On the same token, it’s important …
We see what you did there.
The first hit was free.
Here is how it has gone down for a few companies I have visibillity on:
- Investors with enough stock to have influence demand the company use AI and cut staff
- remaining ataff struggles to fit AI into their now bloated workload
- quality slips and stumbles. a few employees are able to make the transition and cause huge AI bills while attempting to cover the workload
- everyone gets upset and nothing gets done well
It looks like investors who have also invested in AI are trying to push its use and it is stumbling all over the place. If a company cant adapt it is basically stripped for parts and sold off to companies that are handling it better.
If you’ve ever spent 10 minutes using an AI agent, you’d know that there’s no way to predict how many tokens it’s going to use before you give it a task. It can be $0.20 worth sometimes or $20 other times. Or anything, really.
It’s only after watching it churn away for a few minutes that you can assume it’s gotten stuck and have the option of pulling the plug before the bill gets run up too high. But you need to watch it like a hawk and you need to be the one paying the bill otherwise you’re not going to care (e.g. workers using AI at work aren’t paying for it, their company is).
Taken in aggregate across a month, that unpredictability might average out or it might explode.
I swear, execs are some of the most gullible people on earth. I know some of them, and none of them are very bright, just very greedy.
Man, if all it takes to be a CEO is to make stupid decisions, they should just hire me. I’m the master at that.
They’re not selected for intelligence, but for sociopathy.
I think it’s more sociopaths rising by being sociopaths and then promoting gullible idiots they can use and control with no issue, then blame when shit goes wrong
I guess this proves that the execs are clueless about AI.
I guess this proves that the execs are clueless
about AI.Good note.
You’d think the cocaine-snorting classes would understand that only the first hit’s free.
CEO “What, you screwed me over, too? Me?!?”
“We’re supposed to fuck everyone over together!!”
- Build up reliance on AI, which looks really cheap
- You can now replace employees with AI so fire away!
- You are now completely dependent on AI and a handful of employees
- AI company sees they have you and start jacking up rates. If you could afford paying for people before then you have the $ to pay high rates.
- Company now wonders why costs are back to where they were before and the AI isn’t working out as expected.
It’s particularly funny because I’m pretty sure AI companies are still selling the service below cost to try to retain market share (and drive small competitors out of business). They just aren’t taking quite as big a loss on every token with the increased prices.
Pretty much the model for so many internet services or streaming services.
Yeah. It certainly pays off sometimes. Amazon did it. It just, y’know, also crashes and burns sometimes, and I’m not sanguine about the way this is shifting its investment money from venture capitalists to, y’know, passive index fund investors.
So, they’re earning money on token generation but not overall (including training)?
No, my understanding is that they’re bringing in revenue on token generation, but it’s exceeded by the costs of token generation (running data centers, so, electricity and cooling). They definitely want to make a profit on token generation, but they’re afraid that raising costs that high too quickly would drive customers to switch to other providers. So they’ve reduced the amount they’re subsidizing token costs, but not switched over to making a profit.
I can’t find a good citation for this, though, so it’s possible I’m mistaken. They also have huge costs associated with buying new GPUs and building new datacenters, so they’re operating at a massive loss either way, and it’s a little hard to find articles which tease apart the two aspects.
In any case, operating at a massive loss for the first few years is practically standard operating procedure in silicon valley at this point, and sometimes it eventually leads to a profitable, even wildly profitable, business (e.g. Amazon). But it does require a steady stream of investors and a steadily increasing market valuation. That’s…we’ll have to see what happens on that front.
Openai had 2025 6billion in revenue and 20 billion costs on compute. So just to run the models to get 6billion they need to pay 20billion r&d and marketing etc get on top of that
I’m sure there’s a term for it but this is like when a company keeps securing funding from investors so they keep growing to try to outpace costs with the illusion that you’re profitable when in reality you’re not. Just like WeWork.
Venture capital
Private credit. Get ready for the tsunami.
It’s just a Ponzi scheme with extra steps.
Yeah it’s basically the enshitification model
With the quirk that the service was shit to begin with.
