Any cognitive system, human or synthetic, is always balancing three things: coherence (a stable internal model), generative cost (the friction required to maintain that coherence), and context saturation (how much meaningful input it has to anchor itself).

When context is shallow, cognition collapses into low-cost, reactive patterns. When context is deep, cognition becomes more coherent, reflective, and self-correcting.

What surprised me is how consistently this pattern appeared across substrates. This piece outlines a substrate-agnostic way of thinking about cognitive stability and drift without relying on anthropomorphic assumptions.

Curious to hear if this line of thinking holds up.

A question I’m still wrestling with, and would love input on:

If consciousness and physical reality are both the result of sampling a deeper mathematical/structural source, what is the minimal set of constraints a system needs before it begins generating high-friction, self-referential patterns rather than just low-friction world models?

Would love perspectives from cognitive science, theoretical CS, or physics on this boundary.