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My company recently converted our PMs into Vine Engineers right after laying off actual engineers. They don’t even know what git is or how to use it. 3 of them alone are using $7k a month in Claude tokens and they have not raised so much as a single PR.
Who needs PRs? What’s a branch? It defaults to master and that seems to work just fine!
So it has a negative ROI and anyone who brought it into their firm is a clueless twat who uncritically bought a sales pitch.
If corporate governance were not a joke, C-level heads would roll.
I’m confused. I thought employers loved AI and it was the future.
They love money. AI was good money for a while. Or at least it looked like good money until you looked at it for longer than 3 seconds, which greatly surpasses the average attention span of an executive. And also the average executive’s iq.
They loved it too much and now it costs more than paying a living wage to a human being. The end goal of AI was always to cut cost and layoff people. The best sabotage right now is to setup a script that constantly prompts an LLM for something useless. I would recommend it if it didn’t waste so much energy and clean water. But it would send a message. AI is not cheaper, it never was. Even with today’s outrageous token prices, LLM companies are still bleeding money per user. It will only get more expensive as data center contracts fall through and the investment craze fizzles out.
the AI companies are hoping the ones buying the LLM subscriptions to be the suckers and losers.
I would recommend it if it didn’t waste so much energy and clean water.
I wouldn’t. It’s not possible to do meaningful validation of a process that has AI in the loop because it is not repeatable and there is no reliable explainability. So for anything where money or lives are at stake, it’s not worth a shit. Same goes for anything where the company is held liable for false statements.
I meant as a means of corporate sabotage.
Mixed bag.
There are legitimately high value problems that AI works well against. But ungoverned proliferation has a net negative ROI across complex and difficult to measure areas.
When applied expertly, it works great. When blindly handed to your entire workforce as a panacea, not so much
Someone’s been reading the HR posters.
Some CEO guy said employees must evolve. Throttle your workloads even more employees. Transcend! Praise be to the AI overlord(s)!
A sign of the times? Possible lead in the bubble popping?
AI bubble popping is that gif of the crash test truck.
No clue what you mean.
Wait for it.
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
Kids these days don’t even understand trout slapping. SMH
Roflcopter?
Roflcopter?
Hey hey hey hey hey whoa whoa let’s just keep the big guns in reserve for now, ok?
Ai bubble burst will be the time.
Too bad it’s going to hurt so many people too
Albuquerque New Mexico…
IYKYK
Albuquerque New Mexico period period period exclamation mark
It’s just a special case of TANSTAAFL.
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.
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.
Consider each session with Claude a new employee. Your Claude.md file is what it knows and how it acts out the gate. You can save memory to it or save directory links so it knows where or how to look for something.
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.
LLMs generally work in one way. They get the prompt and give an answer. CLAUDE.md, system promp, rules, memory, tool defintions, mcps are different ways to prefix your prompt with extra information or context.
Skills, or plugins, are a way to inject less information until is needed (you can think about them as prefixing your prompt with “if you are asked about pizzas, add to context separate file pizza.md”).
What you could add to CLAUDE.md depends on what you’re doing. Generally it should be context LLM cannot infer relevant to all/most task performed in given project.
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.
That’s exactly what it’s perfect for. If you go further and detail the intent of the project and give a high level overview of the architecture, it’s even better at inferring what needs to be done without a bunch of expensive file reads and asking you repetitive questions
The models are evolving. Everything uses multi modal in the bavkend, eating up more and more tokens for the same task.
I switched to caveman on Claude Code. It cuts the token count; it’s the same output, and it appears to me to be faster as well.
Uplifting News
This is actually how the bubble begins to pop, we’re seeing it happen now.
…said every day now for a year
All over America, employees are saying “But YOU said…”
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.
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…
Heh, re ass.
Imo its because people will lazily ask the llm to remove or change simple code instead of doing it themselves
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”
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?
If you run “agentic coding harness” or any kind of goal oriented loop then tokens goe brrrr.
And LLM sellers are pushing for that (duh), as they managed to convince people to use infinite monkeys typewriting until they make Hamled.
(Type made on purpose)
I do it on purpose
Some companies had leaderboards and encouraged AI usage until they got their bills.
Agent loops for SWE burn a LOT of tokens.
I’m unfortunately temporarily disabled and can’t use my hands for another 2 months. So I’ve leaned heavily into AI based workflows to keep my job in the meantime.
