This is completely orthogonal to the inference and training stack that the parent comment mentions

If it’s written by AI it’s gonna be the same overcomplicated overfit slop in one way or another. Performance pressure doesn’t fix that.

	▲	aurareturn 2 hours ago \| parent \| next [-]
		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.
	▲	stingraycharles 2 hours ago \| parent \| prev [-]
		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.