From a couple hours of usage in the CLI, 5.2-codex seems to burn through my plan's limit noticeably faster than 5.1-codex. So I guess the usage limit is a set dollar amount of API credits under the hood.
The way you get structured output with Claude prior to this is via tool use.
IMO this was the more elegant design if you think about it: tool calling is really just structured output and structured output is tool calling. The "do not provide multiple ways of doing the same thing" philosophy.
Anecdotally, a Max subscriber gets something like $100 worth of usage per day. The more people use Claude Code, the more Anthropic loses, so it sounds like a classical "selling a dollar for 85 cents" business to me.
As soon as users are confronted with their true API cost, the appearance of this being a good business falls apart. At the end of the day, there is no moat around large language models - OpenAI, Anthropic, Google, DeepSeek, Alibaba, Moonshot... any company can make a SOTA model if they wish, so in the long run it's guaranteed to be a race to the bottom where nobody can turn a profit.
> Anecdotally, a Max subscriber gets something like $100 worth of usage per day.
Where are you getting that number from?
Anthropic added quite strict limits on usage - visible from the /usage method inside Claude Code. I would be surprised if those limits turn out to still result in expensive losses for them.
This is just personal experience + reddit anecdotes. I've been using CC from day one (when API pricing was the only way to pay for CC), then I've been on the $20 Pro plan and am getting a solid $5+ worth of usage in each 5h session, times 5-10 sessions per week (so an overall 5-10x subsidy over one month.) And I extrapolated that $200 subscribers must be getting roughly 10x Pro's usage. I do feel the actual limit fluctuates each week as Claude Code engage in this new subsidy war with OAI Codex though.
My theory is this:
- we know from benchmarks that open-weight models like Deepseek R1 and Kimi K2's capabilities are not far behind SOTA GPT/Claude
- open-weight API pricing (e.g. on openrouter) is roughly 1/10~1/5 that of GPT/Claude
- users can more or less choose to hook their agent CLI/IDEs to either closed or open models
If these points are true, then the only reason people are primarily on CC & Codex plans is because they are subsidized by at least 5~10x. When confronted with true costs, users will quickly switch to the lowest inference cost vendor, and we get perfect competition + zero margin for all vendors.
The benchmarks lie. Go try coding full-time with R1 vs Codex or GPT-5 (in Codex). The latter is firmly preferred even by those who have no issue with budgeting tokens for their productivity.
But stripping complex formats like html & pdf down to simple markdown is a hard problem. It's nearly impossible to infer what the rendered page looks like by looking at the raw html / pdf code. https://github.com/mozilla/readability helps but it often breaks down over unconventional div structures. I heard the state of the art solution is using multimodal LLM OCR to really look at the rendered page and rewrite the thing in markdown.
Which makes me wonder: how did OpenAI make their model read pdf, docx and images at all?
I think the OP's point is that all those requirements are to be implemented outside the LLM layer, i.e. we don't need to conceive of any new model architecture. Even if LLMs don't progress any further beyond GPT-5 & Claude 4, we'll still get there.
Take memory for example: give LLM a persistent computer and ask it to jot down its long-term memory as hierarchical directories of markdown documents. Recalling a piece of memory means a bunch of `tree` and `grep` commands. It's very, very rudimentary, but it kinda works, today. We just have to think of incrementally smarter ways to query & maintain this type of memory repo, which is a pure engineering problem.
The answer can't be as simple as more sophisticated RAGs. At the end of the day, stuffing the context full of crap can only take you so far because context is an extremely limited resource. We also know that large context windows degrade in quality because the model has a harder time tracking what the user wants it to pay attention to.
Today’s AI systems probably won’t excel, but they won’t completely fail either.
Basically give the LLM a computer to do all kinds of stuff against the real world, kick it off with a high level goal like “build a startup”.
The key is to instruct it to manage its own memory in its computer, and when context limit inevitably approaches, programmatically interrupt the LLM loop and instruct it to jot down everything it has for its future self.
It already kinda works today, and I believe AI systems a year from now will excel at this:
I wouldn’t worry about job safety when we have such utopian vision as the elimination of all human labor in our sight.
