That's being bad at programming in my opinion. You can mitigate it a lot with how you config you agents. Mine loads our tech stack. The best practices we've decided to use. The fact that I value safety first but am otherwise a fan of the YAGNI philosophy and so on. I spent a little time and build these things into my personal agent on our enterprise AI plan, and I use it a lot. I still have to watch it like a hawk, but I do think it's a great tool.
I guess you could say that your standard LLM will write better Python than I did 10 years ago, but that's not really good enough when you work on systems which can't fail. It's fine on 90% (I made this number up) of software though.
I did find (weirdly) that it improved when running on WSL rather than windows.
However I did get it to code a script for downloading SharePoint files and even got it to reduce the dependencies down to built-ins which was a massive time saver
The thing I should have made clearer is probably that I think the horrible code is great. Yes it's bad, but it's also a ton of services and automation which would not have been made before LLM's, because there wouldn't have been enough developer time for it. Now it being terrible code doesn't mean the sollution itself is terrible for the business. You don't need software engineering until you do, and compute is really cheap on this scale. What do we care their code runs up €5 a year if it adds thousands of euros worth of value?
It's only when something stops working. Usually because what started out as a small thing grows into something where it can't scale that we take over.
