In their recent paper, "Optimal design of the Barker proposal and other locally balanced Metropolis–Hastings algorithms," Giacomo Zanella and colleagues propose a method to compare the performance of complex algorithms within a class. Their work addresses the challenge of maintaining efficiency as algorithmic dimensions expand, providing valuable insights for practitioners navigating the intricate landscape of algorithm design. Zanella emphasizes the crucial role of statistics in optimizing algorithmic performance, underscoring the necessity of careful design choices to avoid potential catastrophes in application.