Programming is one of those skills and industries that is accessible enough that basically anyone can do it, but you will run into trouble later if you're doing anything serious without learning how to do it well. There are hundreds or thousands of ways to make something work, but if it's an unmaintainable mess or you don't even understand how it works, then we end up with our financial institutions running COBOL in 2025. Good luck when regulations change. Have fun when your operating system becomes unsupported and you have to replace the underlying dependencies. Hope your boss doesn't sue when they have to hire people to rewrite your hackjob.

And these were all already problems before AI code came onto the scene. We had the programming equivalent of script kiddies, people who would blindly copy and paste code from web searches without even reading the date or the comments saying "this is bad and this is why". But this probably makes it even easier to do, and possibly harder to spot. Combine this with how many universities don't even focus on lower-level languages so you get plenty of people who can't understand how to fix any of the trickier errors in their code. And that's not to say everyone has to be able to, but it's a problem when so few are able to. So these programmers are unlikely to know if the code has problems so long as it passes their tests, and unlikely to know how to fix those problems when they become clear.

Automation tools are good ideas for assisting and detecting possible mistakes. They're not good at generating that much code. In fact, that amount of code in that amount of time is suspicious, hinting that it's unlikely to be well-designed, maintainable or efficient.