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et1337 16 hours ago [-]
Folks have been saying “things are different now, the agents are now compounding success instead of error” for at least a year now, but I just don’t see it. I was lucky enough to receive a weeklong $50k per head AI training from the people saying these things, and one of their few helpful concrete recommendations was to constantly clear context all the time, to avoid things going off the rails.
However, I think finding security vulnerabilities is one use case where it doesn’t matter. Tokenmaxxing is absolutely effective for that. We as an industry are in the middle of adopting very expensive, complex continuous fuzzers.
liquicity 1 hours ago [-]
50k per head training and the largest takeaway was to clear context.. that is the "hello world" of using agents, insane.
jdiff 14 hours ago [-]
Even modern frontier models benefit so hugely from careful context pruning, maintenance, and rewriting to erase mistakes that it's astonishing to me that there are no tools centered around it. The one tool that used to have such a feature, Zed and its retroactively-named Text Threads, has now stripped itself of it.
RugnirViking 1 hours ago [-]
this! the back-and-forth chat interface where you can edit only your own messages, and only then to get a new response, is a terrible one, but I think favored by vendors because it helps them fight in vain against prompt injection. Custom harnesses and stuff are nice but incredibly time consuming to set up when all I want to do is like, see what the agent is reading, and editing out some irelevant nonsense side quest it went on, or trim some massive log file it read which filled 90% of its context. Theres no inherent reason behind some caching gains that these things must be strictly chronological - a response it gave me previously does not have to be part of the context now
seattle_spring 15 hours ago [-]
> I was lucky enough to receive a weeklong $50k per head AI training
wow! That sounds like an unbelievable grift. Who were they such that anyone could possibly think that's a worthwhile investment?
rezonant 7 hours ago [-]
Isn't that like a day worth of tokens?
codegladiator 6 hours ago [-]
10 days
manicennui 5 minutes ago [-]
This is little more than an ad for their services.
baconmania 19 hours ago [-]
The implication that tokenmaxxing was an intentional and thoughtfully considered approach rather than blind hype-following by an overpaid manager class who are too far removed from value to understand the downsides of LLMs is hysterical beyond belief.
SR2Z 18 hours ago [-]
I really don't understand this take. If you're a carpentry shop that just bought power tools for the first time and you're worried that your employees are sticking with hand tools because that's what they know, then you look for sawdust.
The goal isn't to have people work at converting wood into sawdust, the point is that if you wanna see if the tools are working you wanna see proof they're actually being used.
I'm sure there were some people cargo-culting this stuff, but suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting.
cyphar 17 hours ago [-]
Why would a carpentry shop buy hundreds of thousands of dollars of power tools without consulting with their employees to see what they actually need to get their job done more effectively? The logic of buying the tools then forcing the employees to use them "or else" is completely backwards in any sane world.
(Of course, we've all had bosses that went to some marketing seminar and come back having been tricked^Wsold into buying some wizz-bang widget that we need to now integrate because of a sunk-cost fallacy, but I thought everyone was on the same page that this is not how normal procurement was supposed to work.)
> the point is that if you wanna see if the tools are working you wanna see proof they're actually being used.
That is way too charitable, people were being fired based on these metrics and people were absolutely talking about token burn as being a metric for productivity (do I really need to link the Jensen Huang quote?). That isn't an indication of this hysteria being based on "just trying to see if the tools work".
If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
AussieWog93 12 hours ago [-]
>If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
I run a small business with two employees.
N=2 here, of course, but one of them will experiment with any new process you introduce (as well as plenty more that you don't!)
The other will keep doing what he's always been doing, even if it's frustrating and inefficient, unless you monitor him and force him to use the new process.
I could imagine most "normal employers" would understand that both type of person exists and, assuming you're getting good first impressions from group A, it's usually better off in the long run to shove the new process down group B's throat.
(This isn't to say that the "Group B" employee is less valuable or anything - he is more conscientious and reliable than anyone else we've ever hired - but just that different people need different management styles)
sevenseacat 2 hours ago [-]
In my experience, your first dev will have four thousand ideas and experiments on the go, and leave an absolute mess in their wake.
And your second will be struggling to clean up that mess while also getting their own work done.
Of course, you expect the same level of work from both of them, but because person two has to do a bunch of person one's work as well as their own, person one ends up looking better and gets praised by management.
> it's usually better off in the long run to shove the new process down group B's throat.
> (…) the "Group B" employee (…) is more conscientious and reliable than anyone else we've ever hired
If employee B is proving themselves to be valuable and reliable, then you should trust them to make the best decisions for how they’re going to go about their work and support them. Leave the door open for them to try different things, but no one likes having processes shoved down their throats (your words). All you’re doing is making them unhappy and more likely to leave to go work for someone who’ll value them like they deserve.
dijksterhuis 16 hours ago [-]
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
because that would require actually admitting that employees are the people in an organisation who are responsible for the success of that organisation, rather than the people higher up the org chart.
bitwize 13 hours ago [-]
And here we are. AI use mandates are a humiliation ritual, at least how I've seen them. Because it's not just a matter of making the employees use AI; public criticism or speaking about the drawbacks are also punished. It's get totally on board or get out; if you're not completely gung ho, despite the testimony of your lying eyes, maybe you don't have what it takes to work here, son. It's something they use as a shit test, just like the North Korean dogma that Kim Jong-il scored a perfect 18 holes-in-one every time he stepped on the course: are you willing to compromise your values, to the point of mouthing naked untruths, in total submission to the company's leadership?
SR2Z 11 hours ago [-]
Do you actually have a job? Do you talk to your coworkers?
This is an insane take. Plenty of people are critical of AI at my job despite a big push to use it. I find the comparison to NK distasteful, coming from someone who presumably is pretty well paid and can quit their job whenever they want.
If you're feeling humiliated... well, I don't think it's because your boss wants you to try AI.
hylaride 5 minutes ago [-]
Narcissists, non-violent sociopaths, and control freaks end up in managerial positions (often more likely than the general population). The pointy haired boss in Dilbert is a popular representation for a reason. We've all been subject to degrading and/or stupid management trends (see also: https://ibb.co/Kx46rqkg ), and while in the tech industry we had a golden age were the engineer was king, that's been chipped away even before AI became mainstream. Also, hyperbole is a thing. :-)
watwut 7 hours ago [-]
I had seen exact same dynamic as he describes. So yeah, he is speaking to people and coworkers. That is how he knows.
oblio 4 hours ago [-]
> Plenty of people are critical of AI at my job despite a big push to use it.
Are they critical to you and your 10 people team, aka a small circle or are they critical in the all hands Q&A in front of 500 employees?
woah 15 hours ago [-]
> Why would a carpentry shop buy hundreds of thousands of dollars of power tools without consulting with their employees to see what they actually need to get their job done more effectively?
Are you suggesting that changes to new production technologies are always driven bottom up by line workers? I'm guessing that historically that's rare.
oblio 4 hours ago [-]
Historically that rarely happens because industrial equipment is/was generally too expensive for the average worker to purchase on their own, plus workers usually have a budget of roughly 0 to buy extra tools, especially expensive ones.
But to give you an example, also roughly 0 companies made developers use Linux and still many developers choose it, so bottom up improvements happen in a decent chunk of cases. Nobody paid for PostgreSQL promotion. Or Python, etc.
TeMPOraL 4 hours ago [-]
> so bottom up improvements happen in a decent chunk of cases. Nobody paid for PostgreSQL promotion. Or Python, etc.
It does, but for better or worse, it's an anomaly. Even now, maybe nobody was paid for PostgreSQL or Python promotion, but modern OSS tools and programming languages usually have a business backing it. Linux, too, wasn't commercially promoted until it was; RedHat isn't exactly a charity after all.
Conversely, no one paid for initial AI promotion either - ChatGPT exploded organically after release, and for the first year or two, companies had a problem because a good chunk of their staff, including especially non-engineers, discovered just how useful it was and wanted to use it at work, casually violating every internal policy, bylaw and even regulatory policies about data sharing. The massive spend on promotion - including first-party spend - came later, but at that point it was already obvious ~everyone is going to be buying it.
I suppose bottom-up vs. top-down may be in part about how mature a technology and industry is.
JumpCrisscross 11 hours ago [-]
> The logic of buying the tools then forcing the employees to use them "or else" is completely backwards in any sane world
People are stubborn. A lot of productivity improvements had to be almost forced upon farmers, for example. Even when early adopters demonstrated the benefits, a decent fraction of them just didn’t want to change.
Lutger 2 hours ago [-]
And not few of those 'productivity improvements' for farmers have had disastrous consequences, even though what I think you are referring to has been implemented with far greater discernment and empirical basis than the current AI revolution.
People are stubborn, but sometimes for good reason. Let the stubborn people hold on to their practices, if the innovators are right they will eventually fold anyway.
JumpCrisscross 36 seconds ago [-]
> not few of those 'productivity improvements' for farmers have had disastrous consequences
Sure. Many have not. I’m thinking of stuff like ox-drawn and then mechanized ploughs, four- versus three-crop rotation, et cetera. The point is there is pushback regardless of benefit and even after it’s been demonstrated. Plenty of people are fine being comfortable. Which is fine. But it also explains why companies and societies with a nudge feature do better.
> if the innovators are right they will eventually fold anyway
Again, sure. If it’s their land, it gets acquired. If it’s your land they’re tilling, you get a say.
hnarn 3 hours ago [-]
> People are stubborn.
This is just a variant of the argument ”people don’t know what’s good for them”. You’re very close to the actual answer, which is that the aforementioned ”manager class” is simply convinced that they understand reality better than those below them, which is quite frankly absurd considering the fact that managers very rarely do any of the ”real work” that these tools supposedly make redundant, and yet they still believe themselves to understand the potential better.
>Why would a carpentry shop buy hundreds of thousands of dollars of power tools without consulting with their employees to see what they actually need to get their job done more effectively? T
What happens if employees say no power tools are needed and after a few months a competition shows up with power tools and hires a bunch of noobs and beating your production numbers and sales?
Your employees simply may leave the company and work for them and learn the new culture at this new competitor.
Is there any law which prevents people from moving between companies? No? Then the promoters of that company are going to do what they think is fit to keep them in business and stay competitive. Many times they'll be wrong, sometimes they'll be right.
watwut 7 hours ago [-]
> beating your production numbers and sales?
That did not happened.
HDThoreaun 6 hours ago [-]
Many, many hand tool shops were outcompeted by power tool users.
satvikpendem 14 hours ago [-]
Because people don't know what they want until they have and use it. Faster horses, etc. One can only really implement systemic change from the top down, as Moloch indicates.
TeMPOraL 15 hours ago [-]
> Why would a carpentry shop buy hundreds of thousands of dollars of power tools without consulting with their employees to see what they actually need to get their job done more effectively? The logic of buying the tools then forcing the employees to use them "or else" is completely backwards in any sane world.
For one, software tools are cheap, especially with OSS in the mix. You're buying one "tool" and paying for operational expenses that scale with total usage across all company.
But secondly, and more importantly, the "consulting" and discussing was done over the period of last 3 years, by ~1 year ago the high-level conclusions were pretty much locked in, the worthiness of the adoption was blindingly obvious at that point, so I can see why tokenmaxxing would be where this ended up, even though (here I disagree with the article a bit) the tools aren't at the "compounding correctness" stage just yet. It's really quite simple: the stick didn't work (telling people in increasingly direct ways to try using AI for stuff), so they tried the carrot.
$deity knows a good chunk of engineers will inadvertently fall for any trick that involves a scoreboard. That holds even when they're perfectly aware they're being tricked.
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
Again, they did that, they've been doing it continuously over past 3 years. Some people are excited, some people don't care, but some - a population that's definitely overrepresented in HN comments - just stubbornly refuse to try. Now that the answers are in, and they speak in favor of AI, the companies are doing what "any normal employer would": trying to get the stubborn employers to do their job they way their bosses want them to.
(In fact, normal employers would be more eager to fire people who keep refusing top-down instructions - but it's also obvious this technology is experimental; the models and harnesses get more powerful faster than people can learn to use them - so carrots make more sense than sticks in this transition period. Stubborn people begrudgingly using those tools offer an entirely unique perspective and explore use cases and approaches that you won't get from excited adopters.)
oblio 4 hours ago [-]
> the worthiness of the adoption was blindingly obvious at that point
Everything is so "blindingly obvious" yet nobody can point to ANY serious peer reviewed studies that prove it.
I'm patient, I'll wait.
TeMPOraL 3 hours ago [-]
You don't need peer reviewed studies to tell you water is wet.
Peer review is a technique to get evidence from data when SNR is low. It's not "science", it's just a technique. So is "throwing shit at a wall and seeing what sticks". Don't turn techniques into rituals, and science into religion.
TeriyakiBomb 5 hours ago [-]
To use your analogy again, it's kind of like the shop boss buying everyone a table saw and then saying "The best way to use the table saw is just experiment with it, it's the fastest and most accurate straight cut we can get - the future is table saw."
TeMPOraL 4 hours ago [-]
Yes, this is, in fact, how adoption of table saws and other such tools looked like, while they were still new tools. The basic form and function was established and its utility proven in both testing and early adopters, but as new kind of general tool on the market, every user from "early majority" was still writing the operating playbook for their specific shop conditions and kind of work they're doing.
