> I tend not to actually read most LLM output anymore; I skim it, to check if I vibe with it. But a problem statement of three sentences, that I will fact-check really hard. It is like code review: a review with 1,000 lines of code gets an “LGTM”. A review with 100 lines gets 15 comments.

This is where I take issue. I'm in a similar boat to the author. In the last couple of months, I've been experimenting with increasing the use of local and cloud LLMs for my research code. I'll create a prototype, maybe port it to a language I don't use very much like Rust, run some tests... but at the very end when I'm very happy with it, I _need_ to go line by line and understand _everything_ that is happening. Sometimes that means using an LLM to understand it, but even when I do and there is a concept I don't get, I try to read primary resources written by experts.

The least bad thing I've found LLMs good for is ideation because it's super easy to take the good nuggets and leave the bad, but even that carries risks of shaping thought and making everyone reach for and ignore the same ideas in the way the Spotify radio or YouTube autoplay has been shaping/flattening tastes for the worse.

I'm not sure what I'll rule at the end of my experiments with LLMs, but right now I'm enjoying the rush of having prototypes that run quickly. I've always been a top-down learner, being motivated by hacking a cool demo I half understand and progressively tearing it apart.