@omarsar0: Agents can self-improve without retraining. EvoSkill v2 achieves this with persistent agent skills. A coach agent reads…
Summary
EvoSkill v2 enables AI agents to self-improve without retraining by using persistent skills stored in files, with a coach agent writing lessons from failed tasks, leading to significant performance gains in tasks like spreadsheet repair.
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Cached at: 09/19/26, 04:46 AM
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 the roles. The agent that writes skills cannot touch the test. A person reviews the results after every round.
With that in place, the hardest spreadsheet tasks went from 3 passes out of 120 to 21.
Sentient (@SentientAGI): 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
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