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I never took tokenmaxxing to be about improving productivity directly; mundane feature work that comes out of it is just a side effect. I always saw it as a rac

I never took tokenmaxxing to be about improving productivity directly; mundane feature work that comes out of it is just a side effect. I always saw it as a race between these big tech companies to get a generational advantage by being the one to discover the way of the future, with respect to harnessing AI to actually and truly automate software development. EDIT: whoa, I used "way of the future" as a reference to Howard Hughes in "The Aviator", not this Way of the Future religious organization thing I just stumbled on; no intended reference there.

layer8 5mo ago
To the extent that figuring out the true automation will lead to layoffs, that knowledge will quickly spread as the laid-off knowledge workers are available for hiring.
infecto 5mo ago
Agree and I have wondered behind close doors if this is not the mental model. You need to spend money to see what is working this was simply a way to see that.
lazide 5mo ago
Eh, I also saw it as a rather blatant attempt to undermine the bargaining power of the Software Engineer (which had grown to insane proportions over the years) - both in working conditions and raw cash money. 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.
- lenerdenator 5mo ago
  > insane Not sure if you mean this in a good or bad way.
  - lazide 5mo ago
    Good/bad entirely depends on if you are management/shareholders, or the engineer in question. It was pretty nuts either way though eh? End of an era
izzydata 5mo ago
My impression of companies pushing AI so heavily is that they are basically being forced to do it by it merely existing. Imagine if AI really is as powerful as it is suggested to be and you didn't jump on the bandwagon. Then you would be behind. So by it existing and other companies using it, you have to as well because even if it turns out to be a failure at least everyone else will have failed too and you are on an even playing field.
- jrmg 5mo ago
  You could kind of use that line of thinking to justify spending on anything.
  - bluGill 5mo ago
    There is a fad every few years that uses similar thinking to justify spending. Sometimes they work out sometimes they don't. But they never work out as good as the most optimistic predictions.
    - LogicFailsMe 5mo ago
      Usually, someone extracts genuine value at the expense of everything else IMO. And the enshittification continues apace.
    - nitwit005 5mo ago
      I commented on wasteful AI spending, and my father immediately started talking about how he "went through that a couple of times" as a manager at an oil company. The unusual thing is perhaps how global and cross industry it seems.
    - 12_throw_away 5mo ago
      > Sometimes they work out sometimes they don't 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.
jaredklewis 5mo ago
This is insightful. It does sort of feel like the search for the Northwest passage.
tracerbulletx 5mo ago
Yeah this is right. Its about taking the throttle off of experimentation hoping some team suddenly starts shipping a years worth of features in a week and responding to strategic customer demands in near real time. Then copying what works out across the org. (and probably downsizing)
- groby_b 5mo ago
  What those organizations miss is that they drown their teams in organizational red tape. The way to the future isn't tokenmaxxing - it's cutting back on process noise.
  - basch 5mo ago
    It was very easy to see before this started that the models were just repetitive inflators. It’s not that they should “scale back” their use as much as the metric should be improvement/tokens. Tokens used is a denominator in any worth calculation.
nobodyandproud 5mo ago
My hot take: The way of the future is local LLMs. The AI equivalent of the PC revolution isn’t quite here yet, but it’s the only way forward.
- charcircuit 5mo ago
  It will always be worse compared to a centralized approach where hardware utilization can remain high. Except in case which demand low latency which most development things do not need. It's okay if it takes an extra 100ms for a code review to take place.
  - nobodyandproud 5mo ago
    It's little different from the mainframe/mini computer to the PC: Huge servers and resources will be better--no dispute there--but good-enough will be achieved using local resources. There are privacy and general de-centralization reasons to prefer this outcome, even though most AI and cloud-first tech companies don't want this. How long it will take us to get this point is a different matter.
  - jurgenburgen 5mo ago
    By that logic shouldn’t streaming video games also be centralized? Yet startups keep trying it and failing. Turns out users actually want exclusive access to that hardware to have a smooth experience. The tradeoff has always been between faster exclusive hardware or slower but cheaper shared hardware. If local hardware can’t beat shared hardware on performance then something’s wrong? Either it’s because the providers are charging wildly below cost or because local hardware just hasn’t needed to catch up. Maybe it’s both.
    - alfiedotwtf 5mo ago
      RAMageddon has caused local models to lag far behind hardware for a long while now.
- garrickvanburen 5mo ago
hintymad 5mo ago
> by being the one to discover the way of the future 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.
- butlike 5mo ago
  > action leads to information, iterations lead to enlightenment 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.
waqarjaved 5mo ago
[flagged]
rixed 5mo ago
Like many corporate behaviors I believe we tend to rationalize them too much. Most job posts for management ask for previous experience with "implementing AI". Managers don't want to be left out any more than devs. Devs rewrite everything in the language-du-jour, managers max out tokens.

