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This paper introduces SEA, an architecture for self-evolving agents that confines self-modification to a steering adapter and versioned harness around a frozen base model, using anytime-valid gates to audit modifications against a fixed error budget. Experiments on SWE-bench Verified with four base models show that the suite provides a +4 to +5% improvement on strong base models while preventing regressions.