One dynamic that AI coding has introduced is that features grow and are more "complete" or "complex" after their first development iteration compared to coding pre-AI. An example of this is that I recently built a web crawler for an internal documentation site at my company. My design for scraping, parsing, vectorizing and indexing the data was far more complex/complete than if I had not used AI. This is primarily due to my lack of knowledge in the space and general time constraints for the project.

That increased complexity, while less costly than before, still added time/cost to the project in terms of cognitive load and testing that otherwise wouldn't have been there had the design been "dumber". This notion of increased design complexity could be thought of as a form of Parkinson's Law where the complexity of the design grows to fill the time available.

I think AI is certainly making us write code faster but how much time is really being freed up now that writing code is cheaper? I get the impression that we are often just finding other things to fill that freed up time with, increased design complexity being one of those things.