I've seen two camps of people within the same company I work at. Some think AI is generating acceptable code. Others think it's generating slop.

I sit in the middle a lot of the time as my opinion on code quality vary depending on how important the code actually is.

I will say one thing, the people who I generally deemed as worse developers prior to the wide AI roll out are the ones that are more accepting of AI code. And consequently, they're the ones spending a magnitude more money each day. The people who were writing better code and, in my opinion, were stronger developers, are spending less on AI and are generating more acceptable code when they use it. And they can spot issues from a mile away, because they actually understand the code being generated. They're not just committing lots of redundant code.

We had an AI outage for a day or two a few weeks back. The reaction from some people was like it was the end of the world and they couldn't do any work. Some projects got put on hold because no one actually knew how to work on the code base without AI. Other, better in my opinion, developers just went shrugged it off and got on with their job.

AI over-dependence is a big issue that people will face more and more. Weaker juniors used to just be a bit slower and stagnate a bit, but they could still kinda work independently and understand what they were doing. Now they are almost entirely prompt monkeys, take away their Claude Code terminal and they are completely stumped.

> I sit in the middle a lot of the time as my opinion on code quality vary depending on how important the code actually is.

This is really the key insight that most people on the extreme ends of the discussion don't seem to grasp and then talk in absolutisms because they think that their tiny village is the whole world.

It's the same kind of 'extremism' that dominates most discussions about memory safety btw.

For some types of programs, code quality simply doesn't matter as long the program does its job, and generating those programs even with the most sloppiest vibecoding approaches is totally fine.

And in some areas of the industry (like web development) these types of programs are basically the norm - but this sort of code was already mostly hastily cobbled together slop even before AI.

I also see extreme differences in usefulness of LLM code generation. For anything JS or TS it works great because there's a giant corpus. For C code (or even more obscure languages) especially when using libraries which change all the time my experience is totally different (at least for code generation, bug scanning works quite well).

That's my experience so far anyway, literally "hit and miss" with some areas where there are more hits than misses, and other areas where it's the other way around.