We should start to question whether soaring CEO salary spending is delivering meaningful results.
In reality people are rarely rich based on merit alone.
EDIT: Sorry it was a really clever joke.
And the answer is no, because when chief officers succeed it's because of their genius and forward thinking posture, but when they fail it's none of their fault, so they are shielded in an echo chamber that produces such delusions and psychosis.
So much time has passed that I believe truly the current crop of execs don't know any better, they think this status quo is the only way to manage companies. They aren't really wrong since the incentives are there, and they continue to reap rewards from doing it.
They basically said that everything is too expensive, you have to watch it like a hawk. It was as if they poured a bucket of cold water on the room. People were wondering how they could do anything faster with all these strategies. And then “sorry no questions. Bye!”
However when the 'cost' to do something is relatively flat the cost/benefit analysis is going to depend on the value of the person being enabled. Someone making $60k a year using AI to gain a 20% output improvement may not be worth the cost but someone making $160k a year would.
The ones I’ve stumbled upon seem to be: switch models based on task complexity, use tooling like ASTs and compression, disable unused MCPs, compact often, be verbose with input to give clear guidance…
This is such bullshit. Surely they could have recorded the shared part of the presentation and then spend all their time answering the questions?
When did American capitalism become such a zero sum game
One will never get rich on wages. The only way to get rich is through asset manipulation and rent-seeking.
When tokens get correctly priced, all of the insane over-investment in capital will need to draw back: buying data centers, semiconductors, and politicians.
Even then, it won't be right-priced with regard to actual costs. The environmental impact should have been priced in from the beginning. There seems to be a parallel with subsidizing fossil fuels, under pricing them which encourages over dependence, ignoring the real costs society will pay later.
However, the real problem is running wild with token burning. With parallel agents calling subagents you can burn lots of tokens per minute. Especially with thousands of engineers.
I also think the image gen world is a useful analog because there are a million sites, presumably still making money, with markups that are multiple orders of magnitude off their costs. They're feeding off user ignorance that was, at least in part, artificially seeded by implying high costs for image gen back in its day. Though it's possible/probable that the initial training runs were expensive, but that's a one-and-done cost.
Also ironically, a lot of GenZ and young Millenials who were already bitter at their employers have used the tokenmaxxing push to sabotage the AI rollouts by burning tokens on stupid shit. It seems to be working.
They couldn't see that coming, but for sure they can predict how the future will be when it's time to sell their "visions" of the world.
Meanwhile, sheep's are going to believe and max their token usage with their own wallet. "You are so be left behind if you're not".
It's a mass psychosis. The only winners here are the hardware manufacturers, like nvidia for instance.
It's baffling how these people have entirely shut their ears to all the obvious warnings about this, and are now congratulating themselves for their slightly less psychotic outlook and pivoting to blaming the workers for inefficient usage, after specifically forcing them to tokenmaxx.
It's not baffling. They are a caste, wholly insulated from the consequences of their own actions.
Almost every company is run in a basic dictatorial way. We almost never discuss it, when there is a wide corpus of political Science analysing the pros and cons of governance models that certainly puts it at the bottom.
Sometimes literally.
(Meaning that it's not just business school indoctrination, but a dynamic they've been raised to expect and uphold. Fixing it isn't simply about convincing them of the folly of their approach, because you're attacking their personal sense of self in doing so. Which, I'm to understand, is a no-no, professionally.)
After ejecting anyone who spoke out or were even publicly hesistant against the hard swerve into "just do maximal amounts of AI stuff above all else", they're now surprised to find that everyone that remains is dutifully excited about the emperor's new clothes, and yet he remains mysteriously exposed to the breeze.
Maybe ranking it on a scale of best to worse is too simplistic a view, and there are reasons this develops. Maybe it is the best option when there is a good leader, thus such structures dominate, much as a government ran by philosopher kings are better. But this only lasts as long as a wise rule is in charge, and it reverts back to a norm, and eventually, due to pure time and chance, enough bad leaders come on board that slowly dismantle the giants, but this happens at a time scale we don't particularly notice due to how much inertia large corporations can have (before we even get into the less pleasant issues like regulatory capture).
