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Arulnidhi_k

1 karma · joined December 25, 2025

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Arulnidhi_k··on Show HN: Aegis Memory v1.2 – We solved "what's worth remembering" for AI agents
Voting requires context.agents must specify 'why' something was helpful, not just thumbs up/down. This adds friction that reduces noise.

Here's the Effectiveness score that is implemented in the project: (helpful - harmful) / (total + 1), so marking everything helpful dilutes the signal rather than inflating it.

Along with it gotta pair voting with reflections, agents store "this worked because of X" not just "this worked."

May I know what setup you tried.. was it a single agent or multi-agent?

Arulnidhi_k··on Show HN: Aegis Memory v1.2 – We solved "what's worth remembering" for AI agents
Not yet in production, but actively looking for devs to test it and gain feedback..