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.
I sincerely hope that was your attempt at sarcasm.
"Successful" in which sense?
The most reasonable definition "Successful in convincing other people to give them money" is rather a tautology. :-)
A very related problem concerning your argument is well-known for decades: the Principal–agent problem:
> https://en.wikipedia.org/wiki/Principal%E2%80%93agent_proble...
It says that the self-interest of an agent (e.g. the CEO) is not identical to the interests of the principal (e.g. the shareholders).
Why do I mention this? The CEO being rich is a measurement of the financial success of the agent, but not of the principal. You are rather interested in measuring the success of the principal.
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.
By the time he died (pretty recently actually, 2020!), it was pretty obvious what kind of legacy he was leaving behind. Which is probably why his family was very careful to keep his burial location secret, presumably to keep people from peeing on his grave.
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.)
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.
One other question I had but wasn't sure if it would leave my previous post too unfocused is "aren't we a bit too early to determine in our current government systems are really the most effective?" This is something that will be decided by political scientists far removed from the current societies who can see how our current societies evolve.
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.
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.
If you're thinking "that's bad management" then we are in complete agreement. He should have been able to predict this in advance, but evidently he either did not, or is pretending he did not.
The interview is linked in this article: https://www.businessinsider.com/uber-coo-andrew-macdonald-ai...
Sure most token burning ends up being a waste but some ideas pan out?
Not disagreeing but it's another way of looking at it IMO
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.
For example I want to make it so that users receive an email when their password is changed. I can either do it myself, which requires reviewing and remembering code I’ve written five plus years ago and then wiring everything up and obsessing over the wording of the email. Or I can give a two sentence instruction to the AI, work on something more meaningful while it is doing its thing, and then test it in under 60 seconds when it is done.
If you're just working on a single react component or an algorithm to do stuff with data, there's less chance to amortize the up front planning and verification so it comes out more of a wash.
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.
All that aside, refusal to participate in bullshit doesn't imply some "plan" to bring the company down, it's really just refusing bullshit. It's not "5D bullshit", i.e. a move in the same bullshit game they are refusing
And if you offer someone 5 bucks to help burn down their own house, that of all their friends, so someone can make 5000 bucks, then they might just refuse, not because they have some plan, but precisely because refusal or letting themselves get hollowed out as well is the only option they're given. It's not like any of the hollowed out people listen to them in earnest.
Young people, which is crazy to me, often want some kind of stake and participation in the world rather than being disposable slaves, they want to do work that makes sense, that enables them and others to grow and prosper, in order to prepare them to become stewards of that world later on, which they want to make better and not just exploit, generally. Mostly, some of them of course are assholes or stupid, but in general, people come to this world way less fucked up than the world wants them to be.
I believe it is absolutely ridiculous to have token usage leader boards.
But isn't it also ridiculous for a rational human being to use as many tokens as possible regardless of whether or not that token usage is useful or valuable?
It seems obvious to me that AI service providers make more money the more tokens are used. It also seems obvious to me that companies who sell shovels during a gold rush stand to make a great deal of money, whether or not any gold is found. How is that a good thing writ large?
Anthropic, (and SpaceX), might IPO soon - a move that will grant them access to capital instantly. Capital that comes directly from the retirement plans of all of us.
All I'm saying is if you want to somehow sabotage the game somehow, this is definitely not the right strategy. Political influence would be far more effective.
What am I missing?
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.
If someone else can make it more efficiently, there's a powerful force for you to also have to improve to match that efficiency.
"Why is the airline experience so much worse than 50 years ago?" "It's massively cheaper per seat-mile, and consumers in aggregate reveal that they prefer the cheapest price that online travel searches, so airlines deliver to that preference."
I guess while I agree that American shareholders do reap incredibly benefits coasting is not really something america does. America is more than just shareholders too. You dont grow the world economy by coasting and you dont make up 25% of the world nominal GDP while only making up ~1/25 its population by coasting its inconsistent with reality.
I know we also argued that WW2 is what allowed the US to coast but I'd argue that New Deal programs that made demand and things cheap (like electric think TVA). This arguablely fuels American industry as it rushes to fill in the WW2 demand. All this investiment happend before WW2 even started and I think doesn't get nearly enough credit for allowing the US to 1 not become facists and 2 allows the US to step in and support the large demand of ww2 and post war. If we didn't invest in the nation we would not meet post-war demand and be much poorier today.
Finally, I don't want to be nilhistic or depressed if we can observer that we did things better at one point we can still choose a future that is better regardless of what mistakes we make today. We can make better choices albet it limited from today's options that will actually allow the US to raise people higher out of poverty. I don't agree with the idea of betting against Americian ingenuity in the long term it tends to lose.
Despite all of the problems that exist were still the best off.
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.
To further complicate matters, you had to spend on AI software and potentially additional on legal/risk/security/compliance to enable that.
