Engram shows RL-trained note usage beats text-only agent memory on cost and robustness
scott_linderman · x · 2026-11-05
Engram published a new blog on the agent memory layer: AI-generated context is exploding and agents must re-read it every session, which will become too slow and expensive within 12 months. Their finding: RL can teach models how to use their notes, complementing text-based memory — training is cheap compared to building notes, and stays surprisingly robust even through millions of tokens of memory edits. Engram is building this memory layer combining text memories with training.
Related event: Engram: $373 RL run teaches models to use their notes(7 posts)→
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