I know a lot of people at companies where the marching orders changed on a dime end of Q1/start of Q2. These are shops that were fully on the "use AI or die (because we will fire you)" train.
Now there's monitoring, reporting, alerting not just on overall cost but on "over-use" of best/priciest models based on total-or-percent tokens/dollars, etc. All of this comes with direct developer engagement & standardized management escalation for holding it wrong.
To me this customer behavior does not smell like a product you can 10x the pricing on to get profitable. We have exited the exploration phase and now ROI matters.
Sure, you can use AI to potentially replace software engineers, but the F500 are also terrified of not having accountability or making mistakes. They won't be firing any engineers. In that scenario, there's just no room for AI usage. If you have to be responsible for all the code, then... AI has to either manage it completely autonomously (which even Fable can't) or... humans have to be in the loop which means they still have to understand the code. The best way to understand the code is to write the code yourself. So there's no productivity gain to be had.
I'm pro-AI, but I think we're due for a big crash next year.
Neither Anthropic nor OpenAI are subsidizing enterprise customers. Neither Anthropic nor OpenAI allow Business nor Enterprise customers access to the high value $200/mo plan. Both organizations have moved to a "cheaper plan per user + API Pricing after that" (e.g. $20/mo + usage). The $100/$200/mo plans are for individuals only (of course, many individuals use these plans at work, but that's beside the point; they aren't selling this plan to enterprises).
> SemiAnalysis also analyzed the platform's gross margins, implausibly assuming that tokens were priced at 4 times the cost of generating them and: With the current subsidies, all it takes for a user to have a gross margin of at best negative 25% is for them to use as little as 25% of their rate limit.
The article's source for this claim is not SemiAnalysis; its Zitron. But once you dig through his article, Zitron links to a SemiAnalysis tweet [1] where they, as the paragraph states, implausibly assume gross margins of 75% to come up with their weird analysis of the subscription plans. Citing this for anything is weird, because afaik that 75% number is a total shot in the dark. We have no clue what their margins are. My take is that the only reason that 75% number is implausible is because it may underestimate the inference margins of Ant/OAI's API pricing.
[1] https://x.com/SemiAnalysis_/status/2064815045767213400?ref=w...
Chinese models and open model providers are, indeed, competing on price, and the difference shows.
The drug dealer analogy has a darker side to it, however.
Once your dependent, they can drive up the price just because. It doesn't need to be for existential reasons.
There are ~1.6M software engineers on the US [0], earning a bit under 150k/year on average [1]. If AI companies captured all of that spend, that amounts to about 250B/year. The article assumed that they need around 300B/year to keep up with their debt.
At least based on Meta's recent behavior, forcing 30-50% of developers to switch to data labeling, it looks like that is actually their game plan.
[0] https://en.wikipedia.org/wiki/Software_engineering_demograph...
[1] https://www.indeed.com/career/software-engineer/salaries
So we are going to go through a big IPO period. Everything will fall apart because VCs already extracted the growth value, and that will show up after the bag has been passed. Things will implode. What survives afterwards is what we will have.
Anyone know what they are spending this on? Can't remember seeing one OpenAI ad.. Is it just pr and influencers? Ads in the US?
Consider Google, Apple, Amazon, etc.
It's still early days...
The only moat OpenAI and Anthropic have is regulation. If the Chinese really eant to hammer us, they could realse the full training data and pipeline.
If you think search ads are annoying, pre-roll YouTube ads are annoying, streaming ads are annoying, or basically ads-on-any-screen-anywhere-at-any-time are annoying, just wait until every stupid thing is powered by AI and is subtly trying to manipulate you to buy/watch/believe some crap all the time.
I used in a day or two the limit that would last me a month. Downgrading from Sonnet to Gemini Flash was the only way to keep the limit longer, and who knows when cheaper models will be discontinued for something more expensive.
I don’t know if the prices will remain low, but at least Chinese models being open make them have no control over when it is discontinued, I think learning to work with open models is a good direction, even if not running it on your own hardware.
Appears that Chat will remain cheap as it can be supported by Ads revenue, coding tools will go up in price post IPO as less able to squeeze ads in?
>“We are clearly in the advertising business now,”
https://www.adexchanger.com/ai/at-its-first-ever-cannes-open...
After this it will be hardware optimizations and tooling specializations (having different models for different tasks) and running the whole model might not be too expensive anymore. Will they be outcompeted by cheaper Chinese competitors or open models? Possibly.
I hope we reach the point I can run the whole darn thing on a old laptop.
might as well be the other way around with non subscribed token being 50x overpriced, or any combination thereof
also uber was non profitable for the longest time, raking up 31b in losses, on the bet of capturing the market worldwide. scale here is different, but it's also 10 years later, with a lot more volatility and floating cash in the market (voo grew 327% over that period, not unreasonable that round size grew on the same trajectory)
What makes AI so convenient is how good it is at doing red-team code reviews on my work. I used to need all this unnecessary communication just to get a review, but now I only have to reach out to the people I actually want to talk to.
Frontier models may eventually achieve super-intelligence (no opinion beyond mild skepticism) but super-intelligence isn't necessary for most practical day-to-day programming. The problems, as always, become communication, understanding what users really need, etc. that is, softer skills.
You don't price based on cost, you price based on willingness-to-pay.
So maybe labs are "overcharging" enterprises on interference (because, up til now, enterprises have seemingly had unlimited budget for tokens) and "undercharging" individuals and SMBs (because they don't have an unlimited budget).
This is going to be the new most misquoted/misunderstood data of the year, isn't it? The cost is mostly from a one-time accounting situation due to their pivot from a non-profit organization.[0] If we trust the leak [1] OpenAI is likely turning profitable this year.
