Testing known time in Agent Memory on a 2,200-year corpus

A SurrealDB Agent Memory experiment uses the 47-page, 2,200-year narrative of Aeon’s Surreal Renaissance to test “known time,” the point at which a reader or agent learns a fact, alongside valid time and system ingest time. By assigning each story page an in-world observedAt timestamp and querying memories with asOf dates, the test verifies that revelations remain hidden before their narrative appearance, become available at the correct point, and can supersede prior beliefs without erasing historical versions. The examples include place-name revelations, discovery of the story’s calendar year, changing project plans, and recurring cycles in which the same attribute receives different current values over time. The post also distinguishes time-based filtering from scope-based lenses, which restrict an agent to a particular narrative track or epoch, and argues that this model is useful beyond spoiler prevention for replaying conversations, analyzing decisions, handling backfilled records, and reconstructing what was believed at a particular moment.

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