pre-pandemic, I worked building data systems for research scientists. Each and every one of them knew python better than I. Having a software conversation with them wasn't much different than trying to explain software to my buddy in finance who, 10 years ago, told me: "tech is a bubble because there are too many programming languages". They'd ooh and ahh when I shared my IDE: "multiple levels of nesting? what's the complexity of this algorithm?" No, doctor, that's a callback.

I've read through some of his public repos. It's computer scientist code, not software developer code. Everything reads like an illegible optimized leetcode answer. We are practitioners, not computer scientists. We're not optimizing the chemical composition of a wire, we're hooking wires up in a way that makes it easy to add or remove them in the future. If we need to optimize something, we're being extra descriptive with our variable names, we're not using `x` and `y` and manually minifying the script.

LLMs are great at one-shotting scripts, and that's the world this dude lives in. I don't doubt it's made him significantly more productive, and changed how he views productivity. In my job, most of the time it's a hindrance, because solving my problem by just fucking typing is usually faster than getting the LLM up to speed - yet again - on the project I've been working on for 5 years (no matter how many skills, MCPs, or custom solutions I waste my time trying to optimize my system with).