The smaller the company, the bigger that % of coding is of total time (all the way down to hobby where the majority of time is spent coding)
imo we either need to centralize the agent and and submit plan, spec, reference doc MRs rather than submitting code changes. Or develop SCM systems/workflows that incorporate plan/spec/reference/prompt metadata with code so intent can be factored into merges.
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.
https://www.iheart.com/podcast/1119-better-offline-150284547...
I wonder how many megawatts that waste represented. Just one guy, worse than a small air force of private jets.
"Check all of Confluence for outdated and conflicting info"
"Review all the legal contracts over the past 10 years"
"Evaluate the source code in all our dependencies for vulnerabilities"
All of those would be fairly straight forward for a single person to kick off without thinking about the data set size. Especially if they have Claude set to Opus 4.7 x high effort for everything.
Even someone saying something like "rewrite the 25 year old Java monolith in rust" as a PoC and leaving it running in the background for a week
You have to fight quite a lot with agents to get them to actually read the fucking files in full
They are not the same.
I agree fully with you on the potential for energy waste. We always do that, though, with nearly everything. How many of today's jet plane flights really needed to happen? The question is how much value people feel they're getting. People are having a whole lot more feelings about AI than they ever could about cryptocurrencies, and that train aint stoppin'.
> How many of today's jet plane flights really needed to happen?
Many jet plane flights are indeed not necessary and there are people who deliberately avoid such unnecessary flights.
> The question is how much value people feel they're getting.
It is indeed a question we should keep asking and weight the answers against the energy footprint.
We need to plan for the world we're most likely to be living in in addition to the one we want to live in but probably won't. The latter energy isn't entirely wasted, but it's also not as essential to our immediate survival.
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...
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.
>win
At one point i noticed that the demo had a column that showed how many tokens each AI query was using.. one used 250 THOUSAND (for a single analysis of a single device). I asked the company who is footing the bill for those tokens.. they say they are (*for now). I pointed out the rather high number of tokens being used and does that mean we get a budget or quota or is it all you can eat.
they said it was a good question and they'd have to find out... and then one of the execs said OUT LOUD "Why is that column even there? Why do we show this to the customers"
I lol'd. It wasn't taken very well.
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?
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.
I’d love to see more research on the efficacy of LLMs as organizational middle management, but I fret that without sufficient anonymity protections for staff they’ll just do the same biased shit humans do.
The speed of writing code was never the bottleneck in software. Yes, AI can do it faster, but the parts that are most challenging are finding a market and figuring out how to best serve it. Those are the parts that take the longest and, often, the most resources. In reality, this is the real business of any company, what they produce is just a side effect of finding these two things. AI hasn't shown much promise in this regard. There are some simulated and small real world tries like what Andonlabs[1] is doing but it seems humans are still better at this kind of problem solving.
Companies have been spending ridiculous amounts of money trying to squeeze innovation out of a tool that is designed to produce statistically average results. This leads to mass layoffs because workers, who also produce average results, are seen as redundant. But when average workers come together they can produce extraordinary results through the mere act of working on something long enough and synthesizing ideas. Eventually, someone will say or write something that triggers a thought for someone else and it leads to a breakthrough. AI can't do this, yet.
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'm sure there is an explanation for why they keep doing it.
https://news.ycombinator.com/item?id=48268871
https://news.ycombinator.com/item?id=48238896
However, given government budget deficits and the need to outgrow inflation / the ever increasing annual interest burden the US gov carries, AI kinda HAS to be an insane productivity booster or else everything is kinda effed.
As I understand it, most of us economy / sp 500 growth in the last year or two has been attributed to AI spend and speculation…
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
That's right! Work, slave, pain away every day! How dare you make your life a bit less miserable?!
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.
Example: You work at walmart, as a cashier. You drop a $100 bill on the floor and pocket it from the till. You're caught, cops called, and you are arrested.
Example: You work as a manager at the same walmart. Store manager says labor costs are too damned high. So you go in on 10 employees, and edit their timecards to cut $100 from each of them, totaling $1000. IF you are caught, police will not respond. Instead, it is a "civil matter".
This is a bit dated chart, but its still very much correct. https://www.tcworkerscenter.org/2018/09/wage-theft-vs-other-... But notice the wage theft types are all "civil matters", and the non-eage theft are heavily criminally prosecuted. And who does those? Predominantly poorer people.
We also see this with dumping trash, being criminal and severe to the individual, but companies (read: Musk) can dump thousands of gallons of toxic sludge per day. https://www.yahoo.com/news/articles/inspection-texas-drainag...
We also see criminality differences between charges of freebase cocaine versus crack cocaine. Crack was what black people smoked, so sentencing was like 10x of freebase.
When you start looking at how laws are apllied, its almost always the same pattern: those at the top are a civil matter. Those who report to the top are a criminal matter. Those at the bottom are "charged with the fullest maximum punishment".
