is all happening while SpaceX is quietly becoming an AI infrastructure giant. We’ve got reports of them securing deals with Google and Anthropic worth billions. Like, since when is the rocket company in the AI business?

Sam Hinton: That’s what I’m saying! The whole AI landscape is getting turned upside down. We’re not just talking about better chatbots anymore - we’re talking about satellites processing AI in space, countries building their own AI infrastructure to avoid being dependent on US or Chinese systems.

Alex Shannon: If even half of what we’re seeing today is accurate, we might be looking at the biggest shift in how AI works since ChatGPT launched. And frankly, I’m not sure anyone is prepared for how fast this is moving.

Alex Shannon: You’re listening to Build By AI, I’m Alex Shannon, and we’re diving into what might be the biggest AI interface revolution since ChatGPT launched.

Sam Hinton: And I’m Sam Hinton. Today we’re not just talking about OpenAI’s radical ChatGPT overhaul, but also how SpaceX is quietly becoming an AI infrastructure giant and why every major tech company is suddenly obsessed with South Korea.

Alex Shannon: It’s June 8th, 2026, and honestly, the pace of change in AI infrastructure is getting wild.

Sam Hinton: Buckle up, because if these stories are accurate, we might be looking at the end of the AI interface era as we know it.

OpenAI plots biggest ChatGPT overhaul since launch

Alex Shannon: Alright, let’s dive deep into this OpenAI story because honestly, I’m having trouble wrapping my head around it. We’ve got reports from the Financial Times and Gizmodo saying that OpenAI is planning the biggest ChatGPT overhaul since launch, and Gizmodo is literally using the phrase ‘Chat Is Dead’ to describe what’s happening.

Sam Hinton: Yeah, and that’s not clickbait hyperbole. The reporting suggests they’re fundamentally redesigning the chat interface itself. Think about how radical that is - the entire ChatGPT experience is built around that conversational back-and-forth.

Alex Shannon: But Sam, help me understand this. Why would you kill the thing that made you successful? Chat interfaces work. People get them. They feel natural.

Sam Hinton: OK but here’s what people are missing - chat interfaces are actually pretty limiting when you think about it. You’re forcing complex AI capabilities into this linear, turn-taking model that’s designed for human conversation. What if the AI could show you information, manipulate data in real-time, or work alongside you in a completely different way?

Alex Shannon: So you’re thinking more like a collaborative workspace than a chatbot? Like instead of asking ChatGPT to write code and then copying it out, maybe it’s working directly in your development environment?

Sam Hinton: Exactly! Or imagine instead of describing an image you want, the AI is manipulating visual elements in real-time as you guide it. The chat model forces everything through this narrow text pipeline when AI capabilities are way broader than that.

Alex Shannon: Okay, that makes sense from a capability standpoint, but I’m worried about the user experience angle. Chat interfaces have this huge advantage - they’re immediately familiar. Everyone knows how to have a conversation.

Sam Hinton: That’s a fair point, but remember, before the iPhone, everyone knew how to use physical keyboards too. Sometimes you have to break familiarity to unlock the next level of capability. If OpenAI has cracked a more intuitive way to interact with AI, the learning curve might be worth it.

Alex Shannon: The other thing I’m thinking about is competitive pressure. Google, Anthropic, everyone else is still doing chat interfaces. If OpenAI moves away from chat and it doesn’t work, they’re handing their competitors a massive advantage.

Sam Hinton: But if it does work, they’re not just ahead - they’re playing a completely different game. This could be an iPhone moment where suddenly everyone else’s chat interfaces look ancient. It’s a huge risk, but the potential payoff is enormous.

Alex Shannon: What should people who are building on ChatGPT APIs be thinking about right now? Like, if you’ve built your whole product around chat interactions with GPT, are you potentially screwed?

Sam Hinton: I think the APIs will probably stay stable for a while - OpenAI can’t just break everyone’s integrations overnight. But yeah, if you’re building new products, you might want to design them to be flexible about interaction models. Don’t assume chat is forever.

Alex Shannon: Let me play devil’s advocate for a minute though. What if this is just OpenAI getting caught up in their own hype? Like, chat interfaces aren’t perfect, but they’re good enough for most use cases. Are we solving a problem that doesn’t really exist?

