You call it "lack of ambition", implying a certain arrogance; more humble people might just call it "a different sweet spot" of AI integration. After all, the goal in the end is not to use up as many AI tokens as possible, but the goal is to implement/perform a certain business case in the best way possible with regard to cost/speed/quality.
It's not like everyone using AI has the same software development cycle. It's not even that everyone using AI is developing software.
I propose that there is no such sweet spot.
If the model cannot perform the task with adequate quality while being many times faster and cheaper than a human, it is not good enough in my view.
If a SOTA model would be good enough, surely that would be preferable to a human using cheap AI assistance for a moderate efficiency improvement.