AI Is Getting Way Too Expensive
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The reality is that there is more and more subscriptions available everywhere, and for $400 you can easily get $10K of tokens from Openrouter/official API pricing, you can pile up as many subs as you want and there is virtually no constrain once you make CC an API, you don't need Claude Code, you don't need Codex, you don't need Antigravity, you don't need Kimi Code.
We use now about 20 subscriptions (mixed, around $5K) and we average $60K-100K in token a month, THAT is the price, that's what's debited from our account. There is also many providers that resell tokens for cheaper, why wouldn't that be the price for us consumers?
If that changes in 6 months, so be it, but the current price of AI is that one.
PS: Many enterprises (maybe not large scale) have at least 1-2 subscriptions for each of their employees, so it's not really only startups & consumers.
The amount of money these AI companies are burning is unprecedented and there is simply not enough money in the economy to keep it going at a loss for ten years. Google (Google!) went cash flow negative and is issuing bonds, basically asking for a loan. That's the reason markets are getting so nervous.
And yes, choice is good but how many of these new models are trained from scratch vs distilled from frontier models? If OpenAI and Anthropic go down in flames how much of the cheaper choices we see today are going to keep evolving? I am not trying to make a prediction either way, I am just pointing out the uncertainty. Which, again, is fine if AI is a commodity you can easily cut, but not great if your company is betting big on AI.
If all the research went away tomorrow, people are still going to sell inference at current prices or higher. There are already open weights competitive with proprietary models. There will be no lost capability.
If businesses find inference useful today then it doesn't have to drastically improve in a short timeframe anymore. History is full of inventions which became "good enough" and didn't improve much or at all for a long time.
eg: Western society runs on radial tyres which have seen only marginal improvements for the last 50 years.
(yes there have been some small improvements in compounds, tread patterns, TPMS, etc. hardly drastic revolutionary changes to the tyre industry)
It's been stated by the AI companies, which are known to routinely lie to our faces, and have a vested financial interest in making people believe they will be able to turn a profit at current prices. In other words, it's one of the most unbelievable claims out there, and you shouldn't believe it for a second.
The difference with tyres is that If today's LLMs had been invented and had become "good enough" 50 years ago, you would have a cutover in their knowledge that excludes 50 years of information. Every "write me a program in Rust" conversation would involve LLMs filling up their context trying to learn Rust programming from scratch every time and probably doing a very bad job.
An example of that was when Fable disproved that mathematical conjecture and HN was full of other people who fed that information to other models (or Fable itself) and received incredulous answers from their LLMs. If something is proven true or false in math, the world of science moves on and that new piece of information can be used to build, prove or disprove other things. But an LLM is excluded from learning even from the very thing it just helped demonstrate and needs to re-discover it over and over again. In order to have an LLM that "lives" in a world where the Jacobian conjecture is false, you need to train a new model and add that information.
So in a way your argument that users are able to spend 10k in tokens while paying a sub of 200 is actually agreeing with his point.
They can also leverage their own tech to crush most businesses in an automated way if they wanted/needed to in the future. Let's be real, a good 90% of all existing techs company could be replaced and automated entirely with the right approach and unli-tokens.
I would recommend to watch the documentary „Enron: The Smartest Guys in the Room“.