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Self‑evolving agents acquire skills without scaling

This story is from 2026-08-27. It is preserved in the archive; the latest stories are on the live feed.

Agents that can rewrite their own simulated worlds and distill those rewrites into reusable modules now eclipse raw model scaling as the dominant path to higher accuracy. Two independent systems released this month demonstrate a co‑evolutionary loop where workflows become skills and feedback loops…

Read the full story at DEV Community — Machine Learning ↗

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  1. 2026-08-27 05:00 · DEV Community — Machine Learning
    Self‑evolving agents acquire skills without scaling

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