I supposed you meant "why doesn't it get challenged"?
Well, look at how long it took for a democratic/Republican system to appear and survive. The French 1st Republic was immediately at war with all of Europe (I am not talking of Napoleon at all here, it was before that, when the French King was executed).
Nowadays, good luck getting any kind of financing with an "alternative" governance model. The banks and investors will either refuse or edge by pushing higher return rates on you. The whole system is conservative.
The adage "democracy is the worst system, apart from all others" only becomes true long-term. There are plenty of short-lived democracies back to antiquity, in the middle of the middle ages, during the Renaissance, the XIXth century... All stamped down by "more efficient" dictatorial empires... That aren't here anymore. You can expect the same in the even more cutthroat corporate environment, where fitting the system buys you leverage.
And don't get me stated on startups: most of them seek only an exist strategy. Very few challenge any existing behemoth. They are basically externalized R&D.
Is it not wild that in the Freedom Loving West, we all spend the vast majority of our time as adults living inside tiny totalitarian states?
I think this persists largely because the people atop those tiny states are also the ones behind most of our media apparatus, so they can make it look and feel pretty normal. But that may be a little tinfoil hat of me.
But I'm going to need a citation for this:
> a lot of GenZ and young Millenials who were already bitter at their employers have used the tokenmaxxing push to sabotage the AI
The 3 people on reddit doing this don't even register on a company budget. What seems more plausible to me is that budgets were calibrated to spending before agents were actually useful, and late '25/early '26 changed the pattern significantly.
https://finance.yahoo.com/sectors/technology/articles/nearly...
> assuming you have a clear idea of what you want to do and how
I mean, if I have a sufficiently clear idea of what and how, then surely just coding it manually would work significantly better. Unless maybe I am a painfully slow typer.
Without some level of "actually I'm not sure exactly" permitted, then I'm not really sure what LLMs bring to the table.
Features that used to take months are now expected in days. Oh you didn’t merge 40 pull requests and deploy to prod 15 times today? Aren’t you using Opus the greatest thing since the invention of the wheel?! What do you mean it’s hard to review 100 merge requests per day? Just have Claude review it! That’s a PiP.
Oh prod is down because people keep deploying code that nobody even freakin’ read? Just have Claude fix it! What do you mean it’s doesn’t work well? Just burn more tokens or you’re on a PiP.
Surely there wouldn’t be malicious compliance by people that would prefer to use the right tool for the job instead of having this crap shoved down our throats by management by threat of termination.
Does this happen? I’ve never been at a company that measures employee performance by token burn targets. I suspect most companies don’t do that, but I could be wrong obviously.
Token efficiency where instead of the AI burning money at 1:3 instead of 1:5 isn’t quite a winning argument.
GPT5.5 medium is ~20% the cost of Opus and 27% the cost of Sonnet on a task by task basis. That's a material difference.
The more tokens you burn, the more demand for hardware there will be. More demand for hardware means higher stock prices -> more money in your employer's pocket.
The only question is how long that can last. If taken to an extreme, the output of the AI will get worse over time, and if it gets bad enough, for long enough, people will use it less and less, and demand will slowly evaporate.
My point is NOT: I hope this all comes crashing down.
My point IS: tokenmaxing is bad. AND weaponizing it will not have the intended effect, but in fact, it will, in the short term, do the opposite.
If you work for NVIDIA, sure, but otherwise, this makes no sense to me.
I wonder how widespread that phenomenon is. Perhaps it's no wonder the prominent actors are trying to rush to IPO...
It doesn't matter what the line actually measures, just that it goes up.
And by "projects", I mean corporate ones with big teams involved. Hobby projects actually do get finished much faster.
In fact it is all smoke and mirrors, pure mania from C-level executives out of their depth trying to one-up each other with company money, and they aren't even close.
This isn't surprising. Ive recently run into quite a few rabbit holes where AI is bad enough that its much more efficient to do it myself. I wanted to refactor some code, gave it a design pattern to go towards, some specific classes and methods, etc. making it a well described problem. AI just couldn't do it satisfactorily. The code was ugly, overly verbose, and after multiple tries with multiple prompts saying to keep things simple. They still would introduce new classes, useless fields, etc.
