A growing disconnect between AI adoption and actual AI competency is becoming apparent across development teams. Recent discussions on developer forums reveal a troubling pattern: organizations are deploying large language models without internal expertise to properly evaluate or understand them. Many teams lack even basic comprehension of how these models work, creating a significant knowledge gap that threatens project reliability. This expertise shortage has become a bottleneck preventing teams from confidently shipping AI-powered features and assessing whether their implementations actually work as intended.