I very recently looked at the codebase of a vibe-coded app made by someone with domain expertise but no software dev experience.
It was very clear to me that he had described it from his POV to an AI, and the AI had implemented features in a manner that technically worked, but made future maintenance or expansion extremely tricky, which is why he was now looking for a dev.
For example, in his data schema, for every item on a menu, instead of simply having an array property like so for ingredients:
items["latte"]["ingredients"] = ["water", "milk", "sugar", ...]
He had individual flags for every item for every possible ingredient it could have or not have: items["latte"]["has_milk"] = true
items["latte"]["has_nutmeg"] = false
items["latte"]["has_cinnamon"] = false
items["latte"]["has_sugar"] = true
...
This technically worked and passed tests from his POV at an MVP level. But added a lot of complications when actually trying to build more features or when a new menu item had ingredients the founder hadn't thought to include in the schema beforehand.I totally get how he ended up where he did though. While describing it to the AI, he probably said something like "store info on each menu item's ingredients, they might have milk or coffee or sugar", and the AI created individual flags for them and he didn't think to question it, because he didn't know what's "right" or "wrong", but then as he kept building the AI stuck with keeping individual flags instead of swapping it out with an array mechanism, and he couldn't have known the correct way to implement it.
Only a dev with experience would know how to describe the system to an AI model to get an output that works well, and how to assess the quality of its output beyond what can be assessed through the basic UI. This wasn't a QA failure, it was a design failure.