Sam Hinton: That’s definitely possible, and honestly, it wouldn’t be the first time a tech company threw away something that worked in pursuit of something revolutionary that nobody actually wanted. Remember when everyone tried to kill the desktop metaphor for tablets?

Alex Shannon: Right! And users can be surprisingly resistant to change, even when the new thing is objectively better. I mean, how long did it take people to stop using Internet Explorer?

Sam Hinton: But here’s the counter-argument - OpenAI has access to usage data from millions of ChatGPT users. If they’re making this bet, they’ve probably identified real pain points in how people interact with the current system. They’re not just guessing.

Alex Shannon: That’s a good point. They can see where conversations break down, where users get frustrated, where the chat model stops being helpful. If the data shows chat is fundamentally limiting, then this makes total sense.

Sam Hinton: Plus, think about power users - the people who are pushing ChatGPT to its limits. I bet those users are constantly running up against the constraints of the chat interface. OpenAI probably wants to unlock those advanced use cases.

Alex Shannon: And from a business perspective, if you can create a fundamentally better way to interact with AI, that’s incredibly valuable intellectual property. Even if it’s risky in the short term, it could define the industry for the next decade.

Sam Hinton: Absolutely. And timing-wise, this might be their best window. They’re still the market leader, they have the resources to experiment, and they haven’t locked themselves into legacy systems yet. Better to cannibalize your own product than let someone else do it.

Alex Shannon: For our listeners who are building AI-powered products right now, what’s the takeaway? Should you wait to see what OpenAI does, or just keep building with current chat interfaces?

Sam Hinton: I’d say keep building, but stay flexible. Design your products so they’re not completely dependent on one interaction model. And pay attention to where your users hit friction - those might be the same problems OpenAI is trying to solve.

ChatGPT’s evolutionary leap: Continuous memory across all chats

Alex Shannon: Now here’s another piece of the ChatGPT puzzle that I think ties into this overhaul story. There are reports that ChatGPT is implementing continuous memory functionality that persists across all chats. So instead of every conversation starting fresh, the AI remembers context and information from all your previous sessions.

Sam Hinton: Dude, this is huge and it completely changes the value proposition. Right now, ChatGPT is like having a brilliant conversation partner who has amnesia. Every chat starts from zero, you have to re-establish context, explain your projects again. Persistent memory turns it into more of a long-term collaborator.

Alex Shannon: But Sam, doesn’t this also tie into the interface overhaul we just talked about? Like, if ChatGPT remembers everything about you and your work, maybe the chat model becomes even more limiting?

Sam Hinton: Oh absolutely! That’s a brilliant connection. If the AI knows all your ongoing projects, your preferences, your work style, it doesn’t make sense to interact with it through these discrete chat sessions. You’d want something more like a persistent workspace where it can proactively surface relevant information.

Alex Shannon: I’m starting to see how these pieces fit together, but I have to ask about privacy. Continuous memory means OpenAI is storing and connecting data across all your interactions. That’s a pretty significant privacy shift.

Sam Hinton: Yeah, that’s the trade-off. You get this incredibly personalized, contextual AI experience, but you’re essentially giving OpenAI a complete record of your digital thought process. Some people will love that, others will find it creepy as hell.

Alex Shannon: And what about in enterprise settings? If ChatGPT remembers everything from your work conversations, how do you handle confidential information, client data, stuff that legally can’t be stored by third parties?

Sam Hinton: That’s going to require some serious infrastructure changes. OpenAI probably needs to build enterprise versions with isolated memory systems, maybe on-premise options for sensitive industries. The memory feature is game-changing, but the data governance complexity is going to be massive.

Alex Shannon: From a user perspective though, assuming they solve the privacy concerns, this could be incredible for productivity. Imagine an AI that knows all your projects, remembers your coding style, understands your business context.

Sam Hinton: Exactly, and it gets smarter about you over time. Instead of being a generic AI assistant, it becomes your personalized AI colleague. That’s the kind of stickiness that makes people never want to switch to a competitor.

Alex Shannon: But here’s what I’m wondering - how do you handle the evolution of preferences? Like, if I was working on web development six months ago and now I’m doing data science, I don’t want the AI to be stuck on my old preferences.

Sam Hinton: That’s a really good point. The memory system needs to be smart about what to remember, what to forget, and what to weight based on recency. If it just accumulates everything forever, you’ll end up with an AI that’s confused about what you actually want.

