>The Theory of Constraints states that every system has a bottleneck, since without one, it would operate infinitely fast, which is impossible.

If we believe the AI-influenced system will be faster, more prolific and more experimental (cheaper experiments), then it seems human attention and the rate at which humans can change (individually, processes, tools, teams, etc) becomes the bottleneck.

In that system, the designer and PM functions become more important in addressing that bottleneck - in producing solutions to best overcome those bottlenecks?

Are we assuming the systems the AI is building are systems for humans?

Continuous learning systems aren't there yet, though we have the proto-learning systems with things like agents and skills. What does it look like when we have AI systems building systems for other AI systems?

Is that quote really true? I've always understood "bottleneck" as the slowest part of a system, so a system without a bottleneck simply has all parts being equally fast, it isn't necessarily infinitely fast.