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This paper introduces a method for self-evolution of open-ended dialogue skills using future-feedback prediction, converting conversational feedback into a fixed offline objective to enable reproducible skill optimization without live traffic. The approach achieves over 75% prediction accuracy on a privacy-preserving sales-assistant dataset.