Alex Shannon: And what about shared accounts? If you’re working on a team project and multiple people are using the same ChatGPT account, whose preferences and memory does it prioritize?

Sam Hinton: Oh man, that’s a nightmare scenario. You’d probably need user-specific memory profiles within accounts, or completely separate instances. The complexity just keeps growing when you think about real-world usage patterns.

Alex Shannon: But let’s say they figure all that out. The competitive implications are massive. Once you’ve built up months or years of memory with ChatGPT, switching to Claude or Gemini means starting over from scratch.

Sam Hinton: That’s the vendor lock-in aspect, and it’s incredibly powerful. It’s like how hard it is to switch from one email provider to another, except this is your entire AI relationship. OpenAI would essentially be building a moat around each user.

Alex Shannon: Which makes me wonder if there will be regulatory pressure around data portability. Like, should users have the right to export their AI memory and take it to a different provider?

Sam Hinton: That’s a fascinating question. In the EU, you probably would have that right under GDPR. But good luck getting that memory to work properly in a different AI system. It’s not just data, it’s how that data is structured and used by the AI.

Alex Shannon: For developers building on top of ChatGPT, this memory feature could be either amazing or terrifying. Amazing because your app gets smarter over time, terrifying because your users’ data is even more locked into OpenAI’s ecosystem.

Sam Hinton: Yeah, and you lose some control over the user experience. If ChatGPT is remembering things from other apps and conversations, your carefully designed onboarding flow might be irrelevant for returning users.

Alex Shannon: Keep an eye on this because if OpenAI nails both the interface overhaul and the persistent memory, they’re not just improving ChatGPT - they’re potentially defining what the next generation of AI interaction looks like.

SpaceX secures Google AI compute deal after Anthropic pact ahead of IPO

Alex Shannon: Alright, let’s shift gears to something that caught me completely off guard. SpaceX has secured a Google AI compute deal, and this is coming after they already made a deal with Anthropic. Both of these are happening ahead of SpaceX’s anticipated IPO, and I’m honestly confused about why SpaceX is suddenly in the AI infrastructure business.

Sam Hinton: OK so this is actually brilliant when you think about it. SpaceX has Starlink, which is this massive global network of satellites. What if they’re not just providing internet connectivity, but actually offering edge computing through their satellite constellation? That would be insane.

Alex Shannon: Wait, are you saying they could run AI models in space? Like, instead of sending data down to Earth-based data centers, you’re processing it on the satellites themselves?

Sam Hinton: Exactly! Think about the latency advantages, especially for global applications. If you’re in rural Africa or the middle of the ocean, instead of your data traveling thousands of miles to a data center and back, it’s processed right there in orbit. For real-time AI applications, that could be game-changing.

Alex Shannon: But hold on, that seems technically impossible. Satellites have power constraints, thermal management issues, limited processing capabilities. Can you really run sophisticated AI models in that environment?

Sam Hinton: That’s the engineering challenge, but remember, AI inference is getting incredibly efficient. With model optimization and specialized chips, you might not need massive data center-level hardware. Plus, SpaceX is already planning bigger satellites for Starlink v2.

Alex Shannon: The timing with the IPO is interesting too. If SpaceX can position itself as not just a space company but as a unique AI infrastructure provider, that completely changes their valuation story.

Sam Hinton: Right, because suddenly they’re not competing with other rocket companies - they’re competing with AWS and Google Cloud, but with capabilities those companies literally cannot replicate. You can’t launch AWS into orbit.

Alex Shannon: And the customers make sense too. Google needs global AI compute capacity, Anthropic is scaling up their model deployment. If SpaceX can offer global coverage with lower latency than terrestrial networks, that’s incredibly valuable.

Sam Hinton: What’s wild is this could be the first time space infrastructure becomes directly relevant to everyday AI applications. Like, your ChatGPT query might literally be processed in space.

Alex Shannon: But let’s think about the practical challenges. How do you update AI models on satellites? How do you handle hardware failures in orbit? What happens when you need more compute capacity - do you just launch more satellites?

Sam Hinton: Those are all massive engineering problems. But SpaceX has gotten really good at launching things cheaply and frequently. If you can treat satellites like disposable compute nodes that you refresh every few years, maybe it works economically.

Alex Shannon: And there’s a geopolitical angle too. If SpaceX provides AI compute through satellites, that’s harder for foreign governments to regulate or shut down compared to terrestrial data centers.

