Google WikiSkill paper: Agents reuse experience to outperform larger models
mark_k · x · 2026-08-28
Google Research published "WikiSkill," a method where agents turn execution traces into persistent knowledge stored in a wiki, allowing skills to compound over time.
Results: Qwen 3.5 9B with evolved skills achieved 47.4% accuracy, beating Qwen 3.6 27B without skills (39.4%). On SpreadsheetBench, Qwen 3.6 27B jumped from 40.8% to 81.7% using these skills.
Cross-model transfer: Skills learned by one model often transfer effectively to others, sometimes outperforming self-learned skills. This suggests a key path for agents: accumulating experience to improve capabilities over time, rather than just scaling model size.
Related event: Google's WikiSkill Turns Agent Experience into Reusable Knowledge(4 posts)→
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