All four models reuse artifacts 94-98% of the time, yet their learning gains diverge widely
anirudhg9119 · x · 2026-10-09
The author probes why some agents barely improve:
- One clue: they don't reuse what they've learned — but reuse alone isn't enough.
- Four models reuse artifacts in 94–98% of relevant decisions, yet their gains differ widely.
- Even strong improvers often fail while actively using an artifact.
Takeaway: having memory does not equal learning effectively; reuse quality, not frequency, is the key variable.
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