Sam Hinton: Oh that’s a really interesting point. For companies operating in countries with strict AI regulations, space-based computing could provide a way around local restrictions. That adds a whole new dimension to the value proposition.

Alex Shannon: But what about bandwidth? Even if you’re processing AI models in space, you still need to get the input data up to the satellites and the results back down. Isn’t that still a bottleneck?

Sam Hinton: For some applications, sure. But think about use cases where you’re processing local data - like satellite imagery analysis, autonomous vehicle coordination, IoT device management. If the data is already nearby or generated locally, space-based processing makes more sense.

Alex Shannon: For investors watching the SpaceX IPO, this adds a completely new dimension to consider. They’re not just betting on space transportation and satellite internet - they’re potentially betting on the future of distributed AI computing.

Sam Hinton: And if this works, every other satellite company is going to be scrambling to add compute capabilities to their constellations. SpaceX might be creating an entirely new market category here.

Alex Shannon: The scale could be incredible too. Starlink is planning tens of thousands of satellites. If even a fraction of those have AI compute capabilities, you’re talking about a distributed supercomputer that spans the entire planet.

Sam Hinton: And unlike terrestrial data centers, satellites are constantly moving, so you could optimize compute placement based on demand patterns. Need more AI processing power over Asia during business hours? Route compute tasks to satellites that are currently over that region.

Alex Shannon: The more I think about this, the more it makes sense why Google and Anthropic would be interested. This isn’t just about buying compute capacity - it’s about accessing a completely new type of infrastructure that could enable AI applications we haven’t even thought of yet.

Naver, Nvidia to form AI factory alliance in sovereign AI push

Alex Shannon: Now let’s talk about something that’s flying under the radar but could be really significant. Early reports suggest that Naver, which is basically the Google of South Korea, is partnering with Nvidia to form what they’re calling an AI factory alliance. This is part of a broader sovereign AI push, and there are also reports of Nvidia striking multiple AI infrastructure deals with other South Korean tech firms.

Sam Hinton: Yeah, and this sovereign AI angle is fascinating because it’s not just about technology - it’s about national strategy. South Korea is basically saying ‘we’re not going to be dependent on American or Chinese AI infrastructure, we’re building our own.’

Alex Shannon: Help me understand the sovereign AI concept though. What does it actually mean in practical terms? Like, are they building their own chips, their own models, their own data centers?

Sam Hinton: It’s all of the above. Sovereign AI means controlling your entire AI stack from chips to models to applications, usually within your national borders. Think about it like energy independence, but for artificial intelligence. You don’t want to be cut off from critical AI capabilities because of geopolitical tensions.

Alex Shannon: That makes sense given what we’ve seen with chip export restrictions and trade wars. But why is Nvidia involved if this is supposed to be about independence? Isn’t Nvidia still an American company?

Sam Hinton: That’s the pragmatic reality. South Korea can’t build cutting-edge AI chips overnight, so they’re partnering with Nvidia for the hardware while building everything else domestically. It’s like controlled dependence - they get the chips, but they control the data, models, and applications.

Alex Shannon: And Naver is interesting because they’re not just a search company. They’ve got cloud services, e-commerce, messaging, even autonomous vehicles. So this AI factory could potentially power a huge chunk of South Korea’s digital economy.

Sam Hinton: Exactly, and that’s probably why other countries are watching this closely. If South Korea can successfully build sovereign AI capabilities that actually compete with American and Chinese systems, it becomes a model for other mid-sized tech powers.

Alex Shannon: I’m curious about the economics though. Building sovereign AI infrastructure has to be incredibly expensive. Is South Korea big enough as a market to justify that investment?

Sam Hinton: That’s where the export angle comes in. If they build world-class Korean AI models and infrastructure, they can export that technology to other countries that also want alternatives to US and Chinese AI. Think of it as creating a third pole in the global AI ecosystem.

Alex Shannon: For businesses operating in Asia, this could actually be really important. Having high-quality AI infrastructure that’s not subject to US-China tensions might be worth paying for, even if it’s more expensive initially.

Sam Hinton: And for developers and AI companies, this creates new opportunities. If South Korea builds genuinely competitive AI infrastructure, suddenly you have more options for where to deploy your models and serve your customers.

