A new position paper proposes a robustness layer for Mixed-Integer Linear Programming engines to detect when small input perturbations invalidate optimal plans. The authors argue that current optimization pipelines ignore the gap between solve-time assumptions and real-world deployment. This audit tool provides solver-backed evidence to quantify solution trust for industrial practitioners.