AI has definitely shifted the bottleneck from writing code to evaluating decisions.

One thing I'd add is that AI-generated code often passes code review because it looks clean. The real review should focus on architecture, failure modes, security boundaries, and whether the implementation actually matches the business intent.

I've also noticed teams getting better results when AI is treated as a fast implementation partner rather than an autonomous engineer. The quality of the system still comes down to the questions humans ask, the constraints they define, and the production standards they enforce.

The responsibility never moved from engineers it just moved higher up the stack.