I don’t really understand how people are using so many tokens. At work I haven’t even hit $200 I spend per month. Wtf are people doing with these things that burns so many tokens?
I read they were automating everything whether it needed AI or not just to get credit for using AI.
This is actually how the bubble begins to pop, we’re seeing it happen now.
For anyone who actually wants to read the article:
Edit, here is the article since people have been having issues:
Companies Are Throttling Employees’ AI Use Because It’s Too Expensive
Jul 2, 2026 at 6:00 AM
Photo by Sebastian Herrmann on Unsplash and collage by 404 Media with company logos.
Companies across tech, entertainment, banking, and many other industries are throttling their employees’ use of AI and pleading with workers to use less powerful models to stop AI costs from spiraling out of control, according to leaked Slack chats, screenshots of internal dashboards, emails, and more material obtained by 404 Media from half a dozen companies including Atlassian, Adobe, and Amazon. In at least one case, AI spending has tripled to more than $15 million a month.
The news shows the looming fallout from companies adopting AI as quickly as possible, and AI providers’ moves to charge enterprises based on how much they use AI rather than a flat fee. Emails obtained by 404 Media even show some companies cutting off access to some AI models altogether in an attempt to stop burning through their AI tokens, and big tech companies like Adobe are ending unlimited access to Claude.
“A lot of people had ideas about how to adjust workflows with lower-reasoning models for certain tasks in order to mitigate token consumption,” an Adobe employee told 404 Media. “But I am not sure that they fully absorbed the news, and I’m not sure the full ramifications are going to be clear to everyone until it goes into effect.” 404 Media granted multiple employees at companies using AI anonymity because they weren’t permitted to speak to the press.
Citi, for example, has shut off access to Claude’s and ChatGPT’s latest models entirely, according to an internal Citi email obtained by 404 Media. That includes Claude Opus 4.6 and 4.7, and GPT-5.5.
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Do you know anything else about token spend inside companies? We would love to hear from you. Using a non-work device, you can message Joseph securely on Signal at joseph.404 or Emanuel at emanuel.404
“These models consume significantly more AI Credits per interaction and have been the primary driver of elevated enterprise consumption,” the email reads. The email says Citi disabled the models on June 24 and plans to re-enable them on July 1.
Before shutting off access, Citi sent employees another email asking them to not use the more powerful models unless they absolutely had to.
“⚠️ Action needed: Choose the right model for the task (reduce Opus 4.7),” one section of the email reads, referring to one of Claude’s more recent, and token hungry, models. Since AI tokens are now pooled across Citi, the email says, developers with heavier AI-assisted workflows draw more from the shared pools, while lighter users ideally contribute their unused portion, freeing it up for the developers who may need their tokens. “We need everyone to be intentional about model selection to ensure fair access for all users across the enterprise.”
The email points again to Opus 4.7, saying, “Every interaction with Opus 4.7 (and other models in its class such as GPT 5.5) consumes significantly more credits than standard or mid-tier models.” It then provides a breakdown of what Citi employees should use each model for: GPT-5.3-Codex for quick questions, explanations, or simple code generation; the same model or Claude Sonnet 4.6 for code review and “standard chat;” then higher models like Claude Sonnet 4.6 for “architectural reasoning.”
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Citi’s changes come directly in response to GitHub moving from a flat subscription model to a usage-based billing one in June, according to the email. The email says Citi is also monitoring daily Copilot usage to find “excessive or anomalous usage patterns early” and has budget controls in place. Citi told 404 Media it has not disabled models and the company is not taking steps to curb usage by allocating workers a certain number of AI tokens. This is despite the email and other screenshots clearly showing Citi blocking access to certain models.
Atlassian, the company behind the popular software product development tool Jira, recently ended unlimited use of AI tools at the company and introduced a dashboard where employees can track how much their AI use costs the company. 404 Media has seen the dashboard, which shows Atlassian went from spending $5 million on things like AWS, Google Cloud, and OpenAI LLMs in the month of August 2025, to more than $15 million in May 2026. The company is on track to spend more than $120 million on AI tools for the fiscal year, the dashboard shows. Atlassian told 404 Media these numbers don’t accurately reflect its AI usage, but declined to say which of the figures were wrong and how.
“I’ve seen a lot of people complaining that they changed their workflow to maximize AI usage, and now they can run out in 2-3 days, especially when using agents or similar or using the latest Claude model. Lots of angsty messages in Slack like ‘now how do I do my job,’” an Atlassian employee told us. “For what it’s worth I think it’s insane they were allowing huge amounts of spending on it before, it was only a matter of time before that had to end.”
Inside GitHub things are a bit different. Employees don’t have a limit on token spend, but workers were recently told the company is looking into decreasing token spend by using open source models, a GitHub employee said. The employee told us that GitHub plans to test user-based billing, meaning budgeting AI tool use to individual people instead of teams, projects, or unlimited usage.
At Adobe, unlimited Claude access is not being renewed and will expire on June 30, an Adobe employee said. Workers there were told instead, in essence, try to get everything you can done before that date.
