I would argue that there isn't an underlying general pattern of coherence, at least not one that is measurable in a simple way. The simulation in the article simplifies representations of the world into nodes and edges, but reality is often much more nuanced and complex.
I think the section on Futures really points out how difficult problems can be. They were first introduced in the 1970s, they were implemented in the 80s. They didn't become super relevant until the late 80s/early 90s, and even then it took another 20 years of data gathering, experimentation, and distillation across the entire academic domain AND the industry and all of its real world use cases to really nail them down.
This is basically similar to how prices act as a decent signal of value to a point, but break down because they destroy information about what was actually valuable by simplifying it. The same would be true of an abstract measurement of "complexity" when applied universally to all problems, unfortunately.
I think the section on Futures really points out how difficult problems can be. They were first introduced in the 1970s, they were implemented in the 80s. They didn't become super relevant until the late 80s/early 90s, and even then it took another 20 years of data gathering, experimentation, and distillation across the entire academic domain AND the industry and all of its real world use cases to really nail them down.
This is basically similar to how prices act as a decent signal of value to a point, but break down because they destroy information about what was actually valuable by simplifying it. The same would be true of an abstract measurement of "complexity" when applied universally to all problems, unfortunately.