This is par for the course with this AI slop. Most of the big claims about LLM productivity have completely lacked any backing evidence. Big claims require big evidence, but all I've seen so far is loud assertions and pathetic results.

I’m happy that this shows that hard work, understanding your codebase, having performant software, having actually working software, rigorously measuring and proving proof of results still matters.

There’s a huge difference between using LLMs to offload any hard work and for LLMs to be of some assistance while you are in control and take ownership of the output.

Unfortunately, the general public probably didn’t try a git clone and cargo build, and took the article at face value.