My experience shows that AI can program like the best programmers; its code is very good when given precise instructions, just like a human. I've encountered problems elsewhere, such as anti-patterns in unwired modules, which are "large-scale" implementation errors. I'm resolving these thanks to an open source tool I'm building for AI cognitive governance, and it's yielded excellent results for me. The code produced at both small and large scales is high quality.
In my experience, people experiencing gross AI errors are doing so because they aren't giving it precise instructions. And by precise instructions, I don't mean a highly refined prompt or "vibe-coding"; I'm talking about instructions thousands of lines long, just like the ones we create when developing with human teams.
If two people are using the same model, and one reports that the AI "neglected to handle a case where a database could have multiple rows with the same ID", while the other says they can develop a huge microservices system with multiple databases without any major issues, perhaps one of them isn't using the tool optimally, based on my experience.