layer8 5mo ago

To the extent that figuring out the true automation will lead to layoffs, that knowledge will quickly spread as the laid-off knowledge workers are available for hiring.

infecto 5mo ago

Agree and I have wondered behind close doors if this is not the mental model. You need to spend money to see what is working this was simply a way to see that.

lazide 5mo ago

Eh, I also saw it as a rather blatant attempt to undermine the bargaining power of the Software Engineer (which had grown to insane proportions over the years) - both in working conditions and raw cash money. 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.

lenerdenator 5mo ago
> insane Not sure if you mean this in a good or bad way.
- lazide 5mo ago
  Good/bad entirely depends on if you are management/shareholders, or the engineer in question. It was pretty nuts either way though eh? End of an era

izzydata 5mo ago

My impression of companies pushing AI so heavily is that they are basically being forced to do it by it merely existing. Imagine if AI really is as powerful as it is suggested to be and you didn't jump on the bandwagon. Then you would be behind. So by it existing and other companies using it, you have to as well because even if it turns out to be a failure at least everyone else will have failed too and you are on an even playing field.

jrmg 5mo ago
You could kind of use that line of thinking to justify spending on anything.
- bluGill 5mo ago
  There is a fad every few years that uses similar thinking to justify spending. Sometimes they work out sometimes they don't. But they never work out as good as the most optimistic predictions.
  - LogicFailsMe 5mo ago
    Usually, someone extracts genuine value at the expense of everything else IMO. And the enshittification continues apace.
  - nitwit005 5mo ago
    I commented on wasteful AI spending, and my father immediately started talking about how he "went through that a couple of times" as a manager at an oil company. The unusual thing is perhaps how global and cross industry it seems.
  - 12_throw_away 5mo ago
    > Sometimes they work out sometimes they don't 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.

jaredklewis 5mo ago

This is insightful. It does sort of feel like the search for the Northwest passage.

tracerbulletx 5mo ago

Yeah this is right. Its about taking the throttle off of experimentation hoping some team suddenly starts shipping a years worth of features in a week and responding to strategic customer demands in near real time. Then copying what works out across the org. (and probably downsizing)

groby_b 5mo ago
What those organizations miss is that they drown their teams in organizational red tape. The way to the future isn't tokenmaxxing - it's cutting back on process noise.
- basch 5mo ago
  It was very easy to see before this started that the models were just repetitive inflators. It’s not that they should “scale back” their use as much as the metric should be improvement/tokens. Tokens used is a denominator in any worth calculation.

nobodyandproud 5mo ago

My hot take: The way of the future is local LLMs. The AI equivalent of the PC revolution isn’t quite here yet, but it’s the only way forward.

charcircuit 5mo ago
It will always be worse compared to a centralized approach where hardware utilization can remain high. Except in case which demand low latency which most development things do not need. It's okay if it takes an extra 100ms for a code review to take place.
- nobodyandproud 5mo ago
  It's little different from the mainframe/mini computer to the PC: Huge servers and resources will be better--no dispute there--but good-enough will be achieved using local resources. There are privacy and general de-centralization reasons to prefer this outcome, even though most AI and cloud-first tech companies don't want this. How long it will take us to get this point is a different matter.
- jurgenburgen 5mo ago
  By that logic shouldn’t streaming video games also be centralized? Yet startups keep trying it and failing. Turns out users actually want exclusive access to that hardware to have a smooth experience. The tradeoff has always been between faster exclusive hardware or slower but cheaper shared hardware. If local hardware can’t beat shared hardware on performance then something’s wrong? Either it’s because the providers are charging wildly below cost or because local hardware just hasn’t needed to catch up. Maybe it’s both.
  - alfiedotwtf 5mo ago
    RAMageddon has caused local models to lag far behind hardware for a long while now.
garrickvanburen 5mo ago

hintymad 5mo ago

> by being the one to discover the way of the future 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.

butlike 5mo ago
> action leads to information, iterations lead to enlightenment 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.

waqarjaved 5mo ago

[flagged]

rixed 5mo ago

Like many corporate behaviors I believe we tend to rationalize them too much. Most job posts for management ask for previous experience with "implementing AI". Managers don't want to be left out any more than devs. Devs rewrite everything in the language-du-jour, managers max out tokens.