So yes, it's a great analogy. We're right now well in the stage where bosses say, "evidence is in and conclusively shows this is useful for us, now the job is figuring out exactly how to work it into our particular business".
Lutger 2 hours ago [-]
> figuring out exactly how to work it into our particular business
This is the most crucial bit. Neither ramming it down developers throats nor rejecting it wholesale is particularly productive. You need the conservative people onboard as well, to discover critical edges and failure modes. Including their criticism in the adoption process instead of bluntly banning it is the smarter move. Of course, there will be a few people who just don't play, they will fold eventually or be let go.
jasondigitized 12 hours ago [-]
Because Japanese hand tools are objectively less efficient than power tools in a carpentry shop. The guys that want to use hand tools can go work in a boutique that charges a premium for that level of craftsmanship. If you told them to use power tools, no amount of utility would convince them to use them, with most of their justification being psychological. Also, "It is difficult to get a man to understand something, when his salary depends on his not understanding it."
SR2Z 11 hours ago [-]
> Why would a carpentry shop buy hundreds of thousands of dollars of power tools without consulting with their employees to see what they actually need to get their job done more effectively?
I mean, the difference in the metaphor is that we have pretty fully understood carpentry for many hundreds of years. We still find it difficult to write even simple software to address all our needs, as is evidenced by the insane pay in our industry. Carpenters can suggest tools because they know what's out there. The same was not true about LLMs a year ago.
> That is way too charitable, people were being fired based on these metrics
People get fired for all kinds of reasons including no reason at all. Oftentimes leadership even lies about the real reasons for firing people because they don't sound good!
I'm gonna be blunt: if you're in software and you refuse to use AI for moral reasons, I think you should be fired. There's being principled and there's being obstinate and the difference between the two is how well you can convince people that you _have_ principles. Most LLM-hating people fall short on this point, because
> do I really need to link the Jensen Huang quote?
Sure! Link it again, we all know it's highly immoral when shovel salesmen try to make you want shovels.
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
I do not like this HN take of "let's do this thing that works great in small companies and then just blindly pretend that it'll also work at the largest companies in the world!" No, this doesn't work at "normal companies" because you cannot "just ask" 30k+ employees what they want.
Employees, like EVERYONE ELSE, are resistant to change. If I, as CEO of a company, want to get my company to try Claude I have to measure tokens to see if it's getting used. That's it. There's no wave of delusion here.
ligne 5 minutes ago [-]
Have you considered using a more scientific metric, like the number of bugs being closed or the number of typewriter ribbons being used up?
HDThoreaun 16 hours ago [-]
The logic of trusting employees who are worried that power tools will replace them to utilize power tools effectively is completely backwards in any sane world. People don’t like change, sometimes it needs to be forced on them.
agentultra 16 hours ago [-]
Doubt. People brought in all kinds of web applications in the early Web 2.0 era because corporate IT was being too stingy (for a lot of reasons). People will find efficiencies on their job on their own. No need to denigrate them.
shimman 11 hours ago [-]
Yeah but if you can't attack the workers and make them hate their lives, are you even a good capitalist? Didn't Milton Friedman die for our bosses right to stomp on our faces in the pursuit of profit?
HDThoreaun 15 hours ago [-]
I don’t know, at my company at least tons of devs were holding out on ai usage until the token maxing stuff really started. It was beyond clear by that point that coding agents were a productivity multiplier.
agentultra 15 hours ago [-]
A lot of people believe that. Not a lot of evidence on the table for it (it’s not agent developers’ fault; empirical studies are expensive and rarely live up to scrutiny). Not sure it’s worth forcing people unless you like malicious compliance.
HDThoreaun 15 hours ago [-]
Well here’s where you can level valid complaints against management I think. “Move fast and break things” doesn’t line up super well with “wait for empirical studies to back up your suspicions”
agentultra 14 hours ago [-]
For sure. Just because the studies are incomplete or difficult doesn’t mean they’re useless. We still do unit testing and type systems continue to get more sophisticated and spread further because we believe they have an effect on quality and productivity regardless of the lack of evidence.
However it takes some taste in engineering and perhaps some mathematical sophistication to figure these things out. “Just use AI,” is not a very convincing argument either.
It’ll take time to sort out, I wager.
llama052 13 hours ago [-]
“Beyond clear” I wouldn’t say that confidently. Even now I’m not sure I agree with that, especially looking at it long term.
dijksterhuis 16 hours ago [-]
> who are worried that power tools will replace them
maybe, just maybe, it would have been a better idea to engage with employees first rather than posting on linkedin about how everyone is going to lose their jobs.
cos it's the kinds of people trying to force this stuff on employees that are the ones who have been shouting about that from the rooftops.
SR2Z 11 hours ago [-]
If you take LinkedIn at face value everyone who uses the Internet is a sociopath who lives for no purpose beyond maximizing shareholder value.
Seriously, some of the most deranged things I've ever read were by relatively normal people trying to promote themselves on LinkedIn.
What people SAY does not matter nearly as much as what everyone KNOWS and it's pretty damn clear that AI is never going to be able to replace humans in complex domains. Every time a frontier lab announces a breakthrough it's pretty obvious that the setup was more complicated than "hey chat prove the Riemann hypothesis."
The world is gonna need skilled human beings to drive LLMs, no matter how desperately some people like to pretend otherwise.
paulddraper 16 hours ago [-]
Because those power tools had just been invented and no one had experience with them.
Though in theory power tools are faster than hand tools.
JoshTriplett 16 hours ago [-]
So do a workshop on power tools, measure their efficacy and the quality of the result, do some demonstration videos on power tools, get people to compare, seek feedback on their usage. Don't count electricity and sawdust, or you'll find people getting very good at expensively turning blocks of wood into sawdust.
no-name-here 8 hours ago [-]
Is the idea that most stubborn employees would adopt AI if their company made videos showing internal metrics that AI is better?
> Don’t count electricity and sawdust
I agree that it seems wasteful, but is there some better way to accomplish it at the scale of hundreds, or hundreds of thousands, etc? I'm personally doubtful that stubborn employees would switch even if a video provided internal metrics, videos, etc.
JoshTriplett 7 hours ago [-]
Perhaps don't start out with the conclusion that it's obviously better and anyone rejecting it is just "stubborn".
TeMPOraL 6 hours ago [-]
Nobody started out with that conclusions. The tests and experiments and workshops and consulting with select employees you propose, were all done 2-3 years ago. Results are in, but a chunk of population decides to ignore them and obstinately continue believing and claiming that it doesn't work, which is a conclusion they started out with.
Yes, "results are in". They're all over the map, about productivity, about stress and churn, about trust, about public sentiment, etc.
But sure, if you want to tell people their productivity will be measured by token usage, they will certainly respond to that incentive by setting your checkbook on fire while they work on a job search.
If a company wants to provide AI accounts for people, along with guidance for usage and non-usage, that might well make sense for some jobs. It certainly makes sense for some uses. If they start measuring token usage, that's even worse than when companies tried to measure lines of code written.
oblio 4 hours ago [-]
> Results are in
Awesome, can you please share those results? Surely they would be all over Nature, Science, IEEE, etc.
TeMPOraL 3 hours ago [-]
Nature doesn't publish papers about water being wet either.
summa_tech 16 minutes ago [-]
As a matter of fact, Nature does regularly publish papers about wetting properties of water. In fact, it just published one last week, from Nature Physics:
Scientists find more or less everything very interesting, even (especially?) things that are supposedly self-evident. You can both make a big splash disproving self-evident things, and much can be learned from it.
oblio 2 hours ago [-]
What? The basic properties of water are scientifically defined as best we can. There is mathematical proof that 1+1=2. Do you think science starts from nuclear physics or differential equations?
We couldn't build any of this stuff (rockets, LLMs, heart medicine) if the foundation was ill defined.
I think it's the second time I run into you like this, Temporal. I wish HN had a way to classify you as an "AI booster" or equivalent.
TeMPOraL 59 minutes ago [-]
> What? The basic properties of water are scientifically defined as best we can. There is mathematical proof that 1+1=2. Do you think science starts from nuclear physics or differential equations?
Yes. There's a lot of interesting things science has to say about water, very specific claims that took a lot of effort to discover, precisely formulate, and reproduce.
We're not talking about those. The whole LLM discussion on HN, as well as in the wider industry, is still stuck at the state where a large (or vocal) group of people refuses to believe water is wet. Yes, there is a similar group that tries to sell water as miracle cure, I'm not denying it - IMO both perspectives are dumb and entirely detached from obvious observational evidence that you can collect for ~free at home in 15 minutes. Example will follow.
There exist the equivalent of foundational, detailed studies on LLMs, at every level of rigor imaginable (with a caveat, it's hard to rigorously prove anything useful in software engineering; it's still largely opinion-driven field). But they're not part of the overall "AI hypers/haters" dynamics.
> I wish HN had a way to classify you as an "AI booster" or equivalent.
You can take any of the LLMs and have it vibecode you a user script in under 5 minutes, than you then can paste into Greasemonkey/Tampermonkey, and voilà, you have me labeled as "AI booster" or filtered out.
In fact, let me help you, I'll time it. I opened chatgpt.com in incognito (to emulate being a rando free user), and put the following prompt in:
> I need a user script I can paste into Tampermonkey on my Firefox that will clearly label user named TeMPOraL with robot emoji and some silly emoji, so I never forget when reading their HackerNews comments that they're an unapologetic AI booster.
This is the promised empirical example. It doesn't prove everything, but it proves something, and it took, end-to-end, a total of 1 minute to perform just now. You can collect many such examples over a single day by just trying. People who keep saying AI is useless and a fad and can't do anything useful, obviously never bother with even that.
FYI: I'm not an AI booster. I like AI, and I find it useful, but I'm not going out of my way to boost it. I just enjoy this topic, but more importantly - and I remain consistent in this - I point out bullshit that doesn't agree with obvious observable reality.
EDIT: try the example yourself, and post whether it works for you too - if it does, it's technically a peer-reviewed, replicated study, but I doubt it'll convince any of the naysayers of anything.
EDIT2: I have plenty of negative things to say about LLM capabilities and how irresponsibly people use them, and I do occasionally write about this (mostly at work, these days), but most HN threads on AI are not on this level - not anymore. They used to be more reasonable back in GPT-4 days.
JoshTriplett 45 minutes ago [-]
> refuses to believe water is wet
At the risk of abusing the analogy further: many people aren't refusing to believe it's wet, they're observing that sulfuric acid is also "wet" and can look similar upon visual inspection, and there's a lot of harm coming along with the demonstrated capabilities, in addition to those capabilities themselves being fickle and inconsistent (not a desirable property for a good technology).
This isn't a problem of "doesn't know what AI can do"; yes, some people are misinformed, but you shouldn't dismiss all refusal to use AI as being misinformed. This is a problem of "knows what AI can do, and based on that informed position thinks it's terrible and should have careful guardrails around it".
oblio 50 minutes ago [-]
LLMs are useful.
They're not "3-4 trillion dollars in investments over 5 years" useful, nor "crammed into the throat of every employee on the planet, regardless of their actual job" useful.
The way they are pushed right now will lead to a very hard crash and probably lots of suffering.
Also, you need a more advanced prompt for Firefox on Android :-p
TeMPOraL 12 minutes ago [-]
> They're not "3-4 trillion dollars in investments over 5 years" useful
Why not? They're a general-purpose technology, in the same category as "software" or "electricity".
> nor "crammed into the throat of every employee on the planet, regardless of their actual job" useful
They're potentially useful for anything that can be fed into computers (VLMs lifted the "that can be expressed as text" limitation, visual and audio tokens are not a separate category to text tokens anymore). That touches every single job people do in some aspects. Even though LLMs can't do physical work for people, they're still able to help with directing it and teaching it.
"Cramming into the throat of every employee on the planet" was already covered by many comments here, and the article itself - it's about forcing the obstinate holdouts to at least try.
> Also, you need a more advanced prompt for Firefox on Android :-p
No I don't; literally copy-pasted it to Tampermonkey on my Firefox on Android just now, and it works there out-of-the-box too.
sevenseacat 2 hours ago [-]
source: just trust me bro
TeMPOraL 2 hours ago [-]
Source: it takes less effort to test this yourself than to write comments about it on Hacker News.
sevenseacat 2 hours ago [-]
We did, that's why we're so skeptical of your claim. The burden of proof here is on you, not on us.
trescenzi 17 hours ago [-]
The level of trust in leadership is remarkable. There’s reasonable ways to have people try power tools. Have one team use power tools and another hand tools and see the outcome.
The mandate was literally “the more sawdust you create the more money you’ll make”. Nothing of value is learned by that mandate. Sure it’ll make people use power tools but it won’t cause anyone to learn how to use them to make furniture.
They might understand the danger of bad metric but that doesn’t mean they aren’t victims of them. If there was intentionality here it was lazy as hell at best.
philipallstar 3 hours ago [-]
> If you're a carpentry shop that just bought power tools for the first time and you're worried that your employees are sticking with hand tools because that's what they know, then you look for sawdust.
But to make this work, you cannot tell your workers that you are looking for sawdust, because you just gave them tools that make sawdust very easily.
mh2266 17 hours ago [-]
> suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting.
from my time in FAANG... that seems about correct. Probably the people at the absolute top don't want to just pointlessly burn tokens, but pass that down the chain and eventually the rumor mill turns that into "tokens are an input for your performance review" and people start running Wiggum loops to fix minor typos or linters or something—especially if you do it at a time when every company seems to be doing layoffs.
marcta 3 hours ago [-]
Why would you look for sawdust? That's a waste product. You would motivate everyone to stop producing actual furniture, and just buy the biggest bits of wood to turn entirely into sawdust. Which is textbook Godhart's law.
