Interestingly, that METR study has updated data for 2026 that shows a speed up, although they admit that the data may not be reliable because of changed pay rate for participation, but this quote is telling:

> The primary reason is that we have observed a significant increase in developers choosing not to participate in the study because they do not wish to work without AI, which likely biases downwards our estimate of AI-assisted speedup.

So compared to just last year, they had a hard time finding participants because too many didn't want to work without AI.

I stopped reading at maybe 25% into the article. It's obvious garbage.

He selectively quotes the max theoretical enterprise pricing equivalent of fully using the private subscription. Did SemiAnalysis not also claim a very high margin?

He throws in doubt about the providers having decent margins, which he claims is made up by "AI boosters" rather than leaked financials and open-weight pricing.

Then next he talks about "the real cost" of inference as if it was in any way realistic that labs price the enterprise plans near cost, like he seems to imply.

Then next he claims AI is actually slowing developers down and there isn't much difference between the models.

It just seems delusional.

Welcome to Ed Zitron. There is a reason this man doesn't heavily short the same companies he criticizes. Be wary of anyone that won't put their money where their mouth is.

I don't know if his final analysis is right or wrong, but if he believes this, he's completely clueless (about this aspect at least).

Edit: to be clear, I am talking about Ed’s contention that AI coding isn’t net productive.