Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.<p>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.<p>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.
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.
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".<p>Definitely not some measured, long term, rational out of the gate.
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).<p>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."<p>There's a case for the cost-maxing has hurt our company.
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 being 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".
People in small teams with managers promoted from within could probably have had this in mind.<p>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.
Do you have a source for this?<p>> Tokenmaxxing was just a way to force employees to start leveraging AI in a meaningful way.<p>> It was always a temporary thing to transition the employees to a new world.<p>Trying to understand your justification for rejecting Hanlon’s razor.
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.<p>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.<p>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.<p>Anyway, just needed to get that off my chest.
The problem is that managers have no idea how this is supposed to help either, and just get told from above to use AI.
You're naive, uninformed or turfing if you think companies are still not tokenmaxxing.<p>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