← AI News & Strategy Daily with Nate B. Jones
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OpenAI just released ChatGPT 5.6, but not in a normal way. For now, access is restricted to a small group of government approved partners while Washington reviews the cybersecurity risk. That's not a cancellation, but it's a tremendous slowdown in Frontier availability. And by the end of this video, I want you to understand why that delay. The new Siri, Claude Tag, GLM 5.2 and Codex are all about the same underlying thing. A battle for the part of your brain that understands work, not your brain in the sci fi mind control sense. The everyday part which message matters, which file is current, what the customer actually meant, what the team decided, what can be shared, what can't be shared, what counts as done. Because if Frontier Intelligence slows down even for a few weeks, the next advantage is not owning the newest model, it's having the context that makes any good model useful. Look at the week through that lens and the news starts to rhyme. After Apple's trying to fix Siri by giving it access to your messages and photos and email and notes and screen and apps, Anthropic has launched Claude Tag and Slack, where a team can give Claude access to selected channels and tools and data and code bases. Z AI's GLM 5.2 has made cheap open frontier ish intelligence feel much closer to a reality than it did just a few weeks ago. And OpenAI has a Codex paper showing that inside OpenAI, Codex has become the dominant surface for work related AI output. And those really do sound like completely different stories. I get it. OpenAI being told to slow the rollout, Apple trying to make Siri less embarrassing. Anthropic putting Claude into Slack. How are these related? The problem is the same underneath all of them. The model can be smart and still not know what's going on. If you use AI every day, you already know the feeling. You can Open Codex or ChatGPT or Claude or Gemini. And the model's very capable, right? It can write, it can reason, it can say summarize, it can help you think. But before it can do something useful, you have to carry that entire situation into the context window, often through uploading files to the chat box. You paste the email, you paste the memo, you explain who the client is, you explain which version of the deck is current, you explain that the Slack thread from yesterday changed that decision. This is what prompting has become, as we've asked these models to do more. And then after all of that, when you put all of that in, the AI finally becomes extremely useful. And that's a really big friction point. And that is what we've described as an agent problem, right? A problem that you want agents to fix by going after the context window. And that's the promise that we've all been trying to realize with agents for the last few months. So I'm going to walk you through three surfaces here. I'm going to walk you through Apple's Siri, Claude, Tag and Codex in terms of execution inside OpenAI, and I'm going to walk you through the pressure points around them, just GLM 5.2 on the one hand, the delay of ChatGPT 5.6 on the other. And throughout, we're going to uncover the story of why intelligence is getting cheaper. The newest frontier, intelligence, is coming out more slowly and what that means for all of us. As far as context goes, fundamentally, the next useful AI product is probably not going to be the one that wins a benchmark. It's going to be the one that knows where the work is, what it's allowed to see, what it's allowed to do. And it's going to be something that knows that seamlessly. So let's start with Siri, because Siri is something that, for better or worse, we all understand. Siri has been bad for so long that it's become a punchline. You can ask it something normal, and half the time it either misunderstands the question or gives you a web search that makes you wonder why you bother speaking out loud. So the easy headline for a long time has been Apple's finally trying to do something with Siri. We don't know if it's actually good or not. We have a little skepticism. But Apple's relaunching Siri Siri effectively. And I get where that story exists, right? Apple itself is talking about Siri as a conversational AI assistant, is promising more natural conversations, richer answers, a dedicated Siri app, and that's all a part of the story, and it may well work. I've gotten my hands on it a little bit, I've played with it, but I don't think that Siri becomes Chat. GPT is the story here. I think the story here is that Apple is trying to make Siri useful by connecting it to the context in your life. Like, when is my mom landing on the plane? Requires context from calendar, flight number, email confirmation, whether another family member said they might go pick up mom instead, whether the airplane is late or not. And so the challenge for Apple is to find a way to privately and securely connect Siri to where the context Lives on your phone, right? Photos, calendar, notes, email, app, station, screen, et cetera. And if Siri can do that, Siri's intelligence level doesn't have to be super high for Siri to be incredibly useful. Ultimately, the question of Siri's capability may be the wrong one. And Apple's answer is not a capability answer, it's a context answer. It's an answer about where intelligence lives and they're trying to push it as close to your systems as possible. So on device processing is Apple's goal wherever possible, and then private cloud, where it's not. So one of the things that's really interesting from a product shape here for Apple's solution is that Apple is essentially saying your assistant gets better when it's close to you, and very conveniently, when it's close to you. We can construct a privacy architecture that means