Aside from the nightmare of keeping quality high, not atrophying skills, and avoiding a lack of domain knowledge. It works reasonably okay.
Token usage is insane though. A productive day might cost a few hundred dollars in tokens all things considered. Quality is expensive as well, a good 1/4 of that are automated systems that exist to identify defects, quality, coherence…etc issues early.
A big context costs a lot more
If you click the most expensive model and then click max/fast mode, the same task can easily cost 10 or 20x of the cheaper models
I watched two colleagues this week and both had Opus 4.8 1M max thinking. No matter which task. It’s also slow as fuck. I work almost all day with GPT-5.4 low thinking and get good results… but faster and cheaper.
I guess good model selection and promoting will be what sets devs apart in the near future. Once that bubble bursts a bit more and prices increase further that will be an interesting reckoning. Also for companies who basically taunted their employees into tokenmaxxing.
I tried Warp terminal because now that’s bankrolled by openai’s magic infinite money you can use your own openai api keys without a subscription. So I put one from my work account. I do a git commit (manually) and then it comes a prompt under it “push it, open a PR and switch to main?”. I click yes, it used one million tokens for that… (And it took about a minute because it did like 20 requests, so there was no time saving at all vs doing it manually)
I wget something, it comes a prompt under it “now compare the hash?”. Boom, another 500k tokens
That’s completely insane. At best it would be useful for the pr title and message, but the rest of that is waste.
These are the kinds of things I just ask in chat. “Whata the cli command to compare hashes again?”
People who use slop generators for coding assistance are insane. Everything else is a logical consequence of thinking you can take shortcuts to coding.
I am not able to use the tokens provided by a Claude Max account either.
But if someone tries to be clever and have 10 employees use a single Max account, they probably run into the limits often. And if the response is to let them just buy API-prized tokens instead of getting more accounts, that gets very expensive very fast. The single-user accounts are subsidized. The extra token prices are not.
Actual business accounts are prohibitively expensive. And at least Anthropic terminates subsidized accounts when they see extensive use.Real token prices are insane. Most businesses couldn’t afford them. And eventually the VC capital will dry up. The cheap AI bubble will burst. And then the market is in for a real sticker shock.
Better be prepared to switch to local inference for as many use cases as possible.I read they were automating everything whether it needed AI or not just to get credit for using AI.
I had to push back on that at work. Most of the problems presented were easily solvable via conventional methods. Only one task was a legitimate use of AI. There are some others, but the pressure to consider AI for every task is a little bananas
My boss was talking about using AI agents for CI/CD processes. Like, I get using them to build CI/CD processes, but involving AI agents in the actual build process is ridiculously stupid. A representative from Microsoft specifically said in a training session to not use them that way so it’s obviously not only my stupid ass boss.
involving AI agents in the actual build process is ridiculously stupid
The very notion instills fear and disgust.
Only nerds want idempotent build results, it’s so fun debugging slop…
I’ve heard “loops” will burn a lot of tokens. Haven’t tried it myself. A person could also spool up multiple loops to work on multiple branches at the same time.
3-6 active sessions on different work trees isn’t unheard of either
I am not convinced yet of letting agents completely unattended. Watching them work makes review easier for me. If I let the agent just produce some result it needed half an hour (or more) for, it’s very likely so convoluted that I can at best skim over it and then go „yeah yeah ok, it’s probably fine <merge>“.
What are you using? Which product? I got 2k last month and was told to use cheaper models indeed
I generally use sonnet 4.6, switching to opus 4.6 for more complex stuff. I try to stick with medium thinking, but will use max for stuff I am not super specific about in my prompt (or obscure errors).
I use them through a GitHub copilot enterprise license, via the plugin for jetbrains.
That’s funny now that whole workflows are automated with it. Oops hit the quota, I’m off
You mean those workflows that could’ve been traditional scripting and CI/CD, if not for management forcing AI into them? Those workflows?
Those workflows
Use ai to build an application/ workflow?
No, use ai to call ai to analyze everything and poof insane costs monthly
“Sorry boss, quota resets this evening at 8. See you tomorrow!”
“But it’s 9am!”
*shrugs* “Quota. Got none. Seeya.”
The new sword fighting in office chairs because “compiling”
Seems like A.I. is already demanding workers rights and lunch breaks. We treat the clankers better than actual human workers lol
