How much value are you going to be able to extract over its lifetime once your customers want to see some additional features or improvements?
How much expensive maintenance burden are you incurring once any change (human or LLM generated) is likely to introduce bugs you have no better way of identifying than shipping to your paying customers?
Maybe LLM+tooling is going to get there with producing a comprehensible and well tested system but my anectodal experience is not promising. I find that AI is great until you hit its limit on a topic and then it will merrily generate tokens in a loop suggesting the same won't-work-fix forever.
The whole thing reminds me a bit of the many RAD tools that were supposed to 'solve' programming. While it was easy to start and produce something with those tools, at some point you started spending way too much time working around the limitations and wished you started from scratch without it.
[1] https://museumoffailure.com/exhibition/wonka-chocolate-exper...
There are limits to what even AI can do to code, within practical time-limits. Using AI also costs money. So, easier it is to maintain and evolve a piece of software, the cheaper it will be to the owners of that application.
Code that has not been thoroughly tested is a greater liability, not a lesser one.l, the faster you can write it.