Jev Gates Agent Memory Saves

The author used Jev to check whether proposed agent memories were supported by the original conversation and guide whether to save, skip, or defer them. On 100 synthetic cases at a .40 cutoff, Jev kept 39 of 50 memories labeled worth keeping and saved no candidates labeled skip or defer; its median gate latency was 250 ms.

Open source time250 ms for Jev

Jazzlike_Musician_2 in r/AI_Agents@Jazzlike_Musician_2

Tried using Jev to check what an agent should remember We've been trying Jev for agent memory, mostly to catch cases where the saved note says more than the original conversation did. Think "we might use Postgres" turning into "we chose Postgres." Once that gets saved, the next conversation starts from a decision nobody actually made. We gave Jev the original text and a proposed memory, then used its judgments to decide whether to save it, skip it, or leave it undecided. We ran the same setup with Luna as a comparison. On 100 synthetic cases, using a .40 cutoff, Jev kept 39 of the 50 memories labeled worth keeping. Luna kept 41. Neither saved a candidate labeled skip or defer. Median gate latency was 250 ms for Jev and 1,593 ms for Luna, including network time. Then we checked what happen

Sep 23, 2026Reddit postsView on Reddit

The author compared the same setup with Luna, which kept 41 of 50 memories labeled worth keeping and also saved no skip or defer candidates. The stated latency includes network time.

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