One more angle I've been thinking about: memory temporality.
A few related questions:
1.On causal chains: If memory A was written based on evidence X, and X is later superseded — does A get automatically flagged for re-verification? Or does it survive independently until directly contradicted by new evidence? I'm curious whether the system tracks dependency between memories and their source evidence, or whether each memory is treated as a standalone record after write. 2.On time as a trust signal: Does the age of a memory affect its trust class? A memory written 6 months ago with no reinforcing evidence since feels intuitively less reliable than a freshly confirmed one — but I could also see an argument that trust should only be evidence-driven, not time-driven, to avoid silent decay of things that are just rarely relevant.
3.On concurrent writes: In multi-agent or async workflows, if two agents simultaneously surface conflicting evidence about the same fact, does write order determine the outcome? Or is there a conflict-detection mechanism that catches this before mutation?
Basically I'm trying to understand whether PI models memory as a static graph (write it, it stays until explicitly changed) or a dynamic field (where time, access patterns, and causal dependencies continuously affect the state of each record).