The issue is that you are always optimizing for the current state of the systems, not the _next_ state of the systems, within the bubble. You may be able to increase coherence for the current known set of problems, but you cannot know if that coherence will hold for the _next_ problem.
This is essentially the same issue as the halting problem. You don't know what you don't know, and you don't know what happens if you go just one more loop or explore just a little more about the universe, if all of the previous structures hold. Black swans happen all the time, and adaptability is about working within that matrix of data, absorbing it, and reconfiguring around it.
This is essentially the same issue as the halting problem. You don't know what you don't know, and you don't know what happens if you go just one more loop or explore just a little more about the universe, if all of the previous structures hold. Black swans happen all the time, and adaptability is about working within that matrix of data, absorbing it, and reconfiguring around it.