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> Be a corporate executive
> Tell your employees to use more AI in their workflows
> Punish employees who don't use enough AI, while rewarding those who use it the most, irrespective of actual outcomes
> Be shocked when your company blows through an absurd amount of tokens in one month

Don't know why bosses are universally this out of touch in literally every single industry
I feel like this is fake company and they are spreading this to cook the books.
If it isn't a fake company I'd be shocked. It's not like there's a whole lot of external accountability in the entire business model.
But if we are to uncritically believe what the AI peddlers told us, that means this mystery company should be reaping $10 billion in additional revenue or quantifiable gains in productivity!
Claude yearns for the mines
There are 12 mentions of the "report" and yet not a single link to the source of any report.
Anecdotally, my job trained every office employee on AI tools back in March, encouraging everyone to think of ways to incorporate the tools into their standard work. As of last week, they're asking us to get prior authorization to use their AI portal as a way to limit requests.
So some Fortune 500s must be feeling the squeeze on AI.
yep. everyone at mine was being praised for creating an agent that turned meetings into JSON and then the JSON into Asana tasks and the Asana tasks into a report and the report into an internal and external email and the email into a slack message and the slack messages and emails into weekly summary.
Burning thousands of credits for what could be replaced by...
listening
I created a PoC to have an event parse an employees emails, summarize them, then check the calendar and recommend meetings and follow up based on context. It ended up working okay, but it was such a waste of time. This was a C Suite employee that requested, who gets a high volume of junk email. Why would you want AI to (initially requested) auto create meetings for you? That sounds like my nightmare. In the end, it never hit prod thankfully, but, the dev work to get to where I did was awful. Developing AI agents is like guessing and checking until you get close enough. Debugging is brutal and the work is extremely uninspiring.
Christ I am only realising now they probably see me asking copilot "why are you so shit" or "Just fuckoff, I'll do it myself". They pay for that.
I was put in a position to start building and deploying copilot agents in our company. I discovered in the first day how unprepared our environment was for anything copilot. The default state when you get licenses and an environment to work in, is the wild west. It's really bad and as is tradition, half cocked and rushed to market. I wrote out pages of notes of things we had to do as a company before even the most simple agents are created for security and governance. I never got the support to implement any changes, so I drug my feet as much as I could on anything I could. For 6 months I successfully never deployed any AI stuff and got out to do full stack dev instead. I created PoC agents, but with hard caveats that none of it was usable in the current state in prod.
Now prices are increasing and our drive to force agentic has softened a little company wide. I like to think that my semi malicious yet justified slow walking saved us a whole shit load of headache and expenses over the next couple of months as the new copilot pricing hits on June 1.
Hi, it’s partly my fault. You’re welcome. Boss said use more AI. Boss’s mistake was asking someone who would actually take him seriously, unlike all the koolaid chugs out there. Made a docker runtime harness that hooks up to Snowflake Cortex Code SDK for inference. Supports defining repeatable LLM tasks, scheduling them, lightly orchestrating them, network controls, saving results, ... It’s got support for custom skills, commands, chain prompting, sessions, … So now I can use Docker to schedule LLM jobs like motherfucking database pipelines. It can mediocrely do shit like research, planning, evaluations, … all defined through YAML configuration files.
Basically, I introduced scalability to the stack. Sweet malicious compliance. We’ll see what happens next, when everyone is actually empowered to use AI like the execs want. My prediction is an about-face.
Edit: sometimes the best way to win a fight is to show the referee that the rules don’t make any fucking sense. Sometimes the referee doesn’t speak English, though, so you have to show them via USD speak. Sometimes they have a hard time hearing too, so you have to let them taste the poison a little. Sometimes they get drunk off that little bit, so you then gotta throw them in the fucking pool and tell them to start swimming.
The 'report' is the first linked axios article, and the headline is just a bullet point in it
https://www.axios.com/2026/05/28/ai-spending-roi-enterprise-costs
An AI consultant tells Axios one of their clients recently spent half a billion dollars in a single month after failing to put usage limits on Claude licenses for employees.
In other news, company says unexpected expenses in its technology segment are driving layoffs and site closures. Company CEO said in an interview with Forbes, "There's no way we could have predicted this challenge. In service to our customers and our shareholders we're right sizing our operations and reevaluating our strategic priorities. We'll continue to focus on creating value while being a leader in our industry and accelerating AI adoption in everything we do."
Ugh that reads like it came from a random business sentence generator
What's funnier is that typically the AI providers lose money on every query their customers make. So, this may have cost some company $500m to Anthropic, but it cost Anthropic a whole lot more than that.
What a brilliant business model.
They make it up in volume.
(Volume being how loudly they shout about how it's going to change the world and dupe more people into investing.)
When you owe Claude half a million, you've got a problem.
When you owe Claude half a billion, Anthropic has a problem
It's probably Amazon. They can absolutely afford it.
Sounds like a good way to move around money real and imagined.
Just to make things clear: API access to most models is charged per input tokens + output tokens. It means that the longer your conversation is, the more you pay for every new answer. Single prompt with no context and 100 tokens of answer is cheap. Single prompt with 100k tokens of context and 100 tokens of answer is NOT cheap.
Extremely long conversations with most expensive top of the line models can absolutely demolish your budget.
The more recent report says corporate AI adoption has found several issues with AI, with human workers turning to automating dreary and mundane tasks they don't like doing, rather than valuable or meaningful work.
Thank god we have consulting companies to tell us what humans like!
I just want to know what are the best things to type into these ai chat boxes that will cost the most. If my company wants me to use this garbage then I want to make it as expensive as possible and when their liscenses need to be repurchased I want it to be as expensive as possible to continue to force this garbage on us
Edit. Hey everyone lots of great replies here, please keep the suggestions, fixes, corrections etc coming!
These high prices are not from people talking to chatbots.
They're using agentic tools where their prompt spawns a lot of bots which talk to themselves/the other bots and they keep going until someone (usually a higher quality reasoning model) decides that they've met the goals of the task that they were assigned.
So instead of 1 prompt and 1 response, you get 1 prompt and 800 responses across 5 different bots each using really large context windows.
"Continue modifying this code until all unit-tests pass"
(gives it conflicting unit tests)
I think a lot of SaaS companies love it when people accidentally overuse their services.
Then lays off half it's workforce to save costs and relies on AI to make up the difference.
Big companies license Copilot for less than 25 usd/month per seat. Don't tell me it covers the ops cost, even for mixed calc.
Im June they are switching Copilot to metered usage . People are going to be out of credits on the third day.
Microsoft recently said that they were revoking Claude Code access for employees in favour of GitHub Copilot CLI, wonder if it was them lol
Most companies can't eat a half billion dollar loss so who ends up paying this? AI queries burn actual energy so the AI company would have to charge I would think.
Most companies can’t eat a half billion dollar loss so who ends up paying this?
Taxpaying proles will foot the bill somehow.