This is what's happening here, you have people setting up two chatbots to churn useless tokens at each other, making only sawdust.
I contend that tokens per se are actually a waste product, or at least non-value add. The end user doesn't actually care how many tokens were used to make a thing. If you could get the same result with fewer tokens, that would be an improvement.
geophile 16 hours ago [-]
Bad managers, in general, grab a metric and then unthinkingly optimize it. I’ve never worked for FAANG, but I’d be surprised if they didn’t have bad managers too.
wlesieutre 15 hours ago [-]
Looking for sawdust is a far cry from having a leaderboard of who turned the most wood and electricity into dumpsters full of sawdust
Arainach 16 hours ago [-]
> the people who run FAANG don't understand the dangers of bad metrics is... interesting
They don't. They want some metric to support what they want to do and don't care about good metrics at all.
I've spent the vast majority of my career in FAANGs and it's been the pattern everywhere.
Right now my org has a senior director who is constantly battering managers to tell their reports to fill out the weekly surveys.
Why are the employees not filling out the surveys? Because instead of the old once a year large survey with questions about various levels (including local teams where management cared about the numbers and I could see the actions they took) we now get a survey every week with questions that are meaningless and I have no answer for.
"How does team X deliver on its priorities"?
Team X has O(10K) peoples and a barely countable infinity of projects. Most of which I don't know about and most of which I'm not supposed to know about since things are compartmentalized. So I don't know what team X's priorities are, I don't know how they deliver on them, and I never will know. Asking me and my colleagues is a waste of time and money.
...but none of that matters because the directors want "data" and they want a dashboard showing that we're all giving them "data".
16 hours ago [-]
hcs 16 hours ago [-]
> If you're a carpentry shop that just bought power tools for the first time and you're worried that your employees are sticking with hand tools because that's what they know, then you look for sawdust.
Or count the fingers, I guess. It's all fun and games until someone looses AI.
apsurd 17 hours ago [-]
> but suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting
You're far too charitable. Understanding has nothing to do with it. Big companies are too far insulated from bad metrics. Middle managers get away with anything and everything because their decisions are too far removed from reality. And they're nowhere to be seen when the other shoe drops. And they'll just leave to a promotion elsewhere if they stay and results are bad.
Everything is far removed from reality in bigco. So you get a bunch of theater and house-playing with "data-driven" posters up on the wall. It's a show that everyone is aware of and seemingly we all still attend.
bee_rider 14 hours ago [-]
The switch away from hand to power tools was a while ago but not, like, ancient history. In the era with fairly widespread literacy and records. Did this sort of check for sawdust thing actually happen?
eloisius 5 hours ago [-]
They didn’t measure sawdust accumulation. They measured the electricity bill.
lazide 14 hours ago [-]
I worked at FAANG. If anything, people are not nearly skeptical enough about how dumb it is with all this going on.
People are (in this analogy) building sawdust farms there.
surgical_fire 4 hours ago [-]
Or... If you are a carpentry shop owner, you should understand what exactly the power tools you acquired are good for, how and if they can actually be used by your employees for them to do their job.
This, obviously, presumes that the person managing this hypothetical carpentry shop knows what they are doing. It's almost laughable.
In truth the carpentry shop owner manages on vibes, has no idea what employees do and also doen't trust them, and tells employees he wants to see a lot of sawdust in the workshop floor.
hansmayer 16 hours ago [-]
[dead]
BobbyJo 18 hours ago [-]
Yeah, the rationalization after the fact is kind if absurd. IME, the reasoning underlying tokenmaxxing at the corporate level was "we need to leverage AI as much as possible as fast as possible because we're scared our competitors will find some leverage before us".
Definitely not some measured, long term, rational out of the gate.
tough 18 hours ago [-]
Worse, tokenmaxxing has been pushed by the labs hoping to charge those tokens by the pound on their API prices eventually, even if temporarily hiding such costs behind "highly subsidized plans" or frequent bug-induced "reset buttons"
Anon1096 17 hours ago [-]
I would wager most if not all of the tokenmaxxing was done on enterprise API priced plans, not subscription plans. You can't actually token"max" if you are limited in the amount of tokens you can use per 5 hours.
overfeed 11 hours ago [-]
Enterprise plans weren't usage-based until recently. Lots of enterprises were bait-and-switched by AI companies from flat per-seat fees, and now have to go on a token diet to rein-in budgets - which is the blog post's premise about tokenmaxxing being dead.
overfeed 11 hours ago [-]
The retconning is absurd. Companies CxOs's exhibit herd-line behaviors all the time: hiring scrum masters, mandatory return to office, and now tokenmaxxing. FOMO is a sufficient explanation of the behavior, any trend gaining momentum that they fear will give their competition an edge, they will reflexively force adoption with no further reasoning needed. There is no cost to boarding hype trains that go nowhere.
jmye 13 hours ago [-]
Eh, it’s less hysterical than the ever-pervasive belief among junior devs that they are the smartest people in the room and that all managers everywhere are dumb.
Though I understand that gets social validation from other people with no actual experience.
6 hours ago [-]
not_a_bot_4sho 10 hours ago [-]
> overpaid manager class
Ugh. Tell me you're early in career without telling me. Sophomoric take.
baconmania 5 hours ago [-]
Sorry to disappoint bud, I'm a manager of managers. Being able to look critically at your own tribe is one of the first skills you learn if you want to survive as someone telling other people how to do their jobs.
red_admiral 15 hours ago [-]
> Like, imagine if some serious business leader, like, idk, Mark Zuckerberg, decided to announce that Meta was going to burn money.
Like ... pivoting to the "metaverse" and changing the company name to show he's serious.
VulgarExigency 2 hours ago [-]
It's astounding to me that they looked at Second Life and really thought that was the future.
13 minutes ago [-]
aurareturn 19 hours ago [-]
Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
For companies that have measured performance based on token spend, they can now dial it back. Employees have learned to leverage AI for things they wouldn’t have prior. Now they know what’s possible and what’s not.
No one is stupid enough to always measure performance based on token spend and have unlimited budget. It was always a temporary thing to transition the employees to a new world.
Management felt like employees weren't leveraging AI fast enough. That's why in 2025, there were many mainstream articles about how CEOs were forcing their employees to use AI or get fired. Tokenmaxxing was just the other extreme. Companies will arrive at an equilibrium.
There's no need to overthink this.
Edit: One reply cited this X post as an example of why management needed to do this. Trying to change a company with hundreds/thousands/tens of thousands of employees is hard. You have to send one simple message at a time. https://x.com/danluu/status/1487228574608211969?lang=en
herval 19 hours ago [-]
having heard the arguments made by some VP + C-levels throughout the Tokenmaxxing Tulip Mania, I think the interpretation that those mandates were made intentionally for "forcing employees to start leveraging AI in meaningful ways" is too charitable.
Most companies focused entirely on doing "what everyone else is doing" at best or "to see if Programmer Joe can be as productive as the entire team so we can fire the rest".
And many indeed fired employees in droves because they were "underperforming in token spend".
ido 6 hours ago [-]
Some companies are badly managed (at least in some aspects). But it’s also true that some devs need to be pushed - sometimes forcibly - out of their comfort zone.
I’ve had multiple instances of taking months/years to get some devs to use a more sophisticated git client than GitHub Desktop (so they could properly do anything but the most trivial merges/rebases for example). Or to learn how to use the debugger instead of just printing/logging for debugging. For some of them getting them to seriously figure out how to better use AI required a bunch of repeated prodding.
Funnily enough a few years ago they enthusiastically jumped on copilot’s fancier autocomplete in VS Code, but getting them to really figure out how to get the most out of Claude Code required more pushing.
no-name-here 6 hours ago [-]
> many indeed fired employees in droves because they were "underperforming in token spend"
1. Source for that 4-word quotation? I googled it, but it appears you are the only person who has ever said it?
2. Even if you made up the quote, source for the claim that "many" "fired employees in droves" for "underperforming in token spend"? (Again, even if the companies never used those words, I'm still interested in the source for the claim about many companies firing employees in droves for low token use.)
dspillett 14 hours ago [-]
> Most companies focused entirely on doing "what everyone else is doing"
This is true of my current overlords. It slipped recently that the reason they went AI-nuts was that a competitor had announced going “AI first” and the market responded excitedly. Not because they thought it was a good idea: because the market got excited and they didn't want to get left behind.
This is quite a change as our market is financial services and I remember a time when we had to support decades old browsers (one large UK bank who I won't name here had IE6, and only IE6, on many of its user's machines until ~2017) and web servers because they refused to upgrade anything.
> "to see if Programmer Joe can be as productive as the entire team so we can fire the rest"
I'm not sure who Joe is in our outfit, but I'm certainly in the “the rest who are to be fired” set. I've been unhappy in dev & related for years so the AI revolution which I don't care for is where I'm consciously letting myself get left behind to find something else to do with my life. Haven't touched it. Was too late to claim one of the first tranche of Claude licences. And the second. Oops. Maybe I'll use AI in my next big adventure, or maybe my distaste for it all means I have a grand future waiting for me in the hospitality industry!
robocat 6 hours ago [-]
Isn't it easier to get a job when you already have a job?
There's some jobs I'd love to do, but I can't face the bullshit of tertiary education again.
Without some sort of ticket, job choices become more limited?
animuchan 14 hours ago [-]
This is probably the most charitable explanation humanly possible.
Surely for this specific example of managerial stupidity it just is, but I mean more generally, it's a beautiful posting.
I aspire to have this much misplaced belief in any humans at all, let alone CEOs.
vineyardmike 12 hours ago [-]
At my company, this was the explicitly stated and shared goal from management.
"We can't know all the parts of our business that AI can do a good job automating [because it's so new] but we also don't want to be the last to know and outcompeted along the way. Please throw AI at random parts of your job [and we're tracking this] so we can generate feedback from employees on where to invest in additional automation"
My company has since provided a ton of high-value little AI workflows, alongside a handful that didn't pan out. AI-assisted software development is a major change overall, but the general business-process updates from AI are a net-positive to me.
Scene_Cast2 18 hours ago [-]
I remember a story on HN from a while back. The idea is that the larger the org, the simpler the message and the tool has to be to reach everyone. The comment author was saying that as a junior, his company implemented a "tokenmaxxing" scheme for A/B testing - more tests, better for performance review. He, back then, thought it was stupid. However, it got the desired outcome of everyone being familiar with what experiments are and how to run them.
I agree, but for a completely different reason. A lot of executives simply chase trends. This was another trend they copied from each other. No reason to imagine they carefully studied the issue.
ryandrake 15 hours ago [-]
> Management felt like employees weren't leveraging AI fast enough.
If my productivity is in line with their expectations, I don’t understand why management cares what tools I’m using to do it. No employer ever told me to use emacs instead of vi, even though I’m 10x more productive in one vs the other. So why all of a sudden does management need to micromanage my tools?
IanCal 3 hours ago [-]
Expectations shift, and tools do matter.
Imagine you had a direct report. They were doing just fine, slightly better than a typical report. Then you found out they were writing all their code in notepad - no linting, no automated tests or live updates, no refactoring tools, no highlighting or any code search. They didn’t have any cross code searches and didn’t have any documentation. When they hit a problem, they’d churn away at it and never reach for docs, google or so.
Still, their performance is in line with what you’d expect from someone in their position.
Would getting them to try emacs, vi, linters, etc be micromanaging them? Do you think they’d perform better with them? They are performing in line with expectations for the role, so why bother with something you think would make them more efficient?
I’ve made this obviously over the top, and can hear already replies from other bemoaning my comparison while missing the point — tools do matter and if you genuinely believe that a developer could be more efficient working in a different way it makes sense to not only want them to try it but to actively fund that change. Hell, this is literally what we argue for in training! Spend money to make someone better at their job!
If you think AI tools make you worse or don’t and can’t help, then that’s one thing. But it makes sense for management if they think it might to spend money on it and to get you to try.
Not only this, but wasn’t everyone here shouting about how tokens were subsidised and it couldn’t last? If so, wasn’t the first half of this year a really excellent cheap time to do the maxxing?
moduspol 12 hours ago [-]
Because they're reading blog posts and listening to podcasts that increase their expectations of what your output should be.
aurareturn 14 hours ago [-]
Your productivity isn’t in line with their expectations. Maybe your immediate manager but not the executives. That’s why they are doing it.
bluefirebrand 14 hours ago [-]
Their expectations aren't based in reality so I'm not sure why anyone should care
Edit: I mean besides the obvious of "because they will fire you if you don't care"
But idk. They're aiming to fire me eventually and have AI do 100% of my job so meh. Fire me now instead of later.
lmm 6 hours ago [-]
> why all of a sudden does management need to micromanage my tools?
Because doing so increases the value of their stock options. They might privately think it's as dumb as you do, but apparently the stock market disagrees.
Andrex 15 hours ago [-]
It's FOMO all the way down.
clickety_clack 19 hours ago [-]
People in small teams with managers promoted from within could probably have had this in mind.