Alex Shannon: But let’s talk about the technical challenges. Nvidia provides the chips, but what about the software stack? Training large language models requires incredibly sophisticated infrastructure and expertise.

Sam Hinton: That’s probably where Naver’s existing tech talent comes in. They already have teams working on search algorithms, recommendation systems, natural language processing for Korean. Building on that foundation with Nvidia hardware could actually work.

Alex Shannon: And there’s a cultural advantage too. AI models trained specifically for Korean language and culture might perform better for Korean users than general-purpose models from OpenAI or Google.

Sam Hinton: Absolutely. Think about how much context is lost when you’re using an AI trained primarily on English text to understand Korean business practices, cultural references, local regulations. A truly Korean AI could be significantly better for local applications.

Alex Shannon: This also makes me wonder about data sovereignty. If all your AI processing happens on Korean infrastructure with Korean data, that’s a lot more control over sensitive information.

Sam Hinton: Right, and that’s particularly important for government and enterprise applications. You don’t want your military communications or corporate strategy documents being processed by foreign AI systems, even if they’re technically better.

Alex Shannon: For other countries watching this, what’s the lesson? Should every nation be building sovereign AI capabilities, or is this only viable for countries with South Korea’s level of technical sophistication?

Sam Hinton: I think it depends on your strategic priorities and technical capabilities. Smaller countries might be better off forming regional AI alliances or partnering with trusted providers. But for mid-sized tech powers like South Korea, Japan, or European countries, sovereign AI starts to make sense.

Alex Shannon: And the timing is interesting. If you’re going to build sovereign AI capabilities, now is probably the window to do it. In five years, the technology gap might be too large to catch up.

Sam Hinton: Exactly. The AI industry is still young enough that a focused national effort can potentially compete. But that window is closing as the leaders pull further ahead in terms of compute resources and data.

RAPID FIRE

Alex Shannon: Alright, let’s hit some rapid fire stories. First up: Anthropic has expanded access to Claude Mythos to 150 organizations globally. Sam, this feels like a big scaling moment for Anthropic.

Sam Hinton: Absolutely, and the timing is perfect given all this SpaceX infrastructure news. Anthropic is clearly preparing for massive scale, and having 150 enterprise customers gives them real-world feedback to improve the model.

Alex Shannon: The enterprise angle is key because that’s where the real money is in AI. Consumer subscriptions are nice, but enterprise contracts are what fund the massive compute requirements for training these models.

Sam Hinton: Plus, enterprise customers have different requirements than consumers - better security, compliance, customization options. Getting that right with 150 organizations is incredibly valuable data for Anthropic’s product development.

Alex Shannon: And 150 is a meaningful number. That’s not just a limited beta - that’s real commercial deployment. These organizations are probably paying significant amounts for access to Claude Mythos.

Sam Hinton: Right, and each of those 150 organizations probably represents hundreds or thousands of end users. So Anthropic is getting usage data from potentially tens of thousands of professional AI users. That’s gold for model improvement.

Alex Shannon: Next story: There’s a Yahoo Finance piece asking if Anthropic and Google just gave investors 2.2 billion reasons to buy the SpaceX IPO. This seems to be referencing some major investment deal between Anthropic and Google.

Sam Hinton: Wait, 2.2 billion? That’s not just an investment, that’s a statement. If Google is putting that kind of money into Anthropic, they’re basically betting that Claude becomes a serious competitor to GPT.

Alex Shannon: And the SpaceX IPO connection suggests that investors are viewing AI infrastructure as the key value driver. Like, the rocket business is proven, but the AI infrastructure potential is what could make this IPO massive.

Sam Hinton: Right, because 2.2 billion in AI deals shows there’s real demand for the compute capacity that SpaceX could provide through their satellite network. It’s validation of their AI infrastructure strategy.

Alex Shannon: But here’s what’s interesting - if Google is investing 2.2 billion in Anthropic, and also making deals with SpaceX for AI compute, Google is essentially hedging their bets across the entire AI value chain.

Sam Hinton: That’s classic Google strategy. They’re not just building their own AI capabilities with Gemini - they’re also investing in potential competitors and alternative infrastructure. If any part of the AI ecosystem takes off, Google has a position.

Alex Shannon: For SpaceX IPO investors, this validates that there’s serious enterprise demand for alternative AI infrastructure. These aren’t speculative bets - these are multi-billion dollar commitments from established tech giants.

