I wonder if the codebase will be understandable at all.
You can most often “get used” to a codebase because they authors tend to stick to the same patterns in many ways, and they are somewhat coherent across time. After a bit you can kinda guess in what file is a feature implemented etc etc.
Will this still be true with ai doing most of the work?
Claude is really good about documenting what it has done. I’ve also had some good luck with “I’m interested in this part of the codebase please explain it to me”
And “this part is not working let’s diagnose”
I’ve been doing a lot of productionization of nontechnical vibecoding. And I provide a lot of feedback on best practices (one of which is to ask “is this best practices for security and data protection?”)
That being said there’s no replacement for a real knowledgeable human software engineer.
I would say that the current capabilities of genAI is like a junior dev, sometimes even a mid-level. But one main difference is that a dev is slowly learning and improving and at some point will become a senior dev and also domain specialist.
If there is a codebase created by genAI, then it’s equivalent as if all devs left the company, so no one knows why some piece of code was created in a certain way, if it was part of the business logic or some implementation detail