[nlawalker]

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.

[izzydata]

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.

[stephen_cagle]

I feel like this is kind of like the gambler's risk of "going bust" but applied backwards?

Feels like it would be better to spend just enough so that you have the capacity to scale up IFF LLM's end up being a big deal. You spent less than your rivals (who were competing for a supremacy that never came), but you have saved more "dry powder" to compete against them for the more likely future. The only future you exclude with this strategy is the "LLM Supremacy" future, which you only had a 1/(number_of_players) chance of winning anyway. :]

I think the real reason for the spending is that the scent of LLMs in the air causes stock values to go up. And even if everyone knows it does not make sense, they still want "NUMBER GO UP", and so they will spend more money to excite the amateur and professional investor class.

[jrmg]

You could kind of use that line of thinking to justify spending on anything.

[bluGill]

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.

[nitwit005]

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]

> 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.

[thewebguyd]

That's what throws me off about the AI hype. I've lived through plenty of other hype cycles, but none had such rapid adoption as this during the hype phase. Usually its a bunch of early adopters and a few doomed startups, with the big established (non tech) companies never fully jumping in, and then by the time they might have considered it, the fad died.

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...

[y0eswddl]

because the tech industry is at a hole is out of creative ideas. That why ever seen so many hype cycles since the end of zirp - and why the only innovation we're seeing is on ways to squeeze more money out of people. and AI was sold as a salary cutting magical money machine... AKA one more hype to jump on.

except this one a isn't making anyone rich besides Nvidia

[jrmg]

Sears, the obvious choice, could have been Amazon. There are plenty of other less extreme examples of defunct brick-and-mortar stores who were killed by internet competitors (often, Amazon).

[LogicFailsMe]

Usually, someone extracts genuine value at the expense of everything else IMO. And the enshittification continues apace.

[pfannkuchen]

Only lemming spending. Where the first few lemmings have to justify it some other way.

[cdud3]

Not on anything but on some things like “Nobody Ever Got Fired for Buying IBM”

[tracerbulletx]

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]

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]

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.

[hintymad]

> 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]

> 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.

[layer8]

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.

[rixed]

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.

[nobodyandproud]

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.

[garrickvanburen]

I agree. We don't need a nondeterministic 10quadrillion vector model. We need an deterministic expert on our narrow business. Something small, that can be run on the 2026 version of the spare PC under the CTOs desk.

[charcircuit]

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]

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]

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]

RAMageddon has caused local models to lag far behind hardware for a long while now.

[infecto]

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.

[jaredklewis]

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

[lazide]

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]

> insane

Not sure if you mean this in a good or bad way.

[lazide]

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