[0]: $30Bn of it is the one-time cost. https://www.ft.com/content/e15b0d7e-ff6b-4f16-ba7a-4068feddb...
[1]: I suspect OpenAI itself leaked that financial report. It's almost unbelievably healthy.
I was able to enjoy the subsidy from these AI companies to build some projects quickly. Even my wife (non-techie) is able to get a lot of data analysis and processing done once I taught her how to use Codex. We'll just keep enjoying it while it lasts.
The companies that did not yet jump on this bandwagon and are still evaluating will have a decision to make.
No matter what the AI companies are going to change their pricing strategy and it’s going to become a lot lot more expensive to use. I am just hoping the price stays like this until I am done with my big chunk of work
That is worth a small multiple of the fully-loaded employee cost. So AI might be easily worth more than $200 per human-equivalent hour. With high utilization, that might be $8000-10000 a month.
With that kind of spend, AI provider financials looks less frightening.
[1]: And this too is incorrect, should be " the number of jobs displaced would be around 32.5M" (the post says 32.5K)
The conversation in a lot of wealth management offices has shifted dramatically in the last few month from “how do I get in on this AI thing?” to “how do I protect my assets when this AI stuff blows up.”
There’s little question now if this will all implode, just when and who’s going to lose their shirt and be left without chairs when the music stops.
What’s playing out now is the scene from The Big Short where the banks wouldn’t mark down the value of bonds until they secured a short position. Once the big money has their helmets on it will stop providing fuel for the bubble and then look out below!
Edit to add: Just use Deepseek Flash 4. You can hit those servers all day for next to nothing and still scratch the itch to build useless things. ;)
> [Ratio of per-token cost to subscription cost] means Anthropic is subsidizing their enterprise customers by up to 40 times, and OpenAI up to 70 times
Actually, they could be subsidizing by more (if they are taking a loss on API), or not at all (if they are soaking API customers by a massive margin).
Separately, these subscriptions get sold to large groups with varying usage, so it's crazy to model assuming every subscription is maxed out. Banks, gyms, and many other businesses work this way, offering consumers flexible access to services that they will realistically use in bursts. It's not always worth the complexity to prevent overuse by a small minority. You can feel like this kind of business model isn't as transparent, but it's silly to pretend it can't work.
> OpenAI spent 44% of their revenue [$5.3B] on sales and marketing! The hype needed to keep the AI bubble inflated is incredibly expensive.
Over that same period (2025), OpenAI added $10B in realized revenue and $14B in run-rate. Sounds like they're getting >2X return within 12 months of those go-to-market dollars. Compare that to like, any other business.
> Thus in recent weeks the idea that Generative AI (LLMs for short) is too expensive has been all over mainstream business media.
Would it be smarter for these companies never to test customers' price tolerance? The quotes following this make it seem like the companies are getting important information about the nature of that price tolerance, and preparing to react. This is the work markets do on both sides to understand the value of a new product.
There are lots of good arguments about AI overinflation, but in order for them to be useful, they have to be rigorous and targeted.
Vendor lock-in is the current goal. Consumer prices are a drop in the bucket comparatively.
Lump of labour fallacy spotted.
"a return on these invetment"
It seems like this ideology has been corrupted into a short-sighted "Establish a monopoly position as soon as possible at all costs, don't worry about tomorrow."
It's ironic because monopolizing a sector by investing heavily and suppressing profits used to be a long term move but it seems to have become a short term move as investors are racing each other.
And then remarks like this:
Anthropic, OpenAI and Microsoft have all now transitioned customers from subscriptions to token-based pricing.
Huh? I use OpenAI via a subscription, as is anyone else using GPT-5.5-Pro who isn't a multimillionaire.https://sequoiacap.com/article/follow-the-gpus-perspective/
https://sequoiacap.com/article/ais-600b-question/
https://www.wheresyoured.at/brokenomics/
https://www.wheresyoured.at/exclusive-openai-financials/
https://www.wheresyoured.at/news-microsoft-to-shift-github-c...
https://archive.is/m5MHe#selection-1483.0-1483.74
https://www.youtube.com/watch?v=MNQDrF0HjtI
https://www.youtube.com/watch?v=VBHSjzHW-C8
https://www.derekthompson.org/p/the-great-ai-cost-panic-of-2...
https://www.tomshardware.com/tech-industry/artificial-intell...
https://www.tomshardware.com/tech-industry/artificial-intell...
https://blog.dshr.org/2025/10/depreciation.html
https://x.com/ThierryBorgeat/status/2060069195975422281
https://wlockett.medium.com/the-ai-industry-is-panicking-db5...
https://www.sofi.com/learn/content/average-salary-in-us/
https://www.theglobalstatistics.com/united-states-labor-stat...
https://www.bls.gov/news.release/pdf/ecec.pdf
https://www.businessinsider.com/ai-bubble-heads-doomers-sam-...
https://www.wsj.com/tech/ai/openai-considers-drastic-price-c...
https://www.bloomberg.com/opinion/articles/2026-06-11/anthro...
https://arstechnica.com/ai/2026/06/anthropic-pauses-token-ba...
https://x.com/bcherny/status/2040206441756471399?lang=en
https://code.claude.com/docs/en/agent-sdk/overview
https://windowsforum.com/threads/microsoft-plans-june-30-202...
https://www.datacenterdynamics.com/en/news/anthropic-to-use-...
https://techcrunch.com/2026/06/05/google-will-pay-spacex-920...
https://backofmind.substack.com/p/tokenalysis-and-john-henry
HN commenters quickly attack anything from Ed Zitron these days
But this seems to be flying under the radar