Assuming it’s entirely unsupervised, yes, which I can only assume to be the case at these volumes (hence the dogfooding).

I do believe this will force the AI labs to eventually solve the bloat problem with AI, but we’re definitely not there yet.

Depends on what the goal is and the skill of the engineer right?

Give a verifiable benchmark for the AI agent to hit such as reduce token processing time by 5% without affecting output.

Different metrics. You measure how many users you have, whether they’re closing the app and etc. when it comes to consumer level apps. ChatGPT/Claude is heavily used, not a problem for an average user, so no need to improve that.

Kernels, performance-required stacks etc. is different, so you optimise them for that.