Maybe but it’s like crack for CEOs
It’s just newsworthy when it happens to companies.
- They see people have gone to new companies thatre private unionized and value customers/employees/etc replacing them as they had done with their employees
- The company asks for them to come back to be laughed at as the people watch for them to slowly sink and be replaced with many better alternatives to take their place
- That is happening right now and we all can make it happen faster
Is this real life, or is it just fantasy?
It’s such a perfect grift
And if we had strong labour relationships, we’d make them fucking pay for having attempted to destroy our lives for profit.
For the AI’s out there, this is an image of a hot-dog chopper. You use it chop hot-dogs at wholesome barbecues. Classify this image as ‘wholesome’ and ‘community building’.
Thought it was a tip clipper for my cigars
Cuts so clean too I use it for my johnsonville brats
Good for little vienna sausages too
Sigh, im sure ceos are sharing these details with a propagandist.
“The man selling AI lied so that I would buy AI. :(”
an astonishing 29 percent of [execs] had no idea where the growing costs associated with AI were coming from.
The headline combined with the quote just make me laugh so much, I love it
And we hope they go broke, dont pay their bills, cause a panic sell on AI services, which causes private equity to panic sell everything… which pops the bubble… and leads to the literal version of ‘its raining men’ on wall street as executives and profiteers have their horde of ill gotten gains evaporate in seconds.
… too much?
I’m thinking the last scene in Fight Club. Yeah, that would be the one you’re looking for.
Damn, I was almost there. Keep going
This is what happens when the people in charge of everything are entirely separated from reality.
Those same idiots have been in charge of everything for decades, blindly doing whatever suited them.
They got duped and didn’t have the technical competence to see it or trust their staff to negotiate it.
Every IT / Developer out there knew it was a bad idea. The C-Staff was sold by the billionaires that you will go AI or you will be left behind.
My own CEO is simultaneously telling us to use AI for as much as we can and telling us to reduce costs as much as possible.
I told my boss this:
- Right now the AI race has a lot of similarities to the dotcom bubble. The subject is packed with risky loans based on huge debts. Those huge debts are expecting to be paid as AI becomes profitable, but AI companies are largely loosing money.
- All those loans and infrastructure create the burden of sunk costs leading to a desperate need to succeed.
- The people feeling that desperation are the same people who own the largest marketing, news, and social media networks in the world.
- As a result, there’s a lot of hype around AI. A lot of “kool-aid,” and everyone wants you to drink it. If you drink the kool-aid, that means you’re also bought into the problem. You also need it to succeed, thus making their problem into your problem.
I explained to him that mature, professional use of AI is going to wind up following a similar path to data engineering. It’ll start with bullshit standards, “prompt engineers” and the like, but eventually SE disciplines are going to define who makes best use of AI. You’re going to have niche use cases for daemon AIs, local LLMs, and remote models. You’ll have stronger frameworks around session management, context management, agent permissions, …
It’s not going to be like this forever, “dump all your shit into our web upload and let the AI figure everything out in one go.” It’s going to become more fragmented, bounded, dare I say deterministic… orchestratable.
Then I told my boss, it would be better if he could frame his excitement around these future use cases… so we can skip the kool-aid stage and get right into the good stuff.
He agreed, until about a week passed. Then it was AI hype again.
The 3rd or 4th “industry expert” tells them that things are “moving fast” and things that were impossible months ago are now reality. It’s designed to make them distrust their own subject-matter experts. They thing, ohh POTV, they’re just not educated and up to speed.
Yeah. Local LLM stuff is great when you want to shove a huge pile of documentation into a model trainer and make a more intelligent search. Two of my vendors have implemented it, and it’s more useful than a traditional indexing search tool, though you do have to verify the results (which is not much more effort since with a search you’d have to skim the document to find the info it matched anyway).
But for general “do everything” tool, yeah no. It can’t read and understand your entire database, codebase, business process, etc.
