This is my understanding too. The underlying assumption is that action leads to information, iterations lead to enlightenment. So from an org's point of view, tokenmaxxing means encouraging everyone to explore as much as they can. Of course, token volume should not be the only metric - tokenmaxxing is just a catchy phrase.
So doing something (action) creates something new (more information), and iterating on that new information leads to the realization there is nothing new left to be learned with that information (enlightenment). Is how I'm interpreting that.
The unusual thing is perhaps how global and cross industry it seems.
Genuinely asking: for which fads was it actually beneficial to jump in during the hype phase? Was there ever anything so critical that there was some huge disadvantage if you didn't adopt it right away?
ETA: I suppose the complicating factor, at least for B2B, is "customers demanding $fad", particularly when the purchasing decision makers don't actually understand what $fad is (e.g., "cloud", "blockchain", "ai", ...). If you don't become "$fad native" right away, you lose the Dunning-Kruger segment of the market.
Even "cloud" which did stick around and actually did pan out, didn't see such immediate adoption during the hype. There were a lot of companies that stayed on-prem for a long time, many which still are, and none of them imploded for not jumping on the hype.
Why is the FOMO so strong with AI this time around? I don't ever recall being told "spend as much money on AWS as you possibly can!" during the cloud hype...
The AI equivalent of the PC revolution isn’t quite here yet, but it’s the only way forward.
In many cases it really didn’t/doesn’t matter if the AI automation actually works, just that people think it could - and hence leave money on the table.
Not sure if you mean this in a good or bad way.