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This is deeply vile behavior; not remotely the actions of good people.

I have consumed a decent amount of literature coming out of WWDC and I do not understand how the billing and model availability side of things will work.

Its definitely the case that Apple said that some AI capabilities will rely on cloud hosted models; and that some of these capabilities will be metered; and that "some paid iCloud+ plans" include increased usage. Its unclear what the full extent of capabilities that rely on cloud models are. We know that Spatial Reframing is a capability that relies on cloud models and will be metered; this was stated on-stage. The typical conversations with Siri are, supposedly, a mix, possibly based on how complex the query is? We know there are two cloud-hosted models (what they call internally "Cloud" and "Cloud Pro"); are both of these metered? Does it depend on the use-case (e.g. is Spatial Reframing metered because of its use-case or because of which model it uses?)

A lot of this would be easier to figure out if there was, somewhere, a "meter" you could see drop every time you used a metered feature; but there isn't. There is zero indication of metered AI usage anywhere in the settings that I have found (I am on the 27 dev beta). There is also zero indication that any of the iCloud+ plans include metered AI usage. It is also of note that Apple very specifically said on-stage that "some iCloud+ plans" include increased usage; implying that the $2.99/mo plan likely does not.

Apple has also announced that developers under a certain revenue number can use their foundation models in private cloud compute for free [1]. This implies: third party developers will pay for it. In other words: it might be the case that your shared iCloud+ pool of AI usage only applies to AI capabilities from first-party Apple apps, while in third-party apps the developers are expected to front the bill. Which further reinforces your point: Why would anyone choose to integrate with these cloud models?

Strange situation, and unlike Apple; they seem very frantic.

[1] https://techcrunch.com/2026/06/08/apple-bets-cheaper-ai-will...

IMO there's an even more real story at the heart of this idea than stratechery's predictable, banal attempt to compare Microsoft and Apple's competing visions of the future, and its part of why I've become so bored of stratechery's articles lately. He glances against that Microsoft video, recognizes that the video does a horrible job of communicating their vision, and then carries water for Microsoft by working overtime clarifying their vision for them; instead of doing the obvious and totally reasonable thing of asking: Why the fuck is that video so incomprehensible? Microsoft used to be pretty good at aligning themselves and their customers around a shared vision of their future, but since the advent of AI the company has seemed more-and-more adrift at sea without a bearing.

Much more needs to be said and discussed about this; in comparison, Siri AI is boring and predictable. Siri AI is Apple being Classic Apple: shipping a solid, decent product that works as advertised and isn't that surprising. That's Apple. They lost their bearing as well for a couple years, but they re-found it. Good on them. Meanwhile Microsoft is in meltdown mode behind them shrieking buzzwords and everyone is pretending that everything is fine because they're microsoft, they'll figure it out.

You cannot trust companies to communicate an unbiased vision of the future, because they will always build what they're capable of selling. Microsoft and Meta are incapable of selling phones and laptops; they're certainly capable of building them, but few people will buy them. So instead Meta builds smart-glasses and Microsoft presents this weird vision of "connected thin devices" by keeping the hardware itself very abstract and unknowable. The hardware doesn't matter to Microsoft, not because the hardware doesn't actually matter, but because it cannot matter, because Microsoft cannot win in hardware. Its not a vision of the future; its a vision of what Microsoft can meaningfully sell. Microsoft can meaningfully sell their weird constellation of 365 subscriptions that no one knows what they do or if they remotely do what you buy them for; thus their marketing now wears that idea of "unknowable capability" like a mask.

I literally never made any comments or aspersions on the quality of US graduates relative to other countries; just the quality of graduates relative to the quality of graduates from the same university ten years prior, or at least employers' perceived quality of these candidates.

> We stopped building new housing

The current rate of new build construction is the highest it has been since 2007, ignoring the spike during late COVID-era zero interest rates. Also: US population is growing slower than anytime in modern history, again excluding COVID (though, a few more years and we'll be down at that level again all naturally).

[1] https://fred.stlouisfed.org/series/HOUST?utm_source=chatgpt....

[2] https://www.worldometers.info/world-population/us-population...

> without Chinese construction powress

We need to be honest in calling this what it is: yes the Chinese have incredible construction capacity, but the far bigger reason why their cities are growing so fast is because: they essentially have zero personal or corporate property rights in urban zones.

Broadly, every company is on their own journey and makes their own discoveries in their own time, but Yes. I work with a swath of large employers in the midwest, workforce and economic development stuff, and there's a growing feeling among hiring managers that, the best way to put it is: the people they're interviewing out of college are, on the net, less equipped to succeed in the roles they're posting than their expectations on what level of capability college graduates should be at.

This doesn't mean there aren't great candidates.

This could be less on the individual and more on: colleges are getting worse at instruction/preparation (I'm bullish on this explanation among my colleagues; colleges never adapted to computers, let alone AI, the impacts of this just took a decade or so to shake out, which you should expect given the 16 year latency on education most students undergo) (though, again, ultimately its very complicated. multiple factors at play.)