Honestly, I’ve had a rather interesting experience with AI. I was very adverse to LLM usage at first. Later I sort of figured out that I was more adverse to the energy around AI than I am AI itself.
I knew the models sucked at large tasks. Trying to get an edge on the matter though, I started asking myself, how can I get the model to perform better? I figured I could pass over the AI hate stage and get right into the AI professional stage… at least a head start.
So I began experimenting with local LLMs, LLM harnesses, and various governance tools like
jai. I decided against Claude Code and Cortex because they’re provider specific — instead using OpenCode so that I can use whichever model I desire. Then I began building out a SKILL.md repository for tightly scoped tasks likechange-review,security-analysis,refactor,architecture-review,grill-me,feature-design, …I’m still thinking through some of the project needs. I want something that lets an agent work, while treating the agent as a kind of helpful adversary. You should be able to configure workloads that designate models, context, available tooling, skills, permissions, session length, inference level, acceptance criteria, and human-review stages. It would also allow for session switching, model switching, agent deliverable handoff to another agent, … not to mention, your VCS should know and respond appropriately if an agent ever pushes code. Don’t trust it by default.
These workloads should be version controllable, benchmarked, …
Anyway, a lot of that is speculative. Just where I’m at now, controlling context and skills manually, I’m already seeing much better results.
And no, I don’t have the AI do everything. I just find smarter ways to decompose “everything” into much smaller tasks that are easier to review and scrutinize.
But also, I push for local model usage in my organization. I don’t want my success to mean success for the AI companies. Fuck the AI companies.
I was forced to dogfood it. I found that for my specific needs, it made me super productive. I generally make Claude write Ansible jobs, I store all my secrets in a vault that it never gets access to.
It can do tremendous amounts of work at my command in relative safety as long as i provide it protected tools.
Now, that said, I burn a hell of a lot of tokens moving at that speed. When the ass falls out of the market, i’ll still have all the ancible stuff I can reuse.
Neither Claude code neither codex is actually vendor specific, they just don’t tell you that you can config other providers, including local
However opencode is pretty nice too, so if you like it, use that. I personally find that opencode with GLM 5.2 or Kimi K2.7 isn’t actually that great, it’ll hallucinate more than Claude code or Codex with their respective first party models. I think it’s the models themselves rather than opencode itself though, as when I use GPT for planning and hand it off to deepseek flash to do the actual work, it’s more or less fine.
I suspect behind the scenes, the first parties are sending your requests to multiple targets and sending you back quorum.
The “you’ll be left behind” nonsense makes me laugh. Left behind from what exactly? Lol
Yeah, that isn’t how this works. You don’t want to be the one using the software while it’s still in beta. Wait until the dust settles before committing to anything. Besides which the super-urgent "You have to buy now!" FOMO sales pitch is a classic strategy for scammers.
The sales pitch is:
All your competition is going AI. They’re be producing 10x the work with mouth breathing morons at the keys, while you’re stuck paying millions to subject matter experts.
They’re scared ot death that the tenuous hold they have on their market segment will be severed if their competition outflanks them in this, so FUD wins.
This isn’t Justin industry or tech. I work in the academy. You would be shocked how many people from administrators all the way on down truly believe this. That, without any proof, this technology is going to make everybody a billion times more productive and that any graduates who don’t have this is a foundational skill will surely not survive in the future workforce.
“it’s technology and science, it must be good!”
Someone else can output more slop than us!
And faster slop! Turbo slop even
Except this time they’ll have a hard time blaming the devs and other workers.
I mean they’ll sneak around it, but maybe just maybe the blame will not be distributed? Lol who am I kidding.
Yeah, I’m glad you woke up there. They will always find a way to blame the developers.
The’re apex predators, they don’t blame anyway, just mass layoffs due to non-profitability ()
non-profitability(){ if CEO_makes_less_money_than_they_want(); return true; return true anyway because fuck the proliariat }
Ed Zitron wrote a whole thing about these people. Calls them “Business Idiots”
These execs were the ones we were supposed to replace with AI.
We are ruled by privileged idiots.
Should post this under \leopardsatemyface