Big Corporate managers are much more likely to have felt the need to “do AI” from their VPs, who in turn got it from the executive team, who have probably been under fire to produce a coherent magical AI strategy that makes to company scale infinitely while reducing costs. In that environment it’s much more likely to be copy-and-pasted charts from Gartner and buzzwords overheard at conferences, combined with the hope that somebody somewhere will eventually turn it all into something that resembles forward movement.
linsomniac 19 hours ago [-]
That's a very good point. Our company has been very thrifty with our AI spend, until a few months ago the average employee had ~$50 of supported spend and I was trying to be an AI leader in the company and figure out what was and was not possible, I had a $100/mo spend (Claude $100 service costs $108/mo).
We are now seeing that Claude Code can do a LOT of heavy lifting in our day-to-day work, but the bulk of our employees are stuck cost-maxing and literally cannot "imagine how you are running into your session limits". "I'm fine with the $20/mo account."
There's a case for the cost-maxing has hurt our company.
sevenseacat 2 hours ago [-]
I'm in the boat of wondering how so many people run into session limits so often. I have never hit one, except once when Claude Design came out and I had fun generating a bunch of random things to see what it could do (not with the intent of actually using any of the generated designs/code, because it all sucked).
Aurornis 17 hours ago [-]
An interesting side effect of this spreading across social media is that even companies without token leaderboards were having problems with needless tokenmaxxing.
When everyone was reading about token leaderboards on all of their social media channels (include social news sites like Reddit and Hacker News) it created token anxiety even at companies that didn’t want a leaderboard. Programmers were afraid that their managers would be secretly ranking them based on token usage and they needed to pump up those numbers to avoid layoffs.
Once teams implemented token budgets in response it creates an ugly situation where a few people feel the need to use as many tokens as they can at the beginning of the budget window to stay ahead.
It’s really frustrating to have this phenomenon leak into a company that was never encouraging or looking for high token use.
socialcommenter 5 hours ago [-]
Interesting take - upvoted you. I'm not convinced it's been the optimal management strategy, but you're succinctly explaining what they have done, not what they should have done, and in that sense you have a good point.
Still leaves huge questions about ROI ($26tln of TAM, anyone???) and doesn't quell the concerns brought forward by AI detractors though.
danny_codes 18 hours ago [-]
Yeah there's no way that was the reason. I judge it to be a combination of FOMO and the big tech companies needing to pump demand for compute.
aurareturn 18 hours ago [-]
the big tech companies needing to pump demand for compute.
Demand is already so large that OpenAI, Anthropic, Meta, Google could not fill it. Tokenmaxxing for these companies strictly to pump fake demand is just plain wrong. The inference demand for these companies internally must be a drop in a bucket in overall inference demand.
This reminds me of the popular opinion on HN for return to office mandates as executives wanting to recover their real estate investments.
socialcommenter 5 hours ago [-]
Out of $13Bln of 2025 revenue, OpenAI received $867 million from one customer (less charitably, one bankroller), SoftBank. And $300 million from Microsoft[0]. That's more than a drop in the bucket, especially given that they're not the only players complicit in being both an investor and a customer.
Also are we sure it's all at arm's length? Barring a full audit, it's not possible to guarantee that there's no round-tripping or overstating of revenue. With Microsoft also being a provider for OpenAI, they could be creatively using set-off, or using SG&A, in order to overstate their revenue/gross margin/inference profit margin. I of course have no proof, extraordinary claims etc. etc. It's unlikely but we should at least debate the possibility. They have such a huge collective incentive to do it.
Were there cheaper and humane ways to get more employees to use AI? (yes). Did many people JUST burn tokens (goodbart law)? (Yes). Would people revert back to the mean? (I think yes). Do many professionals hate AI because of this push? (Yes). Was the org net productive?
I wish there was an independent body truly assessing the impact of big tech decisions and running counterfactuals. Instead of accepting nice stories like this as a given.
This is obviously wrong. Management has never cared about how engineers do their job. There's never been a push for any other productivity boosting technology: better languages, better editors, automated refactorings, paid code intelligence tools, etc. But suddenly AI comes along and the CEO says "all developers need to write code entirely with LLMs".
IanCal 4 hours ago [-]
This is absolute nonsense. Management in many places cares enormously about productivity. What’s been a bit different here is a huge claim of improvement other companies are seeing (so you’re going to be left behind), alongside some developers going off and doing this anyway sending proprietary code hither and thither, alongside some devs railing against the very concept of using it. It’s also a wildly powerful tool and how to use it hasn’t been as clear (where does it provide value, where does it not, what can and can’t it do) so experimentation is really important.
rendaw 3 hours ago [-]
I did not say that management doesn't care about productivity. To be clear though, I did mean to say upper management.
theahura 18 hours ago [-]
Independent of everything else, very interesting to see how polarized the comments are here
aurareturn 14 hours ago [-]
I'm a +26 on my post so far so it seems like there are a lot of people who agree with me but most replies disagree with me. I suppose this is the nature of online forums - that those who disagree will take the time to reply but those who agree rarely do.
vineyardmike 12 hours ago [-]
FWIW I agree with you, but it doesn't add much to the conversation to leave a comment saying so.
I also agree with the comment you're replying to as well - the vitriol and anger, along with the "this is just another blockchain bubble" type relies is really interesting. It's so surprising to see the variety of (negative) replies and beliefs people have, along with the general distaste/distrust for management. I guess it's also largely a sign of the times since a lot of ICs probably have a ton of anxiety about their career.
aurareturn 10 hours ago [-]
It’s about power and leverage. Software engineers were seen as “gods” in a tech company. Even the crappy ones. Over the last year, really 6 months, they lost great deal of that. Now they’re seen as costs, rather than assets.
This is especially true for the devs who take the code more seriously than the business that employs them. The technical PM who knows a bit of design are suddenly the kings of the company.
latexr 2 hours ago [-]
> I suppose this is the nature of online forums - that those who disagree will take the time to reply but those who agree rarely do.
Why would those who agree “take the time to reply”? To say what? “This”? “Agreed”? “This guy knows it”? Those comments don’t add anything of value. When you agree, it only makes sense to reply if you have something to say which wasn’t covered by the original argument.
CobrastanJorji 7 hours ago [-]
It's simpler. Management felt like employees weren't leveraging AI fast enough. They chose to measure "AI leveraging" in the easiest way they could: how many tokens each employee was using. Goodhart's Law ("When a measure becomes a target, it ceases to be a good measure") immediately triggered.
pier25 16 hours ago [-]
It seems really absurd that anyone would encourage or even force employees to burn more money to see if maybe something works.
IanCal 4 hours ago [-]
Why? This is literally what experimentation and prototyping is!
You spend money for a potential benefit. In this case it’s also a one off cost to find things that can save money over time.
chairmansteve 17 hours ago [-]
The smart move would have been to get lower level managers to assign specific employees to experiment with applying LLMs to their processes and report back. Then incorpoate the findings into their processes.
Instead there was FOMO mass hysteria. Now there is a backlash. And a lot of time and money wasted.
JV00 17 hours ago [-]
Letting everybody freely experiment for a while is much more effective than appointing somebody to do just that.
JoshTriplett 16 hours ago [-]
Freely experiment sure. But you're not doing an effective experiment if you tell people they'll be graded on how many tokens they use.
7 hours ago [-]
JV00 7 hours ago [-]
I agree with you, but I was answering parent who suggested appointing specific people.
qntmfred 18 hours ago [-]
might be the first time I've seen this reasonable and obviously correct interpretation of the last 6-12 months so directly and unapologetically stated. bravo
aurareturn 17 hours ago [-]
HN opinions are usually divided into individual contributor vs management battles. Usually the IC opinion is majority because most people here are likely ICs.
At the IC level, people don't sense the impending urgency for the overall business. They usually sense the urgency for themselves first. AI has completely changed the software industry in 6 months. We went from having AI write some code and copy/pasting to having AI write 99% of the code in 6 months. SaaS went from nice UX and CRUD code logic being a moat to these being nearly free.
Big software companies have to adapt to this new world or they will be outcompeted by smaller, newer, nimbler companies. That's what management is thinking. For ICs, they're usually thinking about their own jobs first.
Sharlin 12 hours ago [-]
It does not seem obviously correct to me.
Chu4eeno 19 hours ago [-]
The problem is that managers have no idea how this is supposed to help either, and just get told from above to use AI.
dgellow 18 hours ago [-]
You’re post rationalizating
16 hours ago [-]
jdiff 14 hours ago [-]
Did they see productivity gains that they're now calibrating for? Why have these productivity gains not been reflected externally in any measurable way?
gofreddygo 16 hours ago [-]
Its not _just_ that. Orgs aren't remotely sensible at measuring anything that isn't counted in dollars.
employees who are on the ai bandwagon are there for the free management attention.
Management is cooked because the damn market is hard, money is tight and they can't afford to fight the top down love and $$$ thrown at AI.
If you zoom out, all the real money spent on energy to keep AI alive isn't going to be held in nvidia stock for too long. it will burst, but its stupid to time it.
ngm7 16 hours ago [-]
> Orgs aren't remotely sensible at measuring anything that isn't counted in dollars.
A sensible organization machinery will move to optimize the metrics that make money. Often times figuring out said machinery takes iterations. Some of them are idiotic (ref: tokenmaxxing) but they are generally directionally correct.
arexxbifs 19 hours ago [-]
It really wasn't. It was a moronic move fueled by hype, implemented by the same type of incompetent business leaders who previously, to various extents, drank the blockchain and metaverse kool-aid.
There was demonstrably zero cost or consequence analysis, which is also why it was dialed back as soon as the (still) subsidized tokens became just slightly less subsidized, and the wise leaders realized they spent huge sums of money with no way of gauging ROI.
LLMs may have their use cases, but let's not make up free excuses for blithering idiots who, by any rights, should all be fired for cooking up money-burning policies that are textbook implementations of Goodhart's law.
Anyway, just needed to get that off my chest.
throwatdem12311 18 hours ago [-]
This is an insane level of cope.
The whole tokenmaxxing thing started because Jensen Huang said insane things like having a single engineer spend 250k in tokens or he’d fire him; and that OpenClaw was basically AGI.
> No one is stupid enough to always measure performance based on token spend and have unlimited budget.
Yes the people forcing these mandates absolutely are this stupid because that’s what people like Jensen Huang, Peter Steinberger and Boris Cherney were touting. Seriously have you ever actually talked to an average C-Level about AI? They are absolutely cooked.
You’re the one that’s overthinking it.
IanCal 3 hours ago [-]
> like having a single engineer spend 250k in tokens or he’d fire him;
That’s not quite what was said there, he’s budgeting half a devs salary as token spend in a podcast and that if he had a 500k engineer who spent 5k on it at the end of the year he’d go ape shit.
Now you can say that’s wild, and sure, but this is not a standard c suite exec talking it’s the ceo of Nvidia.
Even ignoring other hiring costs this is essentially an argument that Nvidia top engineers should get more than a 50% performance improvement with extremely heavy AI usage. To me, that doesn’t seem like such an enormous statement. For the head of a multi trillion dollar company entirely driven by AI sales arguing it gives a useful benefit to engineers isn’t that odd and betting on a 50% improvement within Nvidia seems kinda normal.
> Seriously have you ever actually talked to an average C-Level about AI?
Yes. Single digit percentage improvements over time would normally excite them, the idea of cappable cost performance improvements that last which your devs actually want to experiment with and a cultural and customer expectation that you’re doing this is pretty enticing. Particularly during a time when tokens were heavily subsidised - isn’t that the perfect time to do it? Now that has ended there’s a huge focus on roi.
jmye 13 hours ago [-]
How many “average C-levels” have you talked to? What, specifically, do you think that actually means? Do you think the average CMO and CTO are identical, and have identical profiles in this case?
Or are you just blathering about things you’ve never experienced because you met the “CEO” of a five person company once? I find grand proclamations by people who speak in TikTok absolutely laughable memeing.
otabdeveloper4 6 hours ago [-]
You don't need to meet these C-levels personally. They spread their insane hot AI takes everywhere and go out of their way to market this crap at conferences, etc.
TeMPOraL 6 hours ago [-]
Did you read those hot takes personally, or only had them reported on by your favorite YouTube/TikTok pundits? Hint: YouTubers and Tiktokers are in business, and that business is entertainment, and they're about as truthful as a fortune teller.
(Difference being, one of these groups is just lying about objective reality that's trivial to independently verify, the other one are just unlicensed therapists with thousand years old rituals).
18 hours ago [-]
catlifeonmars 19 hours ago [-]
Do you have a source for this?
> Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
> It was always a temporary thing to transition the employees to a new world.
Trying to understand your justification for rejecting Hanlon’s razor.
aurareturn 18 hours ago [-]
Do you have a source for this?
Yes, my own company's decision and logic.
nullsanity 18 hours ago [-]
[dead]
ab71e5 16 hours ago [-]
Did not read the twitter thread but I think it is a mix of some companies with above strategy and most others just cargo culting
Forgeties79 6 hours ago [-]
> Now they know what’s possible and what’s not.