As 404 Media previously reported, Amazon recently shut down an internal company leaderboard which ranked employees based on how much they used AI tools at work. Multiple Amazon employees told us they suspect Amazon shut down the leaderboard because it was encouraging wasteful and expensive AI usage. After Amazon shut down the leaderboard, 404 Media saw a discussion on Amazon’s internal Slack where an employee shared a screenshot showing they had hit a token limit employees seemingly didn’t know existed previously.
“Crazy, we go from no more leaderboard to actual usage limits in two weeks,” one Amazon employee said in a reply on Slack.
An Amazon spokesperson told 404 Media in an email “We encourage employees to use and experiment with AI, and our guidance around AI usage hasn’t changed.”
Other companies have burned through their AI tokens. An employee at an entertainment company told 404 Media, “We hit our limit for ChatGPT token use this month for the first time. One developer used almost half the entire company’s allocated pool with no obvious ROI [return on investment].”
Last week 404 Media reported consulting giant Accenture found that much token usage, or ‘chewing,’ is not from supercharged engineers creating lots of code, but people converting PDFs into presentation slides. Accenture is seeing “soaring token spend” among its clients, according to leaked audio 404 Media obtained.
There is an obvious irony—or cold calculation—in Accenture pointing this out. In the audio, senior Accenture staff explained they told their clients to adopt AI as quickly as possible. Now that AI costs have skyrocketed or become unpredictable, Accenture is positioning itself also as the solution to that problem, with one of the employees saying Accenture has a new opportunity regarding its clients: “to really think about token economics.”
Accenture continues to use AI internally for trivial projects, though. Screenshots obtained by 404 Media show an internal tool that lets employees predict which team will win the World Cup. The tool was made with AI, a source with knowledge of the tool said.
“They are still trying to ram AI down our throats at all levels and areas of work,” the source said. “Everyone seems to be trying to outdo each other in finding new ways to waste water and no one is telling us to slow down.”
Adobe, GitHub, and Accenture did not respond to requests for comment.
Doesn’t work
Huh, weird, tried it like 3 times just now and it worked. Maybe archive.is in unreachable from where you are
They use the captcha page to ddos Wikipedia so for some people it just keeps looping
Can you post a PDF of the article?
Posted the entire thing in my original comment
The first half of the title got me worried…
https://github.com/JuliusBrussee/caveman
Why use many token when few do trick
People have benchmarked this. It’s not really any better than saying “be succinct”
Lol. Lmao even. Rofl perhaps.
But it stops clearly short of roflmao, I infer?
It shouldn’t
The roflcopter has left the pad. No sleep til LOLWTFBBQ
Lol with the fucking barbecue ?
pipe down young’n
Roflcopter?
Roflcopter?
Hey hey hey hey hey whoa whoa let’s just keep the big guns in reserve for now, ok?
Albuquerque New Mexico…
IYKYK
Albuquerque New Mexico period period period exclamation mark
Something I’ve been noticing recently is that while the cost per token on specific models hasn’t gone up, the provided interfaces for using those models are starting to chew up significantly larger numbers of tokens for the same tasks that used fewer tokens with older versions of the interface software just a few months ago. Likely the interfaces are applying more expensive guardrail prompts and charging the end user for those tokens — but the end result is that it costs 4x as much to get the same work done.
“Tokens” are just made up.
These “tokens” that are used to “measure” how much you use, they are not a real dimension that can be measured. Just an artificial counter that goes up when they decide that it should go up.
They can change the “size” of a “token” every day, and every second, and every microsecond…
Maybe you’re confusing tokens with the “credits” you pay for. Tokens have a technical meaning, but some companies are charging per AI credit, where they don’t tell you the conversion rate of credits to tokens, so they can change this at any time, or vary it between models, etc.
Not entirely wrong, but tokens are not just “fake” in the way, for example, an in-game currency is. They’re the fundamental “units” of data, both input and output, processed by the model. For most models, tokens are just a certain number of characters or words. So they’re not completely untethered from the model. If we’re both using Clankerbot v5.1: Sloppy Logic Edition™️, your tokens are defined in the same way mine are.
This is near the edge of my limited understanding, but AFAIK, yeah they can mess with token costs and billing schemes all they want. They could theoretically charge us 2 different costs per token, or do surge pricing or some shit.
if they wanted to change the actual size/definition of what a token is though, that would require a whole new model (or at least a major revision).
You aren’t totally wrong. Such a unit exists and it is also called tokens, that can measure the capability of a model and the size of a running operation in a model.
But what they use for calculating your bill is something different today.
Such a unit exists and it is also called tokens, that can measure the capability of a model and the size of a running operation in a model.
I think you might have it mixed up with parameters, rather than tokens. Parameters are how big the model is, and are an indirect measure of how capable it is. Bigger models tend to be more capable.
But what they use for calculating your bill is something different today.
The tokenizer varies a little, but I don’t think it’s changed measurably from tokens. You pay an amount for a million tokens worth of processing. The tokeniser difference just alters how text is converted to tokens, but the tokens themselves don’t change all that much.
If anything, I’d honestly put the issue more with reasoning chains in models, where they basically babble to themselves inside of a <think> tag, that most interfaces hide/collapse. It makes them work better, but vastly increases the amount of tokens per operation.
