I Built a Memory System for AI Agents That Actually Forgets

Every AI agent memory system I've used (Mem0, Honcho, Hindsight) has the same problem: they...

martedì 23 giugno 2026 New tab

TL;DRAI

Recall-sqlite implements tiered memory that auto-forgets old data; 6 months of use: 80ms latency, 1.5MB fixed footprint with 1469 memories. Manager tech value: production memory without token bloat or vector DB, zero-setup pip install vs Mem0/Honcho overhead.

164 words~1 min read

Every AI agent memory system I've used (Mem0, Honcho, Hindsight) has the same problem: they accumulate forever. Old facts pollute retrieval. More tokens → worse results. Your agent gets slower and dumber over time.

So I built recall-sqlite — a memory system that actually forgets.

The core idea: tiered storage. Memories are automatically promoted or demoted based on how often they're accessed.

Hot tier (~500): ANN + keywords + FTS5 — fast full retrieval

Warm tier (~5K): Keywords + FTS5 only — 66-99% less compute

I Built a Memory System for AI Agents That Actually Forgets

I Built a Memory System for AI Agents That Actually Forgets

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