Ask HN: How are you solving long-term memory for production AI agents in 2026?
Specifically interested in teams who moved past demos into real production workloads. Mem0, Zep, custom solutions — what's actually working and what keeps breaking?
Simple vector search + keywords + bm25 + text match + RRF. We specifically avoided graph construction due to associated costs. Everything is in just one sqlite file. Works fine for up to a few million document chunks.
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