How are you going to maintain all that when you find bugs if it generates a ton of code you did not get through to understand it?
Same as any other software team? You keep an eye on all PRs, dive deep on areas you know to be sensitive, and in general mostly trust till there's a bug or it's proven itself to need more thorough review.
I've only ever joined teams with large, old codebases where most of the code was written by people who haven't been at the company in years, and my coworkers commit giant changes that would take me awhile to understand so genAI feels pretty standard to me.
You ask it to fix it.
I've tried fixing some code manually and then reused an agent but it removed my fix.
Once you vibe code, you don't look at the code.
I love using AI and find it greatly increases my productivity, but the dirty little secret is that you have to actually read what it writes. Both because it often makes mistakes both large and small that need to be corrected (or things that even if not outright wrong, do not match the style/architecture of the project), and because you have to be able to understand it for future maintenance. One other thing I've noticed through the years is that a surprising number of developers are "write only". Reading someone else's code and working out what it's doing and why is its own skillset. I am definitely concerned that the conflux of these two things is going to create a junk code mountain in the very near future. Humans willing to untangle it might find themselves in high demand.
The trick is to separate your codebase into "code I care about that I give the AI a fixed API and rarely let the AI touch" and "throwaway code I don't give one iota of damn about and I let the AI regenerate--sometimes completely from scratch".
For me, GUI and Web code falls into "throwaway". I'm trying to do something else and the GUI code development is mostly in my way. GUI (especially phone) and Web programming knowledge has a half-life measured in months and, since I don't track them, my knowledge is always out-of-date. Any GUI framework is likely to have a paroxysm and completely rewrite itself in between points when I look at it, and an LLM will almost always beat me at that conversion. Generating my GUI by creating an English description and letting an AI convert that to "GUI Flavour of the Day(tm)" is my least friction path.
This should be completely unsurprising to everybody. GUI programming is such a pain in the ass that we have collectively adopted things like Electron and TUIs. The fact that most programmers hate GUI programming and will embrace anything to avoid that unwelcome task is pretty obvious application of AI.
You don't, and as long as you're comfortable with that you keep prompting to dig yourself out of holes.
The problem is unless your ready to waste hours prompting to get something exactly how you want it, instead of spending those few minutes doing it yourself, you start to get complacent for whatever the LLM generated for you.
IMO it feels like being a geriatric handicap, there's literally nothing you can do because of the hundreds or thousands of lines of code that's been generated already, you run into the sunk cost fallacy really fast. No matter what people say about building "hundreds of versions" you're spending time doing so much shit either prompting or spec writing that it might not feel worth getting things exactly right in case it makes you start all over again.
It's literally not as if with the LLM things are literally instantaneous, it takes upwards or 20-30 minutes to "Ralph" through all of your requirements and build.
If you start some of it yourself first and you have an idea about where things are supposed to go it really helps you in your thinking process too, just letting it vibe fully in an empty directory leads to eventual sadness.