> if AI coded software works correctly, maybe it doesn't matter?

The problem isn't the amount of code, it's how fitting/unfitting the abstractions are. Wrong abstractions are bugs in waiting. If there's much code with wrong abstractions, future change becomes difficult.

Source: me, I've created many bad abstractions and they led to much pain...

Well, if tokens = cost, and verbosity = more tokens, then smaller code is a financial (and human!) win. Although I'm worried vibe coders are just going to have LLMs modify minified code in caveman mode so they can have 100 agents in a swarm..

On a more serious note, I wonder if this might eventually encourage people to use languages that are a little harder to write but much more concise (functional languages for instance). When you're paying per-token enterprise bean java style verbosity totally sucks

More verbose code takes up more space in the context. It's harder for humans to review, but also harder for future AIs to edit. Unless you manage to keep the AI to firm module boundaries & have it replace modules wholesale it's not really equivalent to how assembly gets replaced wholesale when a compilation unit changes. Compilers aren't editing the `.o` files when you rebuild, they throw the old ones out & replace them. But when you prompt an AI it is reading & editing the source files, so excess verbosity in the source files is detrimental.

But the truth is: it doesn't work correctly. I see quality of software dropped significantly.

At work we are integrating with third party platform to automate excel-powered calculations. It is awful. Rendering the table in browser takes 10s or one click on Export button will throw backend in OutOfMemory state.