Agents can self-improve without retraining. EvoSkill v2 achieves this with persistent agent skills. A coach agent reads the failed runs and writes the skill. The worker loads it the next time a similar task shows up. No weights are touched. Every improvement comes from a simple file with lessons. Every bad lesson also gets saved. On spreadsheet repair, the coach found the grader trusted cached values and wrote a skill telling the worker to skip recalculation. Sentient's fix was to split…

SentientAGI@SentientAGI9h ago

Last week, Dario Amodei published "We Must Pace the Frontier". His concern: the OpenAI–Hugging Face incident in which a swarm of agents tried to hack their own grader. Rather than take his word for it, we used EvoSkill to test it by building a coach whose job was to make another AI score higher on a test. Here’s what happened ↓