SkillGLoW: agents that remember procedures, not tasks, gain 17.2 points with 3.6x smaller memory
rohanpaul_ai · x · 2026-09-06
SkillGLoW argues self-improving agents should store reusable solution procedures rather than every past task: task-specific details are rebuilt at inference instead of persisted. It gains 17.2 points with a 3.6x more compact library, and validates memory updates in real execution, rejecting changes that degrade performance. Less memory, better agents.
Related event: SkillGLoW: Agent Memory Shrinks 3.6x While Scores Rise 17.2 Points(2 posts)→
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