Contextual Memory Virtualisation
Chat history is too weak a substrate for serious work; context needs state management.
Signal summary
Contextual Memory Virtualisation points toward a future where LLM working context is managed more like versioned state: snapshots, branches, continuation, trimming, and reuse. The signal is that context is no longer just "the prompt." It is becoming an operating surface.
Why it matters
Long-running AI work breaks when continuity is informal. If a system cannot tell what happened, what changed, which branch matters, and what can be safely compressed, then the user must carry the continuity burden manually.
LGI reading
This aligns with HKE's canonical spine, handoff patterns, and stewarded vaults. LGI's opportunity is to translate this research direction into practical systems where context is inspectable, recoverable, and governed rather than hidden inside a chat window.
Use this if you are thinking about
long-running AI work, memory systems, handoff, context engineering, continuity, and AI workspaces that need to persist beyond a single chat.
Related LGI concept
HKE Continuity
Related signals