For a lot of these companies this is all surfacing as: They're posting fewer entry level positions than they normally would (oftentimes not zero; just fewer), and if they have money in the budget available due to that, its going into AI.

Companies have never cared about security, because there are almost no consequences to data breaches. A hospital network could get ransomwared for 48 hours, and no one cares. Critical data gets leaked? So what, pay a fine. You either pay a fine to the hackers, or you pay a fine to the government, or you pay a fine to customers, but no matter what its substantially less than a fully staffed security team, not just because security professionals are expensive, but because security professionals slow everything else down, they'll spend all day telling everyone what they can't do, which == lost revenue growth.

The only thing keeping security companies in the business is compliance/certification. If you've been around these compliance programs for long enough you know: they're box-checkers. But, sometimes you need to check that box, begrudgingly, annoyingly, so most companies will prefer to just outsource that security work to some managed security services provider, then think about it once a year when audit time comes around.

I would postulate that there are two reasons why this is happening.

1. Pessimistic, harsh, etc: the quality of US graduates has been falling. Reading comprehension has been on a downward trend over the past decade. Mental illness, depression, and attention disorders are on the rise. Grade inflation, social media, AI availability, we spent years talking about how all of these things would be bad, and now the experimental cohort of kids growing up in this world are graduating and can't find jobs; maybe its not a coincidence.

2. AI automates processes. It doesn't just "do stuff" broadly speaking. AI has increased the leverage that process experts bring to the table: Doing 100x more of the right thing is infinitely more valuable than 100x more of the wrong thing, and with AI proliferating at the rate it is, the differentiator actually isn't in the 100x; its in the driver. Companies need senior talent; its like low-background steel.

I doubt we will see reversal on this in the near term. If anything I expect the "unemployment in their field" chart for every seniority bucket to continue up-and-to-the-right, just lagging behind new grads. But, whether that surfaces in general unemployment remains to be seen: Generally, I think the value of a college education is just going to drop.

Like, legitimately: AI automates college for 85% of college graduates and degrees. The true benefit of college was always immaterial and unrelated to the degree you got; it was in the liberal arts, unfurling your wings, making social connections, just stressing your brain out, hard, for four years to build neuroplasticity, that was always the point. But at some point along the way college became about the little piece of paper they gave out at the end and the words it said on it. All of our capitalistic forces beat college into "the optimal pipeline for that degree"; kill liberal arts, online classes, screw social connection, grade inflation, maximize enrollment, make it easy. Great. And then AI comes along and makes that one thing we optimized everything around pointless.

I'm very much a "it'll all work out in the end" kind of guy, and I think in this case: the societal benefits of a college degree being available for $25/million tokens will far outweigh the societal costs. But we're doing a very bad job of managing those costs, and the first thing we need to be realistic with on this cost management is: about half as many people who currently attend college should actually be there.

How do you know your skills aren't marketable if you don't go out and market them? Go apply around. You don't necessarily need to leave to do it.

Didn’t the UK not six years ago vote to leave the EU? Is he suggesting that there’s demand from Britain to reverse that? Or is he suggesting they be forced to rejoin?

This week an S&P 20 company with previously unlimited Claude limits also set a $250/mo/person limit; though its unclear to me how widely the limits are being enforced, may be the case that its just non-software engineers. Do with this info what you will.

Cringe

I believe the correct way to interpret AISI’s findings is that both Mythos and 5.5-Cyber are capable of solving their full benchmark (the only two models that can); Mythos does it with fewer tokens and more consistently.

Two things of note: 5.5-Cyber is likely to be substantially cheaper than Mythos, given it is priced around Opus. Additionally: AISI has never tested OpenAI’s best public model and actual Mythos competitor: 5.5-Pro.

GPT-5.5-Cyber has already at least hit if not surpassed Mythos capability in cyber tasks. The only reason they're holding back is because once its out everyone would realize that its capabilities were a step change in March, but are not anymore, yet it costs significantly more and is much slower.

Though in fairness: Windows on ARM (even ignoring the earlier iteration of it from ~2016) has had a year or two to mature thanks to the Copilot+ PCs. And, this particular chip seems near-identical to the one Nvidia put in the DGX Spark (again, even ignoring earlier ARM CPUs from Nvidia like Tegra in the Nintendo Switch).

Repayment isn't a goal that anyone in the system should reasonably want. Federal debt is not like credit card debt. Debt is a product that the US Government sells. Me, being a big corporation or human, go to the USG and say "I need somewhere to park my money that is safeish from inflation". The USG sells me debt at X.Y% interest. The money now generates safe interest, which means its safeish from inflation. A world where the USG "repays the debt" is a world where this essential product is no longer available.

High levels of debt only signals high demand for this product.

