Engram blog: RL training complements text memory, stays robust through millions of token edits
canaesseth · x · 2026-11-05
The Engram team published a blog investigating how RL complements text-based memory by teaching models how to use their notes. Key findings: training is cheap compared to building the notes, and performance stays surprisingly robust even through millions of tokens of memory edits, making agents more intelligent, cost-effective, and robust.
Related event: Engram: RL Trains Models to Use Their Notes, Boosting Accuracy at Low Cost(6 posts)→
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