They really don’t IMO. Hell most of the companies pushing these tools don’t even agree what LLMs are for or are capable of. Too many people are trying to use it to cut too many corners on their work (making more work for everyone else) or are using it to attempt things they don’t know how to do, which means they are incapable of vetting the results, (vibe coding anyone?) which means more instances of the first case or even getting hurt.
neonstatic 16 hours ago [-]
Thanks for posting the tweet, it was a very interesting read. A bit amusing knowing what's up with MS and Azure these days, but that's not the point!
flunhat 18 hours ago [-]
An insane re-writing of the last year of bullshit insanity. Good one.
watwut 18 hours ago [-]
> Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
Of course not. That is not what it achieved or could possibly achieve.
> Management felt like employees weren't leveraging AI fast enough.
I agree it was about their irrational feelings.
gsich 11 hours ago [-]
lines of code produced. similar dumb metric.
witx 19 hours ago [-]
You're naive, uninformed or turfing if you think companies are still not tokenmaxxing.
Also tokenmaxxing was never an intentional and smart strategy employed by companies like you say. It was a mix of fear of missing out, signaling to investors they were in on the hype and recouping investmenets in data centers
aurareturn 18 hours ago [-]
Yes, and Uber was trying to recuperate what investments in data centers?
Come on now. Let's not think that we are all smarter than management at these companies.
jdiff 14 hours ago [-]
Let us also not think that management is any smarter than any of us and is playing 5D chess games we couldn't comprehend. Notably, games that they also could not articulate when they were making these decisions.
aurareturn 8 hours ago [-]
It’s so easy to comprehend that even I was able to do it. I don’t think it’s 5D chess. More like checkers. They have dumb the message down just to get developers to try.
SecretDreams 18 hours ago [-]
> Let's not think that we are all smarter than management at these companies.
Outside of a few well run companies, it's hard not to feel like the average IC is smarter than their leadership.
therein 18 hours ago [-]
Your business will suffer greatly for your short-sightedness. But yeah, go imitate Uber, I am sure you will get just as big as they are this way. Everybody knows Uber's success comes from Apple Vision Pro making their developers oh so productive. You should go to the Apple store right now.
Your livelihood now depends on tokens remaining subsidized. How long do you think your engineers will continue to have the independent ability to maintain your codebase if the tokens got 20x more expensive?
Buy and sip that intelligence straight from the tap.
aurareturn 18 hours ago [-]
I never said go imitate Uber's strategy. I just challenged the person who claimed that these companies are only doing it to recuperate data center investments when Uber doesn't have any data center investments.
SecretDreams 18 hours ago [-]
CEOs are just as, if not moreso, susceptibility to fomo than everyone else!
gamblor956 16 hours ago [-]
No one is stupid enough to always measure performance based on token spend and have unlimited budget.
Accenture was.
SilverElfin 18 hours ago [-]
No. While what you’re saying makes sense, that’s not the logic behind the token max mentality. It’s simply lazy ineffective leaders who are bad at their jobs and don’t make rational decisions. They really did think spending more is somehow going to make their business better.
therein 18 hours ago [-]
> Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
No, it was a sinister way to manufacture your consent to cause cognitive atrophy in your employees so that you lose your ability to independently operate your business.
You'll come to realize this once they begin charging you more and more for tokens but you will probably not blame yourself for it.
no-name-here 6 hours ago [-]
> to cause cognitive atrophy in your employees so that you lose your ability to independently operate your business
The argument is tokenmaxxing was put in place by companies, with the goal of causing their employees to lose knowledge?
IanCal 3 hours ago [-]
This feels like it’s on the level of claiming conspiracy theories are invented by tin foil companies to sell more hats.
hansmayer 16 hours ago [-]
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lezojeda 16 hours ago [-]
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regexorcist 11 hours ago [-]
So this is the narrative now? Come on.
ambicapter 12 hours ago [-]
> That’s no longer true. We’ve entered a different regime, where spending more tokens generally results in better results. We call this “compounding correctness” — the more tokens you spend on getting a task correct, the more likely you’ll get a good outcome. We talked about this a bit at the last in person Agentics meetup:
Have we? Is it generally the case that the more tokens you spend, you better results you get? This take is so weird I suspect author somehow financially benefits from tokenmaxxing.
NateEag 12 hours ago [-]
> This take is so weird I suspect author somehow financially benefits from tokenmaxxing.
They might own a chunk of NVDA.
baddash 10 hours ago [-]
it's a huge oversimplification imo. it reminds me of someone worshipping LOC: more = better
dofm 14 hours ago [-]
This is like hell, if hell was being stuck on a really poorly-maintained uncomfortable rollercoaster forever.
jtrn 17 hours ago [-]
Better title more in line with the content of the article would have been: The reports of tokenmaxxing’s death are greatly exaggerated.
Pet peeve of mine is nonsensical usage of the x is dead, long live x.
nezi 16 hours ago [-]
The long live x is a lazy meme that draws attention that posters can use to skip thinking of an actual appropriate title.
theahura 16 hours ago [-]
that is a better title! Added it as a subheader
ElenaDaibunny 1 hours ago [-]
i think tokenmaxxing mostly comes from cloud pricing. once you're paying by the token, you naturally start caring about token counts. with local inference i barely think about it anymore.
theanonymousone 18 hours ago [-]
What is meant by a "loop" here? Just repeating the same prompt until you get the desired result? Are subsequent repetitions too close to each other?
> Just repeating the same prompt until you get the desired result?
Not necessarily the desired result, but until it's 'done', where the LLM itself is the judge on if the is the case according to the given criteria (often just an updated todo-list). One of those extremely simple 'harnesses' (if you can even call it that) was even named the 'Ralph Wiggum Loop' [1] to allude to the braindead-but-persistent tokenmaxxing it results in.
What I have been doing seems a bit different to what's described, but I always make sure to define how to know the task is done so the agent doesn't quit early. Usually this means telling it to to run the tests and type checks to ensure it runs without errors.
Otherwise they often do a first pass looks good enough but it doesn't actually work.
panarky 8 hours ago [-]
> Just repeating the same prompt ...
If you were tokenmaxxing you would understand.
TeMPOraL 5 hours ago [-]
Or if you were ever working with an approximation / search / optimization (really they're the same thing) algorithm that iteratively converges on a solution...
jsemrau 18 hours ago [-]
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kaizenite 16 hours ago [-]
This seems to happen with most big tech adoption in the first few years. The big data boom in the early 2010's had execs just buying up spark clusters and data lakes before they even had a clear analytical use case or governance.
fraywing 18 hours ago [-]
Brute forcing positive outcomes by spending more tokens until a happy path manifests does not solve the underlying comprehension (and liability) problem.
I fear a world where critical software is stood up with
increasingly non-human governed abstraction because it [seems like it] works.
Software engineers as the review terminal in a conveyor of business-led code mass production... coming to a company near you?
leptons 13 hours ago [-]
You're right, but you'd be lucky if a real human actually reviews any code. At my company, merging a PR still requires 2 humans to press "Approve" but I've been instructed that I don't need to read the PR, I only need to click "Approve". This is what 30 years of SWE experience is being used for now.
linsomniac 19 hours ago [-]
>I’ve basically never heard a business leader say that they were going to set a bunch of money on fire because it made them feel good.
Really? ~4 years ago our CEO hired a consultant to fly out several times to do team building exercises. We can't afford to do our 3-year server refresh cycle, but the consultant was no problem to pay.
We just recently had branding consultants come in and also spent thousands of dollars (AWS charges) on rebranding all our photos. We operate in a captive market, if you want to operate in our market you are required to subscribe to our service, and if you aren't in our market you can't subscribe. Branding at the end of the day drives 0 sales.
Heck, reminds me of the time a company I was working with hired a new CTO and one of the first things he did was as "server renaming scheme" using obscure (to the US-centric staff) city names from around the world (database servers are Swiss city names, web servers are Denmark, storage is Finland). We went from cattle naming to pet naming, for a CTO that lasted ~6 months.
In my experience company leadership is not quite as thrifty as this article likes to think they are.
cyphar 17 hours ago [-]
I'm also taken aback with how naive folks are about companies, they really seem to have bought the whole "capitalism is efficient" maxim hook, line, and sinker.
I really struggle to imagine how anyone in a corporate environment has managed to never run into obvious examples of waste like you describe (overpaid consultants and mandatory budgets are classic examples). Office Space came out 27 years ago and has a plotline making fun of overpaid "efficiency consultants" whose only job is to tell management to fire people.
sigbottle 16 hours ago [-]
Narratives are the most ungodly effective thing known to mankind, is the issue.
matheusmoreira 15 hours ago [-]
> "capitalism is efficient"
The precondition for that is competition. If some company has idiot managers that waste resources on idiotic things, they're supposed to be wiped out by the companies that are actually smart.
Capitalism requires constant evolutionary pressure and a sort of government directed corporation level eugenics program to constantly apply that pressure in order to function properly. Without that, it's just distributed fascism.
dijksterhuis 18 hours ago [-]
> database servers are Swiss city names, web servers are Denmark, storage is Finland
consider me officially triggered
hmry 15 hours ago [-]
why name your servers db-us-east-2 and web-de-stuttgart-3 when they could be called grindelwald and silkeborg?
15 hours ago [-]
EA-3167 19 hours ago [-]
To be fair leaders usually don't say that, they say a whole lot of nothing that means "We're gonna set money on fire because it makes me feel good."
Or more accurately, "Because this is good for my career."
natyoung 13 hours ago [-]
Studies have proved that you'd have been better off with fartmaxxing.
thousandflowers 3 hours ago [-]
The thing that most disconcerts me isn't the runtime pruning, it's the cold loading. Months ago, I added a few skills and MCPs to test them, partly in the frenzy of free shopping, but then I forgot about half of them.
So after I got tired of choosing by hand, and therefore also a bit blindly, I created a small tool that runs locally and analyzes conversations to tell you which skills, MCPs, or other things are always unused.
347 items never used · ~19354 dead tokens/session · ~$25.49/month A lot of ECC that I never used but always loaded.
If anyone's interested, I've put it on GitHub, thousandflowers/skillreaper.
Kiog-Aser 2 hours ago [-]
[flagged]
thousandflowers 2 hours ago [-]
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mvkel 16 hours ago [-]
At least it's being used. There are many examples of tech over-adoption, like building out capacity for 1M concurrent users, only to see 50.
leptons 13 hours ago [-]
Or like Meta spending $90 billion on "the metaverse" only to see 300,000 users at its peak.
That comes out to spending $300,000 per user.
koiueo 4 hours ago [-]
> Compounding correctness flips the calculus. If more token spend leads to better outcomes
Citation needed
behnamoh 19 hours ago [-]
Tokenmaxxing was never a thing to begin with. Just because a few companies did it doesn't mean it was a widespread phenomenon.
koiueo 4 hours ago [-]
Maxxing is just a catchy and imprecise name.
In my current company nobody forces you to use more tokens, but you're encouraged to write a 300 lines markdown skill.md which takes 8 minutes and costs 5 bucks to execute. That, instead of writing a 200 lines bash script doing all the same thing, but in a deterministic fashion, completing in under 5 seconds and costing 0 if you're not careful with rounding.
metaltyphoon 17 hours ago [-]
> Tokenmaxxing was never a thing to begin with.
Anecdote, I thought so too until the company I work just instated this where you have spend from 35-60K within 6 months. Insanity
aurareturn 18 hours ago [-]
Agreed. There is way too much noise made out of this from a handful of companies.
minraws 18 hours ago [-]
The issue is the companies doing it could spend billions on tokens and they have. I for one know that there are multiple Big Tech Fortune 500 companies that have burnt over 1B in tokens in a single quarter.
This is purely for coding and analogues.
GeoAtreides 5 hours ago [-]
cute easter egg on the story points showcase :)
gausswho 18 hours ago [-]
It's AI usage mandates now, but rather than focusing on how the current hot topic has ripped through the business world, often without benefit nor repercussions at leadership, I'd prefer to analyze the higher pattern. We've recently experienced such ripples as the metaverse, blockchain/nft/web3, 'the cloud' (and a minor wave of cloud gaming). There was even a teacup buzz of 'apis', oddly disconnected from the semantic web.
Why do such fever dreams occur at all? Are they getting more prevalent? More damaging? Do they jepaordize the global economy? Should they be regulated in some fashion?
I can't prove my case, but I think it's a symptom of media manipulation/consolidation, the 'fiduciary duty' delusion, and that shareholders can hold the puppet strings tighter than they used to. More and more, they place their sillytown bets and expect the plebs to dance to them.
m3kw9 9 hours ago [-]
If you are really engineering, you would really be tokenoptimizing for most quality per token.
impish9208 18 hours ago [-]
“Thing is dead, long live thing” is dead, long live “thing is dead, long live thing.”
dofm 14 hours ago [-]
‘“Thing is dead, long live thing” is all you need’ considered harmful
theahura 18 hours ago [-]
I do abuse this title format, guilty as charged
falcor84 17 hours ago [-]
Phoenixing considered harmful
cyphar 17 hours ago [-]
Would that be pheonixmaxxing or pheonixxing these days?
EGreg 16 hours ago [-]
I don’t think people who write these headlines understand that “long live the king” used to refer to the next king. Where is the next tokenmaxxing?
theahura 16 hours ago [-]
(its in the article, which predicts that there will be another round of tokenmaxxing with different underlying incentives)
Sharlin 11 hours ago [-]
It's actually used properly here.
IceHegel 17 hours ago [-]
Funny, now it's the management saying "Go be a bohemian, experiment, spend freely." and the employee saying, "Hold on, where's my ROI?"
chaboud 11 hours ago [-]
This is more likely the junior camper version of "not everything that counts can be counted, and not everything that can be counted counts."
