The vibe coding maximalist position can be stated in information theory terms: That there exists a decoder that can decode the space of useful programs from a much smaller prompt space.

The compression ratio is the vibe coding gain.

I think that way of phrasing it makes it easier to think about boundaries of vibe coding.

"A class that represents (A) concept, using the (B) data structure and (C) algorithms for methods (D), in programming language (E)."

That's decodeable, at least to a narrow enough distribution.

"A commercially successful team communication app built around the concept of channels, like in IRC."

Without already knowing Slack, that's not decodable.

Thinking about what is missing is very helpful. Obviously, the business strategic positioning, non technical stakeholder inputs, UX design.

But I think it goes beyond that: In sufficiently complex apps, even purely technical "software engineering" decisions are to some degree learnt from experiment.

This also makes it more clear how to use AI coding effectively:

* Prompt in increments of components that can be encoded in a short prompt.

* If possible, add pre-existing information to the prompt (documentation, prior attempts at implementation).