AI writes unarchitectes code if you don't have a system for developing and maintaining a consistent architecture over time. In human coding, a lot of architecture decisions tend to only live in human brains, communicated through ephemeral means (text chats, voice calls, etc) and are not concretely documented. Since LLMs don't really have a way to manage long running architectural decisions (memory systems can only get so far, like it won't capture architectural decisions if you never talk about architectural decisions), you have to (have your agent) capture architecture design within the repository.

I personally like using openspec for this, because it makes the model iteratively ask you architectual decisions, and then manages creating and accessing the documents as needed.

Let him who is without sucking among you, suck the first stone.

> The problem with AI SE is that AI writes un-architecture-ed code

Not necessarily. I use SOTA models with established stacks like .NET which allow my agent to easily follow decades of best practiced patterns (DI, EF Core, ASP.NET Core...) so you still and up with proper architecture.

In fact I can easily still manually inspect everything bc I already know how it's supposed to be written.