> METR

Yes I’ve seen it. It was certainly interesting at the time. If you refresh yourself on the study, it admits to reflecting a narrow point in time on a narrow task type and toolset.

Last July most people I know weren’t automating Jira tickets, pull requests, comment addressing, design docs, multi repo research, and customizing rule sets. Now everyone I know does, each of these incrementally speed up productivity.

> Not to mention the absolute lack of well known AI-produced products that we know of.

This is a strange comment. We have a well known example in openclaw, which is notoriously vibe coded, which again if you follow the thread, I’m not defending. whereas I know senior and staff engineers at most FAANG companies and every single one uses AI to code, so many many products you know are being written with AI.

I don’t wanna dox myself but last year my company developed a greenfield product with a pretty large headcount of eng (multiple teams)that was built with an AI first development workflow, now that doesn’t mean the 20 engineers just stood around and twiddling their thumbs. They were doing real engineering and software development work with heavy agentic AI use. They shipped it in six months and it’s been in prod for months. If you can’t see how AI is being used I don’t know what to tell you.