This is super-counterintuitive, but the debt has little to do with the deficit. We could run a surplus and still be in the same level of debt (in fact, this would be a tremendous place to be). We could run a deficit and have no debt (just print money, duh). The decisions that go into column A generally do not impact the decisions our leaders have to make in column B, though there are of course convenient relationships between the two.

The $175T number is unfair because it treats Social Security and Medicare/aid as a liability instead of the service that they are. You might as well say the US is in infinite debt, because we'll always be paying something for our military every year, so infinity years * any dollars = infinite debt.

Also: All of those numbers you use to scare people are way, way off.

jq can 100% be an MCP tool. Remember: Agent tools do not have to involve a network boundary. They can be natively implemented inside the agent harness, and/or they can be provided via a local MCP server. The point of making it a tool is to tightly allowlist what the agent is capable of executing; it can only execute jq, not any shell program, and moreover it isn't allowed to do things like redirection, pipes, etc; all it has at its disposal is `jq (filters) (data)`.

People seem to think that MCP exists to give agents more capability. That could not be further from the truth, which is actually the opposite: MCP exists to take capability away from agents. It exists to control them.

Cursor is functionally "one of the big 4 labs" (SpaceX).

Cursor only supports a single model (Kimi K2.5) not made by the Big 4 labs (OpenAI, Anthropic, Google, xAI). Cursor is actually extremely bad at wide model support.

OpenCode is much better at it.

You’re right that having a shell is the ultimate tool, and an agent with a shell seems to perform better than one without one. But, making shells safe is really damn hard; e.g. in the context of running an agent on behalf of a SaaS customer in your AWS environment. For now some companies are accepting the performance/security tradeoff of disabling the shell and focusing on specialized tools.

Remember: jq can always be a tool (MCP or otherwise). In this way you can allowlist specific CLI programs and give them to the agent via tools. Making python a tool is more difficult; that would have all of the same RCE injection issues that the shell would have.

There are isolation stacks that help make “running an agent with a shell on behalf of a customer in the cloud” possible. It’s just very risky. There’s a thousand attack vectors, and to a very real degree companies that are getting to this point are re-thinking their cloud infrastructure and architecture from first principals.

Yes, in the same way a programming language would be worse off if they focused all of their effort on building an implementation instead of a language specification.

You could literally, deterministically, zero AI, code-gen a CLI from an MCP specification, just like you can with an OpenAPI specification. I'm sure tools exist that do this. So if you want a CLI, there it is.

But the problem with a CLI is that it requires a shell environment, and not everywhere you may want to run an agent should or can have access to a shell. MCP enables the harness to tightly control that access. MCP allows the user to easily allowlist/denylist specific tools, or categorize tools into "ask me every time" versus "don't ask me just do it". Doing any of this with a CLI is really hard because CLIs are all very different; yes, AIs can easily learn how to use them, but that might be exactly what you don't want, hey AI don't issue that aws ec2 delete-instance command ah crap there it goes I wish I could have just denylisted its access to that tool.

The idea that MCP tool definitions take up a certain number of tokens is laughable. That's an implementation detail of the agent harness. MCP is just an API specification. Hell, there's nothing in it that makes it much of any different than OpenAPI, except that its a bit more local-dev focused. There's a thousand things harnesses can and do do to optimize MCP beyond just "spit out the raw MCP output into the context window and pray".

I definitely believe that you can discern differences between Opus 4.6, 4.7, and 4.8. I might also believe that you believe that you can discern improvements between Opus 4.6, 4.7, and 4.8. But conclusively, consistently, scientifically, and blindly discerning improvement is at this point restricted to problem domains that represent a vanishingly small amount of global token usage, like Erdos problems, superhuman evals, and the like. The idea that typical line of business use-cases have seen broad and measurable improvements since even Opus 4.5 but certainly 4.6 is mostly an illusion that confuses improvements in the harness for improvements in the model, as well as confuses "its different" for "its better".

To be clear, again, cannot stress this enough: I am NOT saying that the models have hit a limit. I am saying that the complexity of the problems most businesses throw at them have always had a limit. The models are now so intelligent that we have not, as of yet, adapted our business use-cases to make use of the new levels of intelligence. Maybe we will.

You're not successful until you exit. And, of course, there's always room to be more successful.

I never said they were doomed. Where did you get that idea? I said they aren't ready for this world. That means they screwed up and need to get ready. They let the Mythos hype get to their heads while the world changed beneath them.

We'll have to agree to disagree on that last point. I think that, historically (past ~6 months), "always use the most advanced model" being the norm is really just an artifact of both: The most advanced models oftentimes being the only model that can solve these problems; and: Infinite AI budgets.

Agreed. But we're seeing Cursor (now SpaceX) take these models and add great coding capability on top of them. Frontier model providers should be concerned that Composer 2.5 costs $0.50/$2.50 (versus Opus 4.8 $5/$25). That's why Google prioritized Gemini 3.5 Flash, and talked up how near-frontier it is ($1.50/$9).