RRSI is a method for evolving AI agent harnesses that avoids overfitting to training benchmarks through regularized search constraints. The approach improves performance on held-out benchmarks by controlling edit magnitude, requiring measured gains to exceed variance, and eliminating benchmark-specific logic, with all candidates logged for transparency.