The ability to differentiate good and bad architectures seems to be a lost art because to build this ability you need to have enough experience (e.g. the discussion in "The Mythical Man-Month"). Most software developers today have had no experience designing even a single system and many systems are often a random assortment of stuff thrown together by people without enough experience. What I call the "sort of works" architecture. It has big gaps but it sort of works and so there is continuous investment in trying to make it good, which is often a waste of time. You've lumped a bunch of stuff together to build something and now you're stuck with it.

AI as it is right now is probably a driver to make this worse because it makes it so much easier to throw random stuff together.

Thanks to LLMs.

Before LLMs even if the architecture principles were simple and clear, distilled into templates + codegens added for boilerplate / skeleton generation ... It was impossible to follow them on the long run. Devs tried their best, but on the long run everything eroded and there were no resources for refactoring.

Now, with coding agents, I was able to create a production grade app following a similar architecture to Presentation Domain Data Layering, from this article.

Now the codebase is 100% uniform both in content (code) and structure (files and folders). It's like being written by a single person. Finding a specific file takes a second with no cognitive load. Editing a file is straightforward since every file follows a specific template.

LLMs have benefits and drawbacks, and in this case their help is enormous.

Is architecture operations?