In the early days of LLMs, we saw the classic hype-driven bi-modality of opinions. Folks were in the "fake news, fad" camp, or they were in the "omg, take over the world" camp.
Those of us closer to the space, with the awareness to know that there was some truth (and a lot of misjudgment) to go around, were in the middle of nowhere. When I co-wrote some driver code with Chat GPT, other engineers (and even one of our directors) told me to keep it quiet. At the same time I had directors and VPs asking me how we could accelerate adoption. For a while, I had access to a cheat code just because I had the audacity to not ask for permission. Folks were sure I would get in trouble for spending thousands per month in LLM operation, but a handful came along for the ride, burning tokens like firewood and learning along the way.
Tokenmaxxing is probably coming from at least a few things:
1. A course-correction for the practiced frugality that kept folks from jumping in and just learning at the ragged edge.
2. A willful and deliberate recognition that the best innovations in the later phases of a disruptive introduction often come from sparks of ideation in concentrations of activity. In other words, we don't know where good is, and we need to find it. (Charitable interpretation from the article)
3. Recognition that, even if they don't know why, leaders and product owners will get punished for not jumping in and, because of bullets 1 and 2, won't get punished for trying and missing. Even if they have no idea what they're doing, they're going to fake it until they make it (or slide into another job).
This last set is where the pain lives. An organization with healthy and increasing AI tool
usage will see elevated token counts, but so too will one using LLMs to rewrite wikipedia articles without the letter "m" to keep token counts high. These are pathological behaviors brought on by conflated metrics.
We had discussions about this in the early LLM days, where my old team was looking to ship new capabilities for older products. There was a lengthy VP-level discussion about getting to "80% usage" of the new system vs the old. Because the new system was a superset of the old, I eventually said "we can do that immediately, but it's a cost goal, where we're just aiming to make our business more expensive to operate, rather than a value goal for our users". We didn't adopt the target, but folks were understandably frustrated that they didn't have a straightforward way to measure and report progress.
Tokenmaxxing is, inevitably, a conflated goal, but it's what we have right now. Take advantage of the moment, learn, build, and keep an eye on levers for efficiency.
j45 19 hours ago [-]
Beyond getting momentum going for a cmpany, Tokenmaxxing is lighting money on fire.
The idea of tokenmaxxing reaches different companies in different waves, so it will be discovered in waves and outgrown in waves in companies and industries in their own cycle.
In the long run, tokenmaxxing is like drunken sailor spending. Scaling is almost always about a large component of efficiency, and lighting money on fire in the street can only last so long.
solenoid0937 16 hours ago [-]
Your comment implies no ROI on spent tokens. I get a lot more work done tokenmaxxing so the cost is negligible to me but YMMV. Of course there's no point in tokenmaxxing if you don't have enough work available to scale beyond yourself, or you're unable to use AI to do so.
I predict startups will continue to tokenmaxx while 40,000+ person companies will become a little more conservative.
However, I think finding security vulnerabilities is one use case where it doesn’t matter. Tokenmaxxing is absolutely effective for that. We as an industry are in the middle of adopting very expensive, complex continuous fuzzers.
wow! That sounds like an unbelievable grift. Who were they such that anyone could possibly think that's a worthwhile investment?
The goal isn't to have people work at converting wood into sawdust, the point is that if you wanna see if the tools are working you wanna see proof they're actually being used.
I'm sure there were some people cargo-culting this stuff, but suggesting that the people who run FAANG don't understand the dangers of bad metrics is... interesting.
(Of course, we've all had bosses that went to some marketing seminar and come back having been tricked^Wsold into buying some wizz-bang widget that we need to now integrate because of a sunk-cost fallacy, but I thought everyone was on the same page that this is not how normal procurement was supposed to work.)
> the point is that if you wanna see if the tools are working you wanna see proof they're actually being used.
That is way too charitable, people were being fired based on these metrics and people were absolutely talking about token burn as being a metric for productivity (do I really need to link the Jensen Huang quote?). That isn't an indication of this hysteria being based on "just trying to see if the tools work".
If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
I run a small business with two employees.
N=2 here, of course, but one of them will experiment with any new process you introduce (as well as plenty more that you don't!)
The other will keep doing what he's always been doing, even if it's frustrating and inefficient, unless you monitor him and force him to use the new process.
I could imagine most "normal employers" would understand that both type of person exists and, assuming you're getting good first impressions from group A, it's usually better off in the long run to shove the new process down group B's throat.
(This isn't to say that the "Group B" employee is less valuable or anything - he is more conscientious and reliable than anyone else we've ever hired - but just that different people need different management styles)
And your second will be struggling to clean up that mess while also getting their own work done.
Of course, you expect the same level of work from both of them, but because person two has to do a bunch of person one's work as well as their own, person one ends up looking better and gets praised by management.
I'm totally not bitter at all.
> it's usually better off in the long run to shove the new process down group B's throat.
> (…) the "Group B" employee (…) is more conscientious and reliable than anyone else we've ever hired
If employee B is proving themselves to be valuable and reliable, then you should trust them to make the best decisions for how they’re going to go about their work and support them. Leave the door open for them to try different things, but no one likes having processes shoved down their throats (your words). All you’re doing is making them unhappy and more likely to leave to go work for someone who’ll value them like they deserve.
because that would require actually admitting that employees are the people in an organisation who are responsible for the success of that organisation, rather than the people higher up the org chart.
This is an insane take. Plenty of people are critical of AI at my job despite a big push to use it. I find the comparison to NK distasteful, coming from someone who presumably is pretty well paid and can quit their job whenever they want.
If you're feeling humiliated... well, I don't think it's because your boss wants you to try AI.
Are they critical to you and your 10 people team, aka a small circle or are they critical in the all hands Q&A in front of 500 employees?
Are you suggesting that changes to new production technologies are always driven bottom up by line workers? I'm guessing that historically that's rare.
But to give you an example, also roughly 0 companies made developers use Linux and still many developers choose it, so bottom up improvements happen in a decent chunk of cases. Nobody paid for PostgreSQL promotion. Or Python, etc.
It does, but for better or worse, it's an anomaly. Even now, maybe nobody was paid for PostgreSQL or Python promotion, but modern OSS tools and programming languages usually have a business backing it. Linux, too, wasn't commercially promoted until it was; RedHat isn't exactly a charity after all.
Conversely, no one paid for initial AI promotion either - ChatGPT exploded organically after release, and for the first year or two, companies had a problem because a good chunk of their staff, including especially non-engineers, discovered just how useful it was and wanted to use it at work, casually violating every internal policy, bylaw and even regulatory policies about data sharing. The massive spend on promotion - including first-party spend - came later, but at that point it was already obvious ~everyone is going to be buying it.
I suppose bottom-up vs. top-down may be in part about how mature a technology and industry is.
People are stubborn. A lot of productivity improvements had to be almost forced upon farmers, for example. Even when early adopters demonstrated the benefits, a decent fraction of them just didn’t want to change.
People are stubborn, but sometimes for good reason. Let the stubborn people hold on to their practices, if the innovators are right they will eventually fold anyway.
Sure. Many have not. I’m thinking of stuff like ox-drawn and then mechanized ploughs, four- versus three-crop rotation, et cetera. The point is there is pushback regardless of benefit and even after it’s been demonstrated. Plenty of people are fine being comfortable. Which is fine. But it also explains why companies and societies with a nudge feature do better.
> if the innovators are right they will eventually fold anyway
Again, sure. If it’s their land, it gets acquired. If it’s your land they’re tilling, you get a say.
This is just a variant of the argument ”people don’t know what’s good for them”. You’re very close to the actual answer, which is that the aforementioned ”manager class” is simply convinced that they understand reality better than those below them, which is quite frankly absurd considering the fact that managers very rarely do any of the ”real work” that these tools supposedly make redundant, and yet they still believe themselves to understand the potential better.
Like when doctors insisted they didn't need to wash their hands (https://en.wikipedia.org/wiki/Ignaz_Semmelweis#Conflict_with...)
or "science advances one funeral at a time" (https://en.wikipedia.org/wiki/Planck%27s_principle)
What happens if employees say no power tools are needed and after a few months a competition shows up with power tools and hires a bunch of noobs and beating your production numbers and sales?
Your employees simply may leave the company and work for them and learn the new culture at this new competitor.
Is there any law which prevents people from moving between companies? No? Then the promoters of that company are going to do what they think is fit to keep them in business and stay competitive. Many times they'll be wrong, sometimes they'll be right.
That did not happened.
For one, software tools are cheap, especially with OSS in the mix. You're buying one "tool" and paying for operational expenses that scale with total usage across all company.
But secondly, and more importantly, the "consulting" and discussing was done over the period of last 3 years, by ~1 year ago the high-level conclusions were pretty much locked in, the worthiness of the adoption was blindingly obvious at that point, so I can see why tokenmaxxing would be where this ended up, even though (here I disagree with the article a bit) the tools aren't at the "compounding correctness" stage just yet. It's really quite simple: the stick didn't work (telling people in increasingly direct ways to try using AI for stuff), so they tried the carrot.
$deity knows a good chunk of engineers will inadvertently fall for any trick that involves a scoreboard. That holds even when they're perfectly aware they're being tricked.
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
Again, they did that, they've been doing it continuously over past 3 years. Some people are excited, some people don't care, but some - a population that's definitely overrepresented in HN comments - just stubbornly refuse to try. Now that the answers are in, and they speak in favor of AI, the companies are doing what "any normal employer would": trying to get the stubborn employers to do their job they way their bosses want them to.
(In fact, normal employers would be more eager to fire people who keep refusing top-down instructions - but it's also obvious this technology is experimental; the models and harnesses get more powerful faster than people can learn to use them - so carrots make more sense than sticks in this transition period. Stubborn people begrudgingly using those tools offer an entirely unique perspective and explore use cases and approaches that you won't get from excited adopters.)
Everything is so "blindingly obvious" yet nobody can point to ANY serious peer reviewed studies that prove it.
I'm patient, I'll wait.
Peer review is a technique to get evidence from data when SNR is low. It's not "science", it's just a technique. So is "throwing shit at a wall and seeing what sticks". Don't turn techniques into rituals, and science into religion.
So yes, it's a great analogy. We're right now well in the stage where bosses say, "evidence is in and conclusively shows this is useful for us, now the job is figuring out exactly how to work it into our particular business".
This is the most crucial bit. Neither ramming it down developers throats nor rejecting it wholesale is particularly productive. You need the conservative people onboard as well, to discover critical edges and failure modes. Including their criticism in the adoption process instead of bluntly banning it is the smarter move. Of course, there will be a few people who just don't play, they will fold eventually or be let go.
I mean, the difference in the metaphor is that we have pretty fully understood carpentry for many hundreds of years. We still find it difficult to write even simple software to address all our needs, as is evidenced by the insane pay in our industry. Carpenters can suggest tools because they know what's out there. The same was not true about LLMs a year ago.
> That is way too charitable, people were being fired based on these metrics
People get fired for all kinds of reasons including no reason at all. Oftentimes leadership even lies about the real reasons for firing people because they don't sound good!
I'm gonna be blunt: if you're in software and you refuse to use AI for moral reasons, I think you should be fired. There's being principled and there's being obstinate and the difference between the two is how well you can convince people that you _have_ principles. Most LLM-hating people fall short on this point, because
> do I really need to link the Jensen Huang quote?
Sure! Link it again, we all know it's highly immoral when shovel salesmen try to make you want shovels.
> If you want to see if the tools work, why don't you just ask your employees? Like any normal employer would?
I do not like this HN take of "let's do this thing that works great in small companies and then just blindly pretend that it'll also work at the largest companies in the world!" No, this doesn't work at "normal companies" because you cannot "just ask" 30k+ employees what they want.
Employees, like EVERYONE ELSE, are resistant to change. If I, as CEO of a company, want to get my company to try Claude I have to measure tokens to see if it's getting used. That's it. There's no wave of delusion here.
However it takes some taste in engineering and perhaps some mathematical sophistication to figure these things out. “Just use AI,” is not a very convincing argument either.
It’ll take time to sort out, I wager.
maybe, just maybe, it would have been a better idea to engage with employees first rather than posting on linkedin about how everyone is going to lose their jobs.
cos it's the kinds of people trying to force this stuff on employees that are the ones who have been shouting about that from the rooftops.
Seriously, some of the most deranged things I've ever read were by relatively normal people trying to promote themselves on LinkedIn.
What people SAY does not matter nearly as much as what everyone KNOWS and it's pretty damn clear that AI is never going to be able to replace humans in complex domains. Every time a frontier lab announces a breakthrough it's pretty obvious that the setup was more complicated than "hey chat prove the Riemann hypothesis."
The world is gonna need skilled human beings to drive LLMs, no matter how desperately some people like to pretend otherwise.
Though in theory power tools are faster than hand tools.
> Don’t count electricity and sawdust
I agree that it seems wasteful, but is there some better way to accomplish it at the scale of hundreds, or hundreds of thousands, etc? I'm personally doubtful that stubborn employees would switch even if a video provided internal metrics, videos, etc.
https://www.faros.ai/blog/ai-acceleration-whiplash-takeaways
Or these?
https://www.forbes.com/councils/forbestechcouncil/2026/03/16...
