[la_fayette]

When you argued that it saved you time by a factor of 10, have you even measured that properly? I initially also had the feeling that LLMs save me time, but in the end it didn't. I roughly compared my performance to past performance by the amount of stories done and LLMs made me slower even if I thought I am saving time...

From several month of deep work with LLMs I think they are amazing pattern matchers, but not problem solvers. They suggest a solution pattern based on their trained weights. This even could result in real solutions, e.g., when programming Tetris or so, but not when working on somewhat unique problems...

[mlyle]

I am pretty confident. Last similar LVGL thing I did took me 10-12 hours, and I had a quicker iteration time (running locally instead of the test hardware). Here I spent a little more than an hour, testing on real hardware, and the last 20 minutes was nitpicking.

Writing front-end display code and instantiating components to look right is very much playing to the model’s strength, though. A carefully written sentence plus context would become 40 lines of detail-dense but formulaic code.

(I have also had a lot of luck asking it to make a first pass at typesetting things in Tex, too, for similar reasons)

[delusional]

There was a recent study that found that LLM users in general tend to feel like they were more productive with AI while actually being less productive.

[asadotzler]

presumably the study this very HN discussion responds to.

[delusional]

Heh, yep. Guess I sometimes forget to read the content before commenting too.