[jayd16]

Well hold on. "They" also thought tokenmaxxing was a good idea, until they didn't.

Whether companies pay will come down to the bottom line once the hype around the country club dies down a bit and for that it's still TBD on the actual product cost impact.

[simonw]

Yeah, tokenmaxxing was obviously stupid. Setting a limit is what happens when the adults in the room stop being stupid.

[satvikpendem]

Not sure about that. As I replied elsewhere, it's a forcing function:

> People misunderstand the point of the tokenmaxxing time period, it was to force people to use AI so as to not have them stuck in their way, as some people are, and then to evaluate how it can help the company.

https://news.ycombinator.com/item?id=49047448#49047826

[simonw]

I expect everyone understood that.

The obvious second effect is that if you have a leaderboard people will compete to top it, by running dumb loops or whatever.

That impacts how much you can learn, and costs you more money than you wanted to spend.

[mholm]

The excessive spending was part of the point. The market is watching AI spend very closely. AI spend is a proxy for AI absorption. Expanding your MS contract to include Copilot for your rank and file doesn't move the meter much. Letting your engineers run up 100k/month shows extreme absorption. The share price increase potentially pays for the entire token bill once Wall Street goes through your earnings.

[satvikpendem]

Not everyone did understand that, you'll see some comments expressing that they've never heard that perspective before, interestingly enough. But yes Goodhart's Law applies.

[bigstrat2003]

That is a truly commendable steelman. But let's be honest, there's basically no chance that was true. Management is frequently stupid enough to not think through the second order effects of their policies, and that is likely what happened this time as well.

[satvikpendem]

At least at my workplace this was exactly what we were told, that it's a short term methodology to get people acclimated to thinking about what in their work could be automated, as honestly most do not think that way, they're not like engineers.

[duhhhhh1212]

It's hard to read this take seriously, when you promoted a company spending $1k per engineer per day on LLM usage.

[simonw]

You mean Strong DM? I stand by what I said about them at the time: they're an interesting case-study in extreme AI-assisted software development, and they have a bunch of ideas that are worth learning from even if you're not going to spend that (absurd) kind of money.

One of the hot topics since then has been how to validate software without reviewing every line of code by hand, which is exactly the kind of thing they were exploring before anyone else.

[duhhhhh1212]

Yes, Strong DM. How is that different from tokenmaxxing? Because of the article you wrote, a few companies went to them and starting adopting their methods and guess what happened in a few weeks into that process? Upper management started tracking engineers who weren't using AI enough (~1k a day). A few engineers got fired because they were slow to adopt StrongDM's process.

[simonw]

Have you really seen engineers fired for failing to spend $1,000 on tokens a day because their bosses read my piece about Strong DM? https://simonwillison.net/2026/Feb/7/software-factory/

I would hope that my commentary on those patterns would be less likely to lead to bad decisions than if people just read Strong DM's own description of their software factory approach: https://factory.strongdm.ai/

[duhhhhh1212]

> Have you really seen engineers fired for failing to spend $1,000 on tokens a day because their bosses read my piece about Strong DM?

Bruh, come on. Not directly is the best answer I have for that. Unfortunately, they didn't read your article carefully, because the idea of productivity gains was all the candy they needed to jump in the van.

[twister2920]

"the last decision these people made was obviously stupid, but trust me bro that this one is smart"