Or these?
https://poll.qu.edu/poll-release?releaseid=3955
Yes, "results are in". They're all over the map, about productivity, about stress and churn, about trust, about public sentiment, etc.
But sure, if you want to tell people their productivity will be measured by token usage, they will certainly respond to that incentive by setting your checkbook on fire while they work on a job search.
If a company wants to provide AI accounts for people, along with guidance for usage and non-usage, that might well make sense for some jobs. It certainly makes sense for some uses. If they start measuring token usage, that's even worse than when companies tried to measure lines of code written.
Awesome, can you please share those results? Surely they would be all over Nature, Science, IEEE, etc.
https://www.nature.com/articles/s41567-026-03299-z
Scientists find more or less everything very interesting, even (especially?) things that are supposedly self-evident. You can both make a big splash disproving self-evident things, and much can be learned from it.
We couldn't build any of this stuff (rockets, LLMs, heart medicine) if the foundation was ill defined.
I think it's the second time I run into you like this, Temporal. I wish HN had a way to classify you as an "AI booster" or equivalent.
Yes. There's a lot of interesting things science has to say about water, very specific claims that took a lot of effort to discover, precisely formulate, and reproduce.
We're not talking about those. The whole LLM discussion on HN, as well as in the wider industry, is still stuck at the state where a large (or vocal) group of people refuses to believe water is wet. Yes, there is a similar group that tries to sell water as miracle cure, I'm not denying it - IMO both perspectives are dumb and entirely detached from obvious observational evidence that you can collect for ~free at home in 15 minutes. Example will follow.
There exist the equivalent of foundational, detailed studies on LLMs, at every level of rigor imaginable (with a caveat, it's hard to rigorously prove anything useful in software engineering; it's still largely opinion-driven field). But they're not part of the overall "AI hypers/haters" dynamics.
> I wish HN had a way to classify you as an "AI booster" or equivalent.
You can take any of the LLMs and have it vibecode you a user script in under 5 minutes, than you then can paste into Greasemonkey/Tampermonkey, and voilà, you have me labeled as "AI booster" or filtered out.
In fact, let me help you, I'll time it. I opened chatgpt.com in incognito (to emulate being a rando free user), and put the following prompt in:
> I need a user script I can paste into Tampermonkey on my Firefox that will clearly label user named TeMPOraL with robot emoji and some silly emoji, so I never forget when reading their HackerNews comments that they're an unapologetic AI booster.
Got back this script in under 10 seconds: https://pastebin.com/akEchvHd. Tested it, works out of the box.
This is the promised empirical example. It doesn't prove everything, but it proves something, and it took, end-to-end, a total of 1 minute to perform just now. You can collect many such examples over a single day by just trying. People who keep saying AI is useless and a fad and can't do anything useful, obviously never bother with even that.
FYI: I'm not an AI booster. I like AI, and I find it useful, but I'm not going out of my way to boost it. I just enjoy this topic, but more importantly - and I remain consistent in this - I point out bullshit that doesn't agree with obvious observable reality.
EDIT: try the example yourself, and post whether it works for you too - if it does, it's technically a peer-reviewed, replicated study, but I doubt it'll convince any of the naysayers of anything.
EDIT2: I have plenty of negative things to say about LLM capabilities and how irresponsibly people use them, and I do occasionally write about this (mostly at work, these days), but most HN threads on AI are not on this level - not anymore. They used to be more reasonable back in GPT-4 days.
At the risk of abusing the analogy further: many people aren't refusing to believe it's wet, they're observing that sulfuric acid is also "wet" and can look similar upon visual inspection, and there's a lot of harm coming along with the demonstrated capabilities, in addition to those capabilities themselves being fickle and inconsistent (not a desirable property for a good technology).
This isn't a problem of "doesn't know what AI can do"; yes, some people are misinformed, but you shouldn't dismiss all refusal to use AI as being misinformed. This is a problem of "knows what AI can do, and based on that informed position thinks it's terrible and should have careful guardrails around it".
They're not "3-4 trillion dollars in investments over 5 years" useful, nor "crammed into the throat of every employee on the planet, regardless of their actual job" useful.
The way they are pushed right now will lead to a very hard crash and probably lots of suffering. Also, you need a more advanced prompt for Firefox on Android :-p
Why not? They're a general-purpose technology, in the same category as "software" or "electricity".
> nor "crammed into the throat of every employee on the planet, regardless of their actual job" useful
They're potentially useful for anything that can be fed into computers (VLMs lifted the "that can be expressed as text" limitation, visual and audio tokens are not a separate category to text tokens anymore). That touches every single job people do in some aspects. Even though LLMs can't do physical work for people, they're still able to help with directing it and teaching it.
"Cramming into the throat of every employee on the planet" was already covered by many comments here, and the article itself - it's about forcing the obstinate holdouts to at least try.
> Also, you need a more advanced prompt for Firefox on Android :-p
No I don't; literally copy-pasted it to Tampermonkey on my Firefox on Android just now, and it works there out-of-the-box too.
The mandate was literally “the more sawdust you create the more money you’ll make”. Nothing of value is learned by that mandate. Sure it’ll make people use power tools but it won’t cause anyone to learn how to use them to make furniture.
They might understand the danger of bad metric but that doesn’t mean they aren’t victims of them. If there was intentionality here it was lazy as hell at best.
But to make this work, you cannot tell your workers that you are looking for sawdust, because you just gave them tools that make sawdust very easily.
from my time in FAANG... that seems about correct. Probably the people at the absolute top don't want to just pointlessly burn tokens, but pass that down the chain and eventually the rumor mill turns that into "tokens are an input for your performance review" and people start running Wiggum loops to fix minor typos or linters or something—especially if you do it at a time when every company seems to be doing layoffs.
This is what's happening here, you have people setting up two chatbots to churn useless tokens at each other, making only sawdust.
I contend that tokens per se are actually a waste product, or at least non-value add. The end user doesn't actually care how many tokens were used to make a thing. If you could get the same result with fewer tokens, that would be an improvement.
They don't. They want some metric to support what they want to do and don't care about good metrics at all.
I've spent the vast majority of my career in FAANGs and it's been the pattern everywhere.
Right now my org has a senior director who is constantly battering managers to tell their reports to fill out the weekly surveys.
Why are the employees not filling out the surveys? Because instead of the old once a year large survey with questions about various levels (including local teams where management cared about the numbers and I could see the actions they took) we now get a survey every week with questions that are meaningless and I have no answer for.
"How does team X deliver on its priorities"?
Team X has O(10K) peoples and a barely countable infinity of projects. Most of which I don't know about and most of which I'm not supposed to know about since things are compartmentalized. So I don't know what team X's priorities are, I don't know how they deliver on them, and I never will know. Asking me and my colleagues is a waste of time and money.
...but none of that matters because the directors want "data" and they want a dashboard showing that we're all giving them "data".
Or count the fingers, I guess. It's all fun and games until someone looses AI.
You're far too charitable. Understanding has nothing to do with it. Big companies are too far insulated from bad metrics. Middle managers get away with anything and everything because their decisions are too far removed from reality. And they're nowhere to be seen when the other shoe drops. And they'll just leave to a promotion elsewhere if they stay and results are bad.
Everything is far removed from reality in bigco. So you get a bunch of theater and house-playing with "data-driven" posters up on the wall. It's a show that everyone is aware of and seemingly we all still attend.
People are (in this analogy) building sawdust farms there.
This, obviously, presumes that the person managing this hypothetical carpentry shop knows what they are doing. It's almost laughable.
In truth the carpentry shop owner manages on vibes, has no idea what employees do and also doen't trust them, and tells employees he wants to see a lot of sawdust in the workshop floor.
Definitely not some measured, long term, rational out of the gate.
Though I understand that gets social validation from other people with no actual experience.
Ugh. Tell me you're early in career without telling me. Sophomoric take.
Like ... pivoting to the "metaverse" and changing the company name to show he's serious.
For companies that have measured performance based on token spend, they can now dial it back. Employees have learned to leverage AI for things they wouldn’t have prior. Now they know what’s possible and what’s not.
No one is stupid enough to always measure performance based on token spend and have unlimited budget. It was always a temporary thing to transition the employees to a new world.
Management felt like employees weren't leveraging AI fast enough. That's why in 2025, there were many mainstream articles about how CEOs were forcing their employees to use AI or get fired. Tokenmaxxing was just the other extreme. Companies will arrive at an equilibrium.
There's no need to overthink this.
Edit: One reply cited this X post as an example of why management needed to do this. Trying to change a company with hundreds/thousands/tens of thousands of employees is hard. You have to send one simple message at a time. https://x.com/danluu/status/1487228574608211969?lang=en
Most companies focused entirely on doing "what everyone else is doing" at best or "to see if Programmer Joe can be as productive as the entire team so we can fire the rest".
And many indeed fired employees in droves because they were "underperforming in token spend".
I’ve had multiple instances of taking months/years to get some devs to use a more sophisticated git client than GitHub Desktop (so they could properly do anything but the most trivial merges/rebases for example). Or to learn how to use the debugger instead of just printing/logging for debugging. For some of them getting them to seriously figure out how to better use AI required a bunch of repeated prodding.
Funnily enough a few years ago they enthusiastically jumped on copilot’s fancier autocomplete in VS Code, but getting them to really figure out how to get the most out of Claude Code required more pushing.
1. Source for that 4-word quotation? I googled it, but it appears you are the only person who has ever said it?
2. Even if you made up the quote, source for the claim that "many" "fired employees in droves" for "underperforming in token spend"? (Again, even if the companies never used those words, I'm still interested in the source for the claim about many companies firing employees in droves for low token use.)
This is true of my current overlords. It slipped recently that the reason they went AI-nuts was that a competitor had announced going “AI first” and the market responded excitedly. Not because they thought it was a good idea: because the market got excited and they didn't want to get left behind.
This is quite a change as our market is financial services and I remember a time when we had to support decades old browsers (one large UK bank who I won't name here had IE6, and only IE6, on many of its user's machines until ~2017) and web servers because they refused to upgrade anything.
> "to see if Programmer Joe can be as productive as the entire team so we can fire the rest"
I'm not sure who Joe is in our outfit, but I'm certainly in the “the rest who are to be fired” set. I've been unhappy in dev & related for years so the AI revolution which I don't care for is where I'm consciously letting myself get left behind to find something else to do with my life. Haven't touched it. Was too late to claim one of the first tranche of Claude licences. And the second. Oops. Maybe I'll use AI in my next big adventure, or maybe my distaste for it all means I have a grand future waiting for me in the hospitality industry!
There's some jobs I'd love to do, but I can't face the bullshit of tertiary education again.
Without some sort of ticket, job choices become more limited?
Surely for this specific example of managerial stupidity it just is, but I mean more generally, it's a beautiful posting.
I aspire to have this much misplaced belief in any humans at all, let alone CEOs.
"We can't know all the parts of our business that AI can do a good job automating [because it's so new] but we also don't want to be the last to know and outcompeted along the way. Please throw AI at random parts of your job [and we're tracking this] so we can generate feedback from employees on where to invest in additional automation"
My company has since provided a ton of high-value little AI workflows, alongside a handful that didn't pan out. AI-assisted software development is a major change overall, but the general business-process updates from AI are a net-positive to me.
I agree, but for a completely different reason. A lot of executives simply chase trends. This was another trend they copied from each other. No reason to imagine they carefully studied the issue.
If my productivity is in line with their expectations, I don’t understand why management cares what tools I’m using to do it. No employer ever told me to use emacs instead of vi, even though I’m 10x more productive in one vs the other. So why all of a sudden does management need to micromanage my tools?
Imagine you had a direct report. They were doing just fine, slightly better than a typical report. Then you found out they were writing all their code in notepad - no linting, no automated tests or live updates, no refactoring tools, no highlighting or any code search. They didn’t have any cross code searches and didn’t have any documentation. When they hit a problem, they’d churn away at it and never reach for docs, google or so.
Still, their performance is in line with what you’d expect from someone in their position.
Would getting them to try emacs, vi, linters, etc be micromanaging them? Do you think they’d perform better with them? They are performing in line with expectations for the role, so why bother with something you think would make them more efficient?
I’ve made this obviously over the top, and can hear already replies from other bemoaning my comparison while missing the point — tools do matter and if you genuinely believe that a developer could be more efficient working in a different way it makes sense to not only want them to try it but to actively fund that change. Hell, this is literally what we argue for in training! Spend money to make someone better at their job!
If you think AI tools make you worse or don’t and can’t help, then that’s one thing. But it makes sense for management if they think it might to spend money on it and to get you to try.
Not only this, but wasn’t everyone here shouting about how tokens were subsidised and it couldn’t last? If so, wasn’t the first half of this year a really excellent cheap time to do the maxxing?
Edit: I mean besides the obvious of "because they will fire you if you don't care"
But idk. They're aiming to fire me eventually and have AI do 100% of my job so meh. Fire me now instead of later.
Because doing so increases the value of their stock options. They might privately think it's as dumb as you do, but apparently the stock market disagrees.
Big Corporate managers are much more likely to have felt the need to “do AI” from their VPs, who in turn got it from the executive team, who have probably been under fire to produce a coherent magical AI strategy that makes to company scale infinitely while reducing costs. In that environment it’s much more likely to be copy-and-pasted charts from Gartner and buzzwords overheard at conferences, combined with the hope that somebody somewhere will eventually turn it all into something that resembles forward movement.
