AI Engineer · September 26, 2026

Long-running agent memory: test provenance, uncertainty and privacy together

Long-running agent memory: test provenance, uncertainty and privacy together video thumbnail
Why it matters

Erina Karati’s publisher notes use a simulated game village to expose memory failures: agents can retain a topic while losing its source, certainty or implications for later plans. The proposed evaluation records observations, memory writes, retrievals and belief changes across complete scenarios. It freezes the harness and evaluator while searching a limited policy space. A corrected rumor example is illustrative; the talk does not claim repeated evidence of general improvement.

My takeaway: Build scenarios for source retention, rumor uncertainty, stale information, replanning and private-information containment. Separate remembered statements from current beliefs. Keep a policy change only when repeated runs improve the scorecard without weakening privacy or other constraints, and preserve rollback.
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