I wonder how many megawatts that waste represented. Just one guy, worse than a small air force of private jets.
If you move those things to software and utilize tools that are cheap at scale (databases, web search etc.) the hardware arms race ends and the price becomes sustainable. With the right tools preparing dynamic context for a conversation, models are used for their reasoning and not for their knowledge. And waiting even a minute or two for a model to prepare a response, evaluate it, and iterate to improve quality makes a huge difference.
I'd like to see real numbers at this point, and this article is just a few bullet points that link to other articles. Talk is far cheaper than tokens and I'd like to have a workflow that I can rely on being there in six months.
https://simonwillison.net/2026/May/27/product-market-fit/#th...
Previously if I needed to automate something I thought really carefully about it. Now, I still think really carefully about it. I had fun AI coding some tools I always wanted but they were just pet projects for me. I had fun AI slop coding a couple of things, but it was not good software. But if you have a clear and valuable target? AI can absolutely get you there.
Multiply that across all your colleagues and a lot /seems/ to be happening, but what is actually moving the needle?
https://www.wired.com/story/how-ai-agents-plunged-tech-world...
The mood has gone quickly from “this is cool” to “screw AI and any business that wants to use it”
This is particularly clear among the taste making class
Look, LLMs thrive when they’re given structured data that’s well annotated, clear direction, and treated as the probabilistic machines they are. Not one of those meshes with the AI narrative of “works on existing stuff, requires minimal guidance, and can behave deterministically.”
I said as much in 2024 when my employer at the time was grading folks on AI usage while my role was entirely deterministic in nature. It didn’t resonate with specific leadership then, it doesn’t seem to be doing so in the larger market now, and unfortunately not one of these dolts will suffer any consequences for their organizational myopia.
If I understood correctly, a few months ago Anthropic and OpenAI both started charging per-token billing at API pricing for Enterprise customers? i.e. representing roughly a 10x price increase? That's kinda nuts.
Similar discussion yesterday:
There is a complete disconnect between wages of employees and company's revenue => Why aren't employees working towards revenue? What a mystery. Children, let's help Elmo solve this mystery.
And then random mass layoffs to make numbers for shareholders look great in quarterly reports. Surely this motivates people work to their fullest potential and to care for company's revenue.
Companies with EOSP programs outperform those that do not in the market by about 17%.[0] Companies that perform layoffs, despite short-term stock boosts, underperform on a period of years showing a 14% decline in their Return on Assets (ROA) in the years following the layoffs.[1]
[0] https://www.nceo.org/employee-ownership-blog/new-study-shows... [1] https://www.researchgate.net/publication/277473996_Financial...
So im looking at CEO, CTO, CFO, and all the chief-something-officer. If LLMs are that totally amazing at thinking, then we should be targeting upper management, not the workers.
That would save a LOT of money for the shareholders! /snark
We all know why they wont.
But good forbid we actually correct a major social ill at the expense of the people who profit from it.
CEOs: “Get me some of that GenAI”
CTO: “OK, we have all the GenAI”
CEOs: “Employees, it’s AI or bust”
Employees: Tokenmax
CFO: “Um, this is costing a ton and we’re not seeing savings or efficiency materialize.”
CEO: “Are we getting any value out of this?”
COO: “Not really, and frankly I’m getting annoyed at all the AI slop turning up all over.”
CEO: “OK, well, let’s do a big layoff and then I’ll just say it was because of AI. Hopefully folks won’t blame me for the mess and I’ll just talk about how amazing AI is.”
Lesson #1 from business school : take all credits, put the blame on others, if there no easy scapegoat blame the "economical context"
Lesson #2 and beyond : just see lesson #1, it's enough. You've made it and it's ALL thanks to this amazing business school degree you got, now go profits with your new already wealthy peers.
It's amazing to me how subtle the difference can be between a business leader that seems to know what they're doing and one that clearly does not. Same words, even, but from one mouth it's compressing a complex thought and from another it's word salad to give the appearance of complex thought.
Indeed the "worst" part is that the initial concept might very well make sense, even be grounded in actual research.
Masters of semblance.