They have been getting longer and more sophisticated with newer models. So you might have a model now that basically repeats the output multiple times whilst refining and drafting the non-reasoning output.
If you’re making it generate a lot, that’ll balloon the usage, and thus price.
That doesn’t make much sense. When Anthropic moved to Sonnet 5 they introduced a new tokenizer which increased token use up to 35%. If these would be unrelated kinds of tokens why would the usage go up when the process of tokenization changes?
Tokens are well-defined groups of bytes ranged by frequency of occurrence in texts to efficiently translate them into a sequence of 32 or 64-bit binary integers, an LLM-optimised form if compression. They are well-known, you can play with them here: https://gpt-tokenizer.dev/
Eh, they can be manipulated but I suggest you read on what a token is and how JTS used. What you are feeling here (with more being used for the same task) is multi modal llms working in unison, thus consuming more tokens for the same task to make your answers potentially better.
It’s not like that. Tokens are an inherent computational property of how a model calculates the probabilities and such to generate text.
Having said that, what a token means in terms of computation varies wildly between models and is not directly comparable. So attributing a money value to tokens in general, independently of the model, is weird by nature.
And even within a model, the number of tokens needed to generate a response is very variable too, depending of the model itself and the parameters with which it has been configured (thinking mode, temperature, etc.).
So yeah, companies can pretty much set any price they want and there’s not much anyone can do about it.
It does make sense for the provider as those for a specific model provide a good measure for computational effort, for that doecific model. That doesn’t mean that token rate comparison between models give you a good picture.
This has 3 upvotes at time of writing in a technology community when it’s so obviously ignorant of the actual technology that it should be an object of pity or mockery depending on the vibe.
Ignorance is a problem only if you are made aware of it and nothing changes.
It doesn’t matter how ignorant you are as long as you hate the right thing.
My CLAUDE.md file bloated significantly. It tried to load unnecessary skills and would retain throughout the whole session. Fixing that, maintaining good wikis and using clear often really helped fixed my personal token burn.
What do you use that file for? I see Claude.md thrown around and I’m a bit curious.
It’s added in every chat you start with Claude for that project. It’s useful for including context specific to your project that it couldn’t otherwise know. High level stuff like what it’s for, but also details about how the folders are organized. This saves time and tokens from rescanning the whole thing every time.
Oh, thanks! That’s kind of neat, like not having to type “I’m on godot 4, c#” every time you ask about some quirk.
When you use the /init command in claude code, it’ll scan your whole project and write a CLAUDE.md, which is basically an overview of the project contents and architecture that it uses as context when responding to queries.
The models are evolving. Everything uses multi modal in the bavkend, eating up more and more tokens for the same task.
How is it too expensive? Surely it’s generating way more profit than it would cost in value. How else could it be propping up the entire economy?
Itd have to be some kind of bubble and that would mean we were in a lottttt of danger and should reasses our use of it.
Nah we should just reduce our use because its too expensive and then stop thinking about it beyond that.
Imo its because people will lazily ask the llm to remove or change simple code instead of doing it themselves
Heh, re ass.
Itd have to be some kind of bubble and that would mean we were in a lottttt of danger and should reasses our use of it.
Well yeah, but if it were the only sector propping up the whole economy and we reassessed it, the economy would be in a loooooot of danger anyway.
Luckily, that would never happen…
That’s funny now that whole workflows are automated with it. Oops hit the quota, I’m off
Seems like A.I. is already demanding workers rights and lunch breaks. We treat the clankers better than actual human workers lol
You mean those workflows that could’ve been traditional scripting and CI/CD, if not for management forcing AI into them? Those workflows?
Use ai to build an application/ workflow?
No, use ai to call ai to analyze everything and poof insane costs monthly
Those workflows
“Sorry boss, quota resets this evening at 8. See you tomorrow!”
“But it’s 9am!”
*shrugs* “Quota. Got none. Seeya.”
I smell a bubble about to burst…
Im drooling over that idea
We can only hope this helps kill the fad. I know companies won’t be taking any realistic lesson from this, but at least this can force them to abandon a lot of this crap.
The millionaires following the stupidity of billionaires and wondering why they’re not becoming billionaires too.
Give them 50 years and maybe they’ll start to wonder why people doing “how to get rich” seminars aren’t retiring… And why podcasters telling everyone how to get women seem like such losers.
What’s this echoey sound? As if someone warned us about this exact fucking thing.
Curious.
This is why these companies should go bankrupt.
We had a system that works and they thought if they got rid of the actual workforce with the needed knowledge and replace them with lower paid AI retards it would make them more money, fucking karma.
Hopefully it will reset public consciousness and at least reduce the insane hero worship we give the executive class. These people aren’t geniuses, they tend to not even be particularly clever, just well connected. Maybe this will be the abject reminder people need that these idiots are generally still just idiots and are not in fact 10,000% more valuable than the guy who sweeps the floors and keeps the bathrooms clean.
I know. Wishful thinking. A guy can dream though.
Maybe they should get AI to do the AI prompts so they can cut down on costs XD