Sam Hinton: And it shows that the AI infrastructure wars are really heating up. Companies are willing to pay premium prices for compute capacity that gives them strategic advantages, whether that’s lower latency, better security, or just alternative supply chains.

BIGGER PICTURE

Alex Shannon: If you zoom out and look at everything we covered today, there’s this fascinating theme about the next phase of AI competition. It’s not just about who has the best models anymore - it’s about who controls the infrastructure and who defines how people interact with AI.

Sam Hinton: Exactly, and what’s wild is how different the strategies are. OpenAI is betting on revolutionary interfaces, SpaceX is betting on space-based computing, South Korea is betting on sovereign infrastructure, and Google is just throwing billions at everyone to make sure they have a seat at every table.

Alex Shannon: The infrastructure wars are really heating up. Five years ago, AI was about algorithms and data. Now it’s becoming about satellites, chip factories, and geopolitical alliances.

Sam Hinton: And for regular people and businesses, this fragmentation could actually be good news. Instead of being locked into one or two AI providers, we’re heading toward a world with multiple competing infrastructures and interaction models.

Alex Shannon: The question is whether all this innovation leads to better AI experiences or just more complexity. Like, do people really want AI in space if their current AI works fine?

Sam Hinton: I think it depends on what new capabilities emerge. If space-based AI enables real-time translation for global calls, or if new interfaces make AI collaboration seamless, people will adopt it quickly. The key is whether the technology improvements are actually noticeable to end users.

Alex Shannon: What’s really striking to me is how quickly the landscape is changing. Two years ago, ChatGPT was this revolutionary chat interface. Now OpenAI is reportedly killing chat, and we’re talking about AI processing in orbit.

Sam Hinton: And that pace of change is only accelerating. The companies that are making big infrastructure bets now - like SpaceX with satellites, South Korea with sovereign AI - they’re betting on where AI will be in 2030, not where it is today.

Alex Shannon: The geopolitical dimension is fascinating too. AI is becoming like energy or telecommunications - critical infrastructure that countries need to control for national security reasons.

Sam Hinton: Right, and that’s driving a lot of the sovereign AI initiatives we’re seeing. It’s not just about having the best AI models - it’s about ensuring you’re not dependent on potentially hostile nations for critical AI capabilities.

Alex Shannon: For businesses trying to navigate all this, the key seems to be avoiding lock-in while still taking advantage of new capabilities. You want to benefit from innovations like persistent memory or space-based compute without betting your entire company on any single provider.

Sam Hinton: Absolutely. And I think we’re going to see more demand for interoperability and standards. Businesses want to be able to move their AI workloads between providers, export their data, integrate multiple AI systems.

Alex Shannon: The other thing that strikes me is how capital-intensive this all is. We’re talking about billions of dollars for satellite constellations, sovereign AI infrastructure, major model training runs. This is not a garage startup kind of game anymore.

Sam Hinton: Which might actually create opportunities for smaller players to focus on specialized applications or niche markets. While the big players fight over general-purpose AI infrastructure, there’s probably room for focused solutions in specific industries or use cases.

Alex Shannon: And for developers, this explosion of AI infrastructure options means more choices but also more complexity. You have to think about where to deploy your models, how to handle data sovereignty, which interaction models to support.

Sam Hinton: But that complexity also creates opportunities for new tools and platforms that help manage multi-provider AI deployments. There’s going to be a whole ecosystem of companies that help businesses navigate this fragmented AI landscape.

Alex Shannon: Looking ahead, I think we’re entering a phase where AI infrastructure becomes as important as the AI models themselves. The companies that control the pipes might be more valuable than the companies that create the content.

Sam Hinton: And that’s why these infrastructure plays - whether it’s SpaceX’s satellites, South Korea’s sovereign AI, or OpenAI’s interface innovations - are so strategically important. They’re positioning themselves to capture value from the entire AI ecosystem, not just model performance.

OUTRO

Alex Shannon: That’s a wrap for today’s Build By AI. Honestly, if even half of these infrastructure changes happen, 2026 is going to be remembered as the year AI went from chatbots to something completely different.

Sam Hinton: Yeah, and we’re just getting started. Make sure to subscribe wherever you listen to podcasts because tomorrow we’ll probably be talking about AI robots in space or something equally wild.

Alex Shannon: Thanks for listening, and we’ll see you tomorrow.