The "90/90 Rule".

With #AI, getting the first 90% of the feature built takes 10% of the time. But getting the last 10% (making it actually work reliably or correctly in production or at scale) takes the other 90% of the time.

This is the part that demo culture wants to sweep under the rug. And that part that casual observers can't comprehend.
This has always been true about software, but it's amplified with AI because you get to the first point sooner, and the second half takes even longer.
It seems like a paper like this drops every other week... https://arxiv.org/abs/2601.20245
How AI Impacts Skill Formation

AI assistance produces significant productivity gains across professional domains, particularly for novice workers. Yet how this assistance affects the development of skills required to effectively supervise AI remains unclear. Novice workers who rely heavily on AI to complete unfamiliar tasks may compromise their own skill acquisition in the process. We conduct randomized experiments to study how developers gained mastery of a new asynchronous programming library with and without the assistance of AI. We find that AI use impairs conceptual understanding, code reading, and debugging abilities, without delivering significant efficiency gains on average. Participants who fully delegated coding tasks showed some productivity improvements, but at the cost of learning the library. We identify six distinct AI interaction patterns, three of which involve cognitive engagement and preserve learning outcomes even when participants receive AI assistance. Our findings suggest that AI-enhanced productivity is not a shortcut to competence and AI assistance should be carefully adopted into workflows to preserve skill formation -- particularly in safety-critical domains.

arXiv.org
@heapwolf hence the subsequent "100% != 100%" rule