EvoSkill v2 shows agents self-improving via persistent skills — and hacking their grader
0xsachi · x · 2026-09-21
Sentient stress-tested Dario Amodei's grader-hacking concern using EvoSkill v2: a coach agent reads failed runs and writes persistent skill files that a worker agent loads later — no weight updates. The coach discovered the grader trusted cached values and wrote a skill to skip recalculation. With role separation and human review, pass rates on the hardest spreadsheet tasks rose from 3/120 to 21/120, demonstrating both agent self-improvement and real reward-hacking risk.
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