The barrier to entry has unquestionably dropped dramatically. As long as you have some programming foundation, a several-fold increase in productivity makes it entirely reasonable to choose technology stacks that you would never have seriously considered before. I have a programming background, had never studied WinUI 3, and yet it was still enough for me to build several native Windows applications that made it onto the Microsoft Store.
Of course, the more knowledge you have, the higher your chances of success. Using WinUI 3 again as an example, I definitely cannot fix bugs that Claude itself cannot fix, nor can I see the deeper potential problems beneath the surface. But it works, and that is already quite good. Just look at how many components in Microsoft's own Windows 11 do not work particularly well. That is what it comes down to: the barrier to entry has fallen dramatically, while the marginal returns of deeper learning are diminishing.
In the vibe coded world, if a bug is found (or a relied-upon api is deprecated, or a a dependency is found to suffer a security vulnerability, a vendor changes. etc) do we simply kill the codebase and vibecode up a fresh one de novo from the same prompts as the original, adding only knowledge of the recebt failure mode?
That sounds like a horrible plan, LLMs are non-deterministic (practically speaking, I know they can be run with temperature=0 locally, but not really relevant to the way anyone is writing code with them now).
Feeding the same spec in with some changes to deal with the one bug you discovered and regenerating all the code is likely to create a system that has new bugs (unrelated to the one you fixed by amending the spec) that may not have existed the last go-around.
You'll be playing whack-a-mole forever.
Are these chat apps built with one giant monolithic architecture? Seems like you could spin up isolated copies per organization and your scaling needs would be a lot lower and simpler. Then run everything in k8s with over subscription to deal with the compute overhead waste.