Tokenmaxxing makes no sense, it is akin to write extremely inefficient SQL / Spark Jobs, full of cartesian joins, ultra skewed datasets, etc, just for the sake of using as much compute / memory / IO as possible.

This always happens when the metric becomes the goal, companies should nurture and foster an environment where AI is used in the most efficient way possible, first asking "do we really need an agent for this" and if so, what kind of agent is needed, what model, reasoning level, etc.

They should also promote projects that aim at saving tokens, increasing cache hits, codifying the information in ways such they use as less context as possible (graphs of knowledge are pretty good for this!)

▲

InsideOutSanta 2 hours ago | parent | next [-]

It's toddler-level logic. "You can achieve positive outcomes by using X. Therefore, we need to use as much X as possible to maximize positive outcomes."

It's like trying to win a race by setting a gas station on fire.

▲

HDThoreaun 2 hours ago | parent | prev | next [-]

Tokenmaxxing exists because executives think employees are resistant to change. Thats it, a way to incentivize/force every employee to experiment with a new technology. Obviously once they think everyone is utilizing AI the tokkenmaxxing stuff will end.

	▲	loeg 2 hours ago \| parent [-]
		Yes. Executives think, correctly, that employees are resistant to change.

▲

SpicyLemonZest 2 hours ago | parent | prev [-]

The argument in favor of "tokenmaxxing" has always been that it's creating space for employees to freely explore the broad and novel space of AI-enabled workflows. I've seen a number of use cases where I'm skeptical any value is being produced, but a number of others where some team or another has finally solved a long-standing problem of theirs with an agentic workflow that would have been hard to justify to a cost review committee.

> They should also promote projects that aim at saving tokens, increasing cache hits, codifying the information in ways such they use as less context as possible (graphs of knowledge are pretty good for this!)

My understanding is that most big "tokenmaxxing" companies do have teams who are working on this in the background.

	▲	onesociety2022 an hour ago \| parent [-]
		+1 I find the general disdain for C-suite or senior engineering leadership on HN so silly. These people didn't get promoted or hired because of nepotism. A lot of them moved up the engineering ladder and are familiar with how software engineering works and the incentives involved. Yes, some of them are sheep and will blindly copy what is fashionable but so do a large swath of ICs. If you want incredibly fast adoption of AI within a company, the best thing you can do is to signal from the top that tokenmaxxing will be rewarded (or at least not be punished for it). 1. It forces everyone including the lazy ones who normally wouldn't invest their time in learning anything new to actually install codex/claude and learn to use them. 2. It prevents any middle manager from putting up blockers for adoption/experimentation ("this is new, I don't trust this, let's do it the old familiar way", "this might be expensive, we care about efficiency here", etc). Once the C-suite dictates tokenmaxxing is allowed, every middle manager will fall in line instantly. 3. Tokenmaxxing is not choice you have to live with the rest of your life. A year or two from now, once C-suite is satisfied with the rate of AI adoption within their org/company, they can just as easily switch the focus to efficiency. Teams will be asked to justify their token spend and start to optimize.