We are now seeing that Claude Code can do a LOT of heavy lifting in our day-to-day work, but the bulk of our employees are stuck cost-maxing and literally cannot "imagine how you are running into your session limits". "I'm fine with the $20/mo account."
There's a case for the cost-maxing has hurt our company.
When everyone was reading about token leaderboards on all of their social media channels (include social news sites like Reddit and Hacker News) it created token anxiety even at companies that didn’t want a leaderboard. Programmers were afraid that their managers would be secretly ranking them based on token usage and they needed to pump up those numbers to avoid layoffs.
Once teams implemented token budgets in response it creates an ugly situation where a few people feel the need to use as many tokens as they can at the beginning of the budget window to stay ahead.
It’s really frustrating to have this phenomenon leak into a company that was never encouraging or looking for high token use.
Still leaves huge questions about ROI ($26tln of TAM, anyone???) and doesn't quell the concerns brought forward by AI detractors though.
This reminds me of the popular opinion on HN for return to office mandates as executives wanting to recover their real estate investments.
Also are we sure it's all at arm's length? Barring a full audit, it's not possible to guarantee that there's no round-tripping or overstating of revenue. With Microsoft also being a provider for OpenAI, they could be creatively using set-off, or using SG&A, in order to overstate their revenue/gross margin/inference profit margin. I of course have no proof, extraordinary claims etc. etc. It's unlikely but we should at least debate the possibility. They have such a huge collective incentive to do it.
[0]: https://www.wheresyoured.at/exclusive-openai-financials/ (no affiliation with the website owner, who has a unique bias in this)
I wish there was an independent body truly assessing the impact of big tech decisions and running counterfactuals. Instead of accepting nice stories like this as a given.
Using Claude, I recently tried to do something similar for the Covid hiring spree: https://claude.ai/public/artifacts/21bba86a-ad5d-439c-861d-0...
I also agree with the comment you're replying to as well - the vitriol and anger, along with the "this is just another blockchain bubble" type relies is really interesting. It's so surprising to see the variety of (negative) replies and beliefs people have, along with the general distaste/distrust for management. I guess it's also largely a sign of the times since a lot of ICs probably have a ton of anxiety about their career.
This is especially true for the devs who take the code more seriously than the business that employs them. The technical PM who knows a bit of design are suddenly the kings of the company.
Why would those who agree “take the time to reply”? To say what? “This”? “Agreed”? “This guy knows it”? Those comments don’t add anything of value. When you agree, it only makes sense to reply if you have something to say which wasn’t covered by the original argument.
You spend money for a potential benefit. In this case it’s also a one off cost to find things that can save money over time.
Instead there was FOMO mass hysteria. Now there is a backlash. And a lot of time and money wasted.
At the IC level, people don't sense the impending urgency for the overall business. They usually sense the urgency for themselves first. AI has completely changed the software industry in 6 months. We went from having AI write some code and copy/pasting to having AI write 99% of the code in 6 months. SaaS went from nice UX and CRUD code logic being a moat to these being nearly free.
Big software companies have to adapt to this new world or they will be outcompeted by smaller, newer, nimbler companies. That's what management is thinking. For ICs, they're usually thinking about their own jobs first.
employees who are on the ai bandwagon are there for the free management attention.
Management is cooked because the damn market is hard, money is tight and they can't afford to fight the top down love and $$$ thrown at AI.
If you zoom out, all the real money spent on energy to keep AI alive isn't going to be held in nvidia stock for too long. it will burst, but its stupid to time it.
A sensible organization machinery will move to optimize the metrics that make money. Often times figuring out said machinery takes iterations. Some of them are idiotic (ref: tokenmaxxing) but they are generally directionally correct.
There was demonstrably zero cost or consequence analysis, which is also why it was dialed back as soon as the (still) subsidized tokens became just slightly less subsidized, and the wise leaders realized they spent huge sums of money with no way of gauging ROI.
LLMs may have their use cases, but let's not make up free excuses for blithering idiots who, by any rights, should all be fired for cooking up money-burning policies that are textbook implementations of Goodhart's law.
Anyway, just needed to get that off my chest.
The whole tokenmaxxing thing started because Jensen Huang said insane things like having a single engineer spend 250k in tokens or he’d fire him; and that OpenClaw was basically AGI.
> No one is stupid enough to always measure performance based on token spend and have unlimited budget.
Yes the people forcing these mandates absolutely are this stupid because that’s what people like Jensen Huang, Peter Steinberger and Boris Cherney were touting. Seriously have you ever actually talked to an average C-Level about AI? They are absolutely cooked.
You’re the one that’s overthinking it.
That’s not quite what was said there, he’s budgeting half a devs salary as token spend in a podcast and that if he had a 500k engineer who spent 5k on it at the end of the year he’d go ape shit.
Now you can say that’s wild, and sure, but this is not a standard c suite exec talking it’s the ceo of Nvidia.
Even ignoring other hiring costs this is essentially an argument that Nvidia top engineers should get more than a 50% performance improvement with extremely heavy AI usage. To me, that doesn’t seem like such an enormous statement. For the head of a multi trillion dollar company entirely driven by AI sales arguing it gives a useful benefit to engineers isn’t that odd and betting on a 50% improvement within Nvidia seems kinda normal.
> Seriously have you ever actually talked to an average C-Level about AI?
Yes. Single digit percentage improvements over time would normally excite them, the idea of cappable cost performance improvements that last which your devs actually want to experiment with and a cultural and customer expectation that you’re doing this is pretty enticing. Particularly during a time when tokens were heavily subsidised - isn’t that the perfect time to do it? Now that has ended there’s a huge focus on roi.
Or are you just blathering about things you’ve never experienced because you met the “CEO” of a five person company once? I find grand proclamations by people who speak in TikTok absolutely laughable memeing.
(Difference being, one of these groups is just lying about objective reality that's trivial to independently verify, the other one are just unlicensed therapists with thousand years old rituals).
> Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.
> It was always a temporary thing to transition the employees to a new world.
Trying to understand your justification for rejecting Hanlon’s razor.
They really don’t IMO. Hell most of the companies pushing these tools don’t even agree what LLMs are for or are capable of. Too many people are trying to use it to cut too many corners on their work (making more work for everyone else) or are using it to attempt things they don’t know how to do, which means they are incapable of vetting the results, (vibe coding anyone?) which means more instances of the first case or even getting hurt.
Of course not. That is not what it achieved or could possibly achieve.
> Management felt like employees weren't leveraging AI fast enough.
I agree it was about their irrational feelings.
Also tokenmaxxing was never an intentional and smart strategy employed by companies like you say. It was a mix of fear of missing out, signaling to investors they were in on the hype and recouping investmenets in data centers
Come on now. Let's not think that we are all smarter than management at these companies.
Outside of a few well run companies, it's hard not to feel like the average IC is smarter than their leadership.
Your livelihood now depends on tokens remaining subsidized. How long do you think your engineers will continue to have the independent ability to maintain your codebase if the tokens got 20x more expensive?
Buy and sip that intelligence straight from the tap.
Accenture was.
No, it was a sinister way to manufacture your consent to cause cognitive atrophy in your employees so that you lose your ability to independently operate your business.
You'll come to realize this once they begin charging you more and more for tokens but you will probably not blame yourself for it.
The argument is tokenmaxxing was put in place by companies, with the goal of causing their employees to lose knowledge?
Have we? Is it generally the case that the more tokens you spend, you better results you get? This take is so weird I suspect author somehow financially benefits from tokenmaxxing.
They might own a chunk of NVDA.
Pet peeve of mine is nonsensical usage of the x is dead, long live x.
Not necessarily the desired result, but until it's 'done', where the LLM itself is the judge on if the is the case according to the given criteria (often just an updated todo-list). One of those extremely simple 'harnesses' (if you can even call it that) was even named the 'Ralph Wiggum Loop' [1] to allude to the braindead-but-persistent tokenmaxxing it results in.
[1] https://awesomeclaude.ai/ralph-wiggum
Otherwise they often do a first pass looks good enough but it doesn't actually work.
If you were tokenmaxxing you would understand.
I fear a world where critical software is stood up with increasingly non-human governed abstraction because it [seems like it] works.
Software engineers as the review terminal in a conveyor of business-led code mass production... coming to a company near you?
Really? ~4 years ago our CEO hired a consultant to fly out several times to do team building exercises. We can't afford to do our 3-year server refresh cycle, but the consultant was no problem to pay.
We just recently had branding consultants come in and also spent thousands of dollars (AWS charges) on rebranding all our photos. We operate in a captive market, if you want to operate in our market you are required to subscribe to our service, and if you aren't in our market you can't subscribe. Branding at the end of the day drives 0 sales.
Heck, reminds me of the time a company I was working with hired a new CTO and one of the first things he did was as "server renaming scheme" using obscure (to the US-centric staff) city names from around the world (database servers are Swiss city names, web servers are Denmark, storage is Finland). We went from cattle naming to pet naming, for a CTO that lasted ~6 months.
In my experience company leadership is not quite as thrifty as this article likes to think they are.
I really struggle to imagine how anyone in a corporate environment has managed to never run into obvious examples of waste like you describe (overpaid consultants and mandatory budgets are classic examples). Office Space came out 27 years ago and has a plotline making fun of overpaid "efficiency consultants" whose only job is to tell management to fire people.
The precondition for that is competition. If some company has idiot managers that waste resources on idiotic things, they're supposed to be wiped out by the companies that are actually smart.
Capitalism requires constant evolutionary pressure and a sort of government directed corporation level eugenics program to constantly apply that pressure in order to function properly. Without that, it's just distributed fascism.
consider me officially triggered
Or more accurately, "Because this is good for my career."
So after I got tired of choosing by hand, and therefore also a bit blindly, I created a small tool that runs locally and analyzes conversations to tell you which skills, MCPs, or other things are always unused.
347 items never used · ~19354 dead tokens/session · ~$25.49/month A lot of ECC that I never used but always loaded.
If anyone's interested, I've put it on GitHub, thousandflowers/skillreaper.
That comes out to spending $300,000 per user.
Citation needed
In my current company nobody forces you to use more tokens, but you're encouraged to write a 300 lines markdown skill.md which takes 8 minutes and costs 5 bucks to execute. That, instead of writing a 200 lines bash script doing all the same thing, but in a deterministic fashion, completing in under 5 seconds and costing 0 if you're not careful with rounding.
Anecdote, I thought so too until the company I work just instated this where you have spend from 35-60K within 6 months. Insanity
This is purely for coding and analogues.
Why do such fever dreams occur at all? Are they getting more prevalent? More damaging? Do they jepaordize the global economy? Should they be regulated in some fashion?
I can't prove my case, but I think it's a symptom of media manipulation/consolidation, the 'fiduciary duty' delusion, and that shareholders can hold the puppet strings tighter than they used to. More and more, they place their sillytown bets and expect the plebs to dance to them.
In the early days of LLMs, we saw the classic hype-driven bi-modality of opinions. Folks were in the "fake news, fad" camp, or they were in the "omg, take over the world" camp.
Those of us closer to the space, with the awareness to know that there was some truth (and a lot of misjudgment) to go around, were in the middle of nowhere. When I co-wrote some driver code with Chat GPT, other engineers (and even one of our directors) told me to keep it quiet. At the same time I had directors and VPs asking me how we could accelerate adoption. For a while, I had access to a cheat code just because I had the audacity to not ask for permission. Folks were sure I would get in trouble for spending thousands per month in LLM operation, but a handful came along for the ride, burning tokens like firewood and learning along the way.
Tokenmaxxing is probably coming from at least a few things:
1. A course-correction for the practiced frugality that kept folks from jumping in and just learning at the ragged edge.
2. A willful and deliberate recognition that the best innovations in the later phases of a disruptive introduction often come from sparks of ideation in concentrations of activity. In other words, we don't know where good is, and we need to find it. (Charitable interpretation from the article)
3. Recognition that, even if they don't know why, leaders and product owners will get punished for not jumping in and, because of bullets 1 and 2, won't get punished for trying and missing. Even if they have no idea what they're doing, they're going to fake it until they make it (or slide into another job).
This last set is where the pain lives. An organization with healthy and increasing AI tool usage will see elevated token counts, but so too will one using LLMs to rewrite wikipedia articles without the letter "m" to keep token counts high. These are pathological behaviors brought on by conflated metrics.
We had discussions about this in the early LLM days, where my old team was looking to ship new capabilities for older products. There was a lengthy VP-level discussion about getting to "80% usage" of the new system vs the old. Because the new system was a superset of the old, I eventually said "we can do that immediately, but it's a cost goal, where we're just aiming to make our business more expensive to operate, rather than a value goal for our users". We didn't adopt the target, but folks were understandably frustrated that they didn't have a straightforward way to measure and report progress.
Tokenmaxxing is, inevitably, a conflated goal, but it's what we have right now. Take advantage of the moment, learn, build, and keep an eye on levers for efficiency.
The idea of tokenmaxxing reaches different companies in different waves, so it will be discovered in waves and outgrown in waves in companies and industries in their own cycle.
In the long run, tokenmaxxing is like drunken sailor spending. Scaling is almost always about a large component of efficiency, and lighting money on fire in the street can only last so long.
I predict startups will continue to tokenmaxx while 40,000+ person companies will become a little more conservative.