> A general pattern for LLMs is that they look really good at things you are bad at.

This is true for coding, too, which I think, to a large degree, might explain the polarized differences in opinions on HN about the quality of LLM-produced code. You have the 1. "AI produces code better than I could possibly write, one shots things it would take me days to do, and has made me 10X more productive!" camp, and you have the 2. "AI constantly hallucinates, makes mistakes, has to be babysat, and ultimately costs me time!" camp, with a spectrum in between those. How could the output of the same product be seen so differently? Well, I have bad news for camp 1...

I think there are some factors beyond just skill too - the kinds of tasks you're giving the AI, and how involved you are in ensuring the output is good (via either extensive planning guidance, extensive review/testing, or a combination).