Curious that he references a METR study from July 2025, before the leap in model and harness performance towards the end of 2025/early 2026.
> 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.
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.
yes, because in order to take a short position you have to predict exactly when the bubble is going to pop, which is different from predicting that at some point it will
What leveraged? yeahnah thats not going to be profitable.
Not true.
Edit: to be clear, I am talking about Ed’s contention that AI coding isn’t net productive.