it's only yours. And that's a consumer answer to this context problem, right? It's an answer where Siri doesn't have to be able to be that smart to use your phone to be extremely useful. And so suddenly, instead of Apple's advantage coming from the App Store ecosystem or from the hardware, Apple's advant from the fact that we have Apple products and we have context that lives inside the iPhone, and Apple can access that context in ways that are very useful to us. Keep that in mind as we walk over to the work side and we talk about Claude tag. Now, Anthropic's product announcement is pretty plain on the surface. Claude tag starts in Slack. A team can grant Claude access to selected channels, to tools, to data, to code bases. It can tag it in, and then Claude just works through tasks and stages as it's tagged, tagged in, and it can respond in the thread, it can remember relevant information from channels it's in, and it can operate inside of particular permission scopes, particular spend limits, particular logs it can touch. That sounds like a Slack bot, but don't say that too fast, because Slack has had bots for a long time. And the interesting thing is that Anthropic is trying to put the assistant inside your team's context. So on your phone, the context is private and messy because it's your life. In a company, the context is shared and permissioned and political and stale, half written and in six places. And so the thing that's interesting about all of this is that work is happening in those messy places. And for a long time, AI has been kind of separate from that, except in a few instances. Devin has been very successful with this from a coding perspective, but there's not a lot of great off the shelf instances for really intelligent AI coming into that kind of messy context. And so when Anthropic says Cloud Claude Tag can build context over time, that is not only a real claim, but the heart of where the company is going to go. It's a very powerful and dangerous statement because the more useful Claude becomes in Slack, the more it need access to messy stuff companies are bad at governing, like engineering decisions and customer tickets and pricing debates and people information. Anthropic knows this, which is why the launch language spends so much time on scopes and permissions, on admin controls, on channel defined memories. They recognize that they're going to have to earn that trust, because if you put an AI teammate in Slack and it breaks boundaries, you've created a context leak, you've created a corporate liability. And so what Anthropic is saying is you can trust us with this context because you're in charge the whole time. And I think that Claude Tag is a much better signal than most out there of this whole AI coworker phenomena phenomenon, because we have a lot of startups that are in this space and one of the things that Anthropic is doing very intentionally here is they're saying you fed us formal context through prompts, through cowork, through Claude code for a while now trust us with informal context and enable us to be a coworker that's more useful as a result. And no other company can say that in the same way way. This is Anthropic doing for work what Apple is doing for your phone. Now let's bring in Codex. Now, a Codex study is easy to dismiss. It doesn't feel like it's news. But I think the Codex paper is really useful in this conversation because software is showing us the assistant context problem in its cleanest form. And Codex is a piece of software. And the study that's released is essentially how actual employees at OpenAI chose or did not choose to adopt Codex over the course of time and what they used Codex for. In other words, what context did they trust Codex with? And this is fascinating to me because you might think that at OpenAI it's a requirement and everyone's mandated to use Codex. That wasn't how it worked. Codex had to earn everyone's trust. Codex had to earn trust first with engineers and then with other knowledge workers at OpenAI. And so the thing that matters the most to me when I read this study is that even at a company that is one of the most AI native companies on the planet. You still have to think about where you trust a particular AI application with context. And it's not a zero to one light flip switch. But it is true that you can see tipping points. And one of the tipping points that's evident in the data from OpenAI and that I have seen personally, is that codecs got a lot more useful in the last couple months after 5.5 was released. And you can see that in the adoption data that shows that the popular adoption of Codex after 55 in non tech circles in OpenAI skyrocketed. Now, the thing that stands out to me when you put that in the context conversation we've been having is that codex has with 55 earned the trust to get legal stuff, recruiting stuff, sales stuff, like all of that dirty context fed into it in the way it earned trust with engineers for code. And there's a lot more in that study. I encourage you to read it. I can link it. Codex is doing the opposite of cloud tag. So if cloud tag is basically saying you work in Slack, so tag Claude in. Codex is saying your work is sensitive, your work is important. Make sure you point Codex at the local files you care about for that work and Codex can take care of the rest. And so that's a frame that has Codex as your launchpad, Codex as your headquarters, Whereas Claude's frame is more let Claude come to where you already are and you can give it the messy context. In both cases there's some mess. But Claude is saying that they can tackle the human conversation and the context and still do useful work. And Codex is saying, you know what? Give us the files, give us the jobs and we can produce great outputs for you whether you're in legal or sales or