The paper highlights the importance of post-solve robustness in Mixed-Integer Linear Programming (MILP) decision engines, addressing how small perturbations can affect solution feasibility and optimality. It proposes a new evaluation layer to enhance trust in decision-making systems by assessing their robustness under various conditions.