Not only will AI run the company, it will run the world. Remember: a product/service only costs money because somewhere down the assembly line or in some office, there are human workers who need to feed their family. If AI can help gradually reduce human involvement to 0, with good market competition (AI can help with this too - if AI can be capable CEOs, starting your business will be insanely easy,) and we’ll get near absolute abundance. Then humanity will be basically printing any product & service on demand at 0 cost like how we print money today.
I wouldn’t even worry about unequal distribution of wealth, because with absolute abundance, any piece of the pie is an infinitely large pie. Still think the world isn’t perfect in that future? Just one prompt, and the robot army will do whatever it takes to fix it for you.
Sure thing, here's your neural VR interface and extremely high fidelity artificial world with as many paperclips as you want. It even has a hyperbolic space mode if you think there are too few paperclips in your field of view.
Manual labor would still be there. Hardware is way harder than software, AGI seems easier to realize than mass worldwide automation of minute tasks that currently require human hands.
AGI would force back knowledge workers to factories.
My view is AGI will dramatically reduce cost of R&D in general, then developing humanoid robot will be an easy task - since it's all AI systems who will be doing the development.
A very cynic approach is why spend time and capital on robot R&D when you already have a world filled with self-replicating humanoids and you can feed them whatever information you want through the social networks you control to make them do what you want with a smile.
As long as we have a free market, nobody gets to say, “No, you shouldn’t have robots freeing you from work.”
Individual people will decide what they want to build, with whatever tools they have. If AI tools become powerful enough that one-person companies can build serious products, I bet there will be thousands of those companies taking a swing at the “next big thing” like humanoid robots. It’s a matter of time those problems all get solved.
Individual people have to have access to those AGIs to put them to use (which will likely be controlled first by large companies) and need food to feed themselves (so they'll have to do whatever work they can at whatever price possible in a market where knowledge and intellect is not in demand).
I'd like to believe personal freedoms are preserved in a world with AGI and that a good part of the population will benefit from it, but recent history has been about concentrating power in the hands of the few, and the few getting AGI will free them from having to play nice with knowledge workers.
Though I guess maybe at some points robots might be cheaper than humans without worker rights, which would warrant investment even when thinking cynically.
Yes, number-wise the wealth gap between the top and median is bigger than ever, but the actual quality-of-life difference has never been smaller — Elon and I probably both use an iPhone, wear similar T-shirts, mostly eat the same kind of food, get our information & entertainment from Google/ChatGPT/Youtube/X.
I fully expect the distribution to be even more extreme in an ultra-productive AI future, yet nonetheless, the bottom 50% would have their every need met in the same manner that Elon has his. If you ever want anything or have something more ambitious in mind, say, start a company to build something no one’s thought of — you’d just call a robot to do it. And because the robots are themselves developed and maintained by an all-robot company, it costs nobody anything to provide this AGI robot service to everyone.
A Google-like information query would have been unimaginably costly to execute a hundred years ago, and here we are, it’s totally free because running Google is so automated. Rich people don't even get a better Google just because they are willing to pay - everybody gets the best stuff when the best stuff costs 0 anyway.
AI services are widely available, and humans have agency. If my boss can outsource everything to AI and run a one-person company, soon everyone will be running their own one-person companies to compete. If OpenAI refuses to sell me AI, I’ll turn to Anthropic, DeepSeek, etc.
AI is raising individual capability to a level that once required a full team. I believe it’s fundamentally a democratizing force rather than monopolizing. Everybody will try and get the most value out of AI, nobody holds the power to decide whether to share or not.
There's at least as much reason to believe the opposite. Much of today's obesity has been created by desk jobs and food deserts. Both of those things could be reversed.
> When it’s able to create code that compiles, the code is invariably inefficient and ugly.
At the end of the day this is a trivial problem. When Claude Code finishes a commit, just spin up another Claude Code instance and say "run a git diff, find and fix inefficient and ugly code, and make sure it still compiles."
If payments are always approved by the payer with their PIN / FaceID, then the idea of a fraudulent charge is just undefined.
Like you hand cash to someone. The transaction is done at the moment money changes hand. You don't get to call someone to snatch the money back to you against the payee's will.
For online purchase, for example, buyer pays the marketplace (e.g. taobao.com) to temporarily hold the money -> seller ships the goods -> buyer confirms goods are received -> marketplace pays seller. If there is a question, you take it to the marketplace to sort things out according to marketplace & seller policy. Either way, the payment provider doesn't concern itself with any of this - it only routes money according to payer's request.
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