hr. I love that distinction. Not because I don't think that OpenAI will release a tag codec soon. These models tend to copy each other, but because I think it shows the difference in product shape around context that these two labs have. Claude has always been a we come to you when we wrap our interface around you kind of products. Claude code was really exciting and cowork was really exciting, partly because they basically said, just type what you want into the terminal, type what you want into Cowork and we will just take care of it for you. Now they're taking the next step into Slack. It's in a sandbox. It's just going to do the work there and then you'll get an output. It's almost like bring your wheelbarrow of work and let us do the work and then we'll give you an output. And it's gotten much more wide ranging as computer use has come in in the last couple of months and that's made it much more useful and you can see that in the study. But it's still fundamentally a file shaped tool and CLAUDE is kind of a chat shaped tool. And I realize that that is a gross simplification because both of them tackle files, both of them do chat, right? So I'm not saying it's one or the other. It's not a light bulb on off conversation. CLAUDE has for a long time thought of the problem of context as conversational in the way they've designed their product. And Codex for a long time has thought about the problem of context in terms of files and has been a file shaped answer. And you can still see the legacy of that context in these moments this week. Now, this brings us to the next OpenAI story, which is around this ChatGPT 5.6 delay. If a frontier model spends the next few weeks or months in a restricted preview, which it looks like almost all of them will, we in the world, do not pause and wait. Companies still have CLAUDE and they have OpenAI models and they now have GLM 5.2, and they'll have whatever new open source model is coming right after that, maybe a new deep seq who knows? And they will have a anticipation, but not the reality of future frontier work from Anthropic and OpenAI, which by the way, are still developing and still accumulating knowledge very rapidly internally. They're just not able to release it as fast. And so the government restriction is putting friction at the frontier of intelligence. And it means that there is more pressure on anthropic and OpenAI to release features like CLAUDE Tag because you have to increase the utility of the intelligence. You already have to bring it closer to context so that you get more value for the customer. If you can spend, you know, two minutes tagging in Claude or 30 seconds tagging in Claude instead of 10 minutes briefing the AI, you've saved yourself a lot of time. You can add that up, right? If it's something where it becomes a seamless part of your work, then you perceive a lot more utility from that, even if the model didn't get smarter. What that means is that we are in the middle of a context war and that is the way you should read the news for the next few weeks. I think you should be looking at it and saying Apple is battling for your personal Context, which, because we bring our devices to work, becomes a work context conversation. Anthropic and OpenAI are definitely battling over work context. They have different shapes for how they do that. And one of the most interesting things here is that effectively the government slowdown is giving open source models time to catch up in in public, even if they're not catching up in private. So Anthropic and OpenAI may maintain their 6, 7, 8 month lead over Open source models privately, but the public models we have access to may start to close because the US Government is slowing down frontier model releases. And that leads to a tremendous amount of pressure on utility in the context there. There's going to be a huge war over how quickly and easily an AI model can apply intelligence to that context. And so look at Apple and Anthropic and OpenAI as being in the same boat, even though we don't typically put them in that boat. And think about your context, Think about what context you're comfortable giving to these companies, think about what context you want to retain, and think about whether you are willing to put the time in to actually build elements of a harness that allow you to decide where to route your context. And so when I've talked about Open Brain and OpenEngine most recently, a lot of what I'm doing is basically building pieces of a harness in public so that you have more choices. And I'm not the only one doing it. There are others who are doing it. It's a good work. I'm glad it's widespread. There's a big movement around this. I think it's important that we have choice. We shouldn't have to feel like we're locked in to each other. Any given model provider, we should have the option to retain our context and use intelligence in order to get meaningful work done. And I think the more we look at the story going forward, the more it's a story of the intelligence wars shifting into the context wars. It's going to be less about when does 5.6 come out? And it will eventually, when does Fable come out? And it will eventually. And more about when can we make the next step in applying intelligence so that it's useful? And the story of Siri really shows us, pardon me, Apple, that you don't have to have an incredibly intelligent model to have incredible utility. Like your model doesn't have to max out the benchmarks. That's not what Siri is going to do. But Siri, applied across your context on your phone seamlessly, can still be incredibly utilized. Powerful. So that's the story under the story this week. Pay attention to the context layer. It's going to matter a lot. And if you want more stories under the story, I do them every week. Subscribe for more.