Quentin Anthony Profile picture
I make models more efficient. Google Scholar: https://t.co/kzVsAKPLgX
Jul 12 8 tweets 5 min read
I was one of the 16 devs in this study. I wanted to speak on my opinions about the causes and mitigation strategies for dev slowdown.

I'll say as a "why listen to you?" hook that I experienced a -38% AI-speedup on my assigned issues. I think transparency helps the community. Image Firstly, I think AI speedup is very weakly correlated to anyone's ability as a dev. All the devs in this study are very good. I think it has more to do with falling into failure modes, both in the LLM's ability and the human's workflow. I work with a ton of amazing pretraining devs, and I think people face many of the same problems.

We like to say that LLMs are tools, but treat them more like a magic bullet.

Literally any dev can attest to the satisfaction from finally debugging a thorny issue. LLMs are a big dopamine shortcut button that may one-shot your problem. Do you keep pressing the button that has a 1% chance of fixing everything? It's a lot more enjoyable than the grueling alternative, at least to me.