Closed systems, exemplified by the efficiencies seen in 'Moneyball' baseball, lead to predictable outcomes, but human life and complex systems exhibit chaotic elements, producing infinite outcomes. While optimizing systems can enhance efficiency, such practices may inadvertently make them more fragile, as illustrated by the Suez Canal incident that demonstrated the danger of being pushed to absolute limits without resilience. A focus on avoiding catastrophe, rather than squeezing out inefficiencies, is essential for individual success. The tension between optimization and resilience becomes crucial, especially in light of unpredictable global events like financial crises or pandemics. Machine learning excels in closed systems and can revolutionize sectors like healthcare, but its uncritical application to open systems poses risks, as it fosters an illusion of control that may lead to disastrous consequences. The comfort derived from regular patterns in daily life can create cognitive biases, distracting from the chaotic realities of the larger world, emphasizing the need for a balance between the two approaches to effectively navigate complexity.