The 97% cost reduction figure is the one that should get more attention. Re-injecting full conversation history on every turn is a silent killer for autonomous agents running at scale.

The part I'm curious about: how do you handle temporal conflicts? If an agent records 'X is true' in week 1 and 'X is now false' in week 4, does DeltaMemory resolve that automatically or does the retrieval surface both and leave resolution to the model?

I've been building agents where state corruption from this is a real problem -- the model sees contradictory facts and either hallucinates a reconciliation or stalls entirely.