If the manager hadn't stolen $100 from the cashier, there would have been a MUCH weaker incentive for the cashier to steal themselves.
This is the crux around which everything else turns: we are effectively post-scarcity, as far as production is concerned. As a society, we purposely create theft, and debt, and the associated desperation and crime, as a matter of policy. As a choice.
If you were eradicate wage theft, you would essentially eradicate the internal logic of street theft, in the vast majority of cases. We could just... not have theft. But by not prosecuting wage theft, we, as a society, have decided that we condone and even need theft.
https://www.wired.com/story/how-ai-agents-plunged-tech-world...
There are literally no good programmers mentioned in that article. They are all boiler room VC types. Shame on Levy, this article is planted or has has no clue.
If that's the case, then I do expect the AI bubble is going to pop spectacularly next year as token budgets are going to collapse. The damage to the tech industry is going to be catastrophic. If you think the job market is bad now, wait until data center spending goes off a cliff.
Well, no shit, but also: suggests those tasks have questionable value? And also: this is why I learned to write code in the first place.
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:
This is act one the AI bear market. Yes I know everyone screams “bubble”. Let me explain the scenario I have in mind.
1. AI booms because the technology seems to actually have promise of revolutionizing how work gets done. It can do your taxes! It can drive Excel! It can act as a CEO! It can code up full apps and SaaS products! It can replace this vendor or that! You know the drill.
2. Every company must in corporate AI or be seen as obsolete. Having a bad quarter? Announce that you are “seeking to explore opportunities to develop an AI integration plan framework” for your plumbing business. Massive AI compute buying happens. While two of the three major AI houses are not publicly traded proxies like Nvidia and RAM manufacturers are so the market rips higher and higher. Nvidia trades as if it is already 10+ years from now, every company out there has adopted AI perfectly, and it is delivering huge profits to them.
3. Reality checks start pouring in. Turns out that not only is AI expensive (a problem that presumably will be taken care of with time and development), but that the technology itself just isn’t suitable for everything. (IMHO it’s great at augmenting a power user but it is terrible at interacting directly with customers). We start seeing individual companies change tone on investment. They can’t stop it due to momentum but they are starting to shift the narrative to warn of what comes next. This is where we are.
4. Numbers come in. Earnings show what the actual ROI is. Some companies do benefit, but crucially we see examples of where investing in AI destroys value. I think this happens when replace crucial parts of their workforce with agents and find that they lost in-house expertise, when customers left due to worse products, or simply when AI was roughly as expensive as human labor without being significantly more productive.
5. The market stumbles. What do you mean AI won’t take over every corporate America?! Surely that can’t be right! Nvidia and other proxies flag.
6. In a late to the game rush Anthropic and OpenAI IPO fearing that the market has noticed that the emperor has no clothes. Their internal numbers turn out to be scary: very high revenue but no path to insane profitability. They quickly get included in QQQ and maybe even S&P500 but as their IPO price is the highest they trade they drag the broad market indexes down. This is leveraged by the Nvidia proxy status.
7. Infrastructure course correction. Hyperscalers who started huge datacenter buildouts cannot justify it. They pay contract penalties and get out of some of the projects, writing down losses. The market fully melts.
—-
I think there is a competing market downturn fueled by the affordability squeeze. Basically while AI spend is corporate driven, the biggest investors are consumer companies. Of the hyperscalers you can maybe argue that Microsoft is not a B2C fully but it is close. If consumers don’t have money to spend, hyperscalers take a hit, investment slows from there, and AI is hit directly by it.
I think either scenario is likely, it’s just which happens first. But right now the market is sprinting down a tight rope and trading like that tight rope has no end and that the sprinter never makes a mistake regardless of wind changes. Everything has to go right for a very long time to justify valuations. One stumble can stop it all.
It is ironic that people got laid off due to capitol allocation for compute capacity and people will get laid off when there isn't much ROI and things crash.
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.
My analysis of the whole space is that all the tech people are focused on completely the wrong end of the problem space (model quality, training, token cost, etc.). They are geeking out on that stuff. Worse, they are mostly not even that good at using their own tools. I regularly talk to so called "AI native" companies that are hiring enterprise sales people to do sales like it's 2006 instead of 2026. Their product is AI native, but their companies aren't.
The real issues are on the low level plumbing end. How do you connect all the data silos you have. Are they even the right silos still? And once you fix that: how do you get organized around tapping into those. What guardrails do you need? How do you deal with compliance issues? Etc. You don't need to do a lot to get value back. Most people haven't gone there yet.
Mostly people actually already have and pay for the tools that would enable a lot more if only they knew how: ChatGPT, Codex, Manus, Perlexity Computer, Claude CoWork, etc.
What you are outlining is funny but true. The issue isn't money or tools but figuring out what to do with the tools you already bought.