I think the interesting shift is that AI changed the bottleneck from writing code → understanding systems deeply enough to review what’s being generated. A lot of generated code looks correct because it works initially, but production problems usually appear around scaling, edge cases, security, state management, or long-term maintainability. Feels like the developers who benefit most from AI are the ones who already understand architecture well enough to challenge the output instead of blindly accepting it. We’ve been seeing similar discussions while helping founders structure scalable AI-assisted products at FoundersBar: https://foundersbar.com