A good outcome does not automatically validate the decision-making process, as luck plays a significant role. Howard Marks stresses the importance of intellectual humility in recognizing that a successful result could have stemmed from wrong reasons or randomness, a crucial distinction for repeatable success.

True scientific progress comes from being proven wrong. When an experiment falsifies a prediction, it definitively rules out a potential model of reality, thereby advancing knowledge. This mindset encourages researchers to embrace incorrect hypotheses as learning opportunities rather than failures, getting them closer to understanding the world.

Howard Marks argues that declaring uncertainty is a sign of strength, not weakness. In important settings, saying "I don't know" signals that your ego is in check and thinking is robust. It makes people trust you more, not less, because it shows intellectual humility.

A founder must simultaneously project unwavering confidence to rally teams and investors, while privately remaining open to any evidence that they are completely wrong. This conflicting mindset is essential for navigating the uncertainty of building a startup.

The more people learn about a subject, the more they realize how much they don't know. This contradicts the idea that expertise leads to arrogance. Novices, who are unaware of a field's complexity, are often the most overconfident.

Physicist Brian Cox's most-cited paper explored what physics would look like without the Higgs boson. The subsequent discovery of the Higgs proved the paper's premise wrong, yet it remains highly cited for the novel detection techniques it developed. This illustrates that the value of scientific work often lies in its methodology and exploratory rigor, not just its ultimate conclusion.

To counteract the brain's tendency to preserve existing conclusions, Charles Darwin deliberately considered evidence that contradicted his hypotheses. He was most rigorous when he felt most confident in an idea—a powerful, counterintuitive method for maintaining objectivity and avoiding confirmation bias.

Beyond the mid-20s, the primary mechanism for rewiring the brain (neuroplasticity) is making a prediction and realizing it was wrong. This makes mistakes a biological necessity for growth and becoming more capable. It reframes errors not just as learning opportunities, but as the central, physiological catalyst for adult learning and improvement.

Current LLMs fail at science because they lack the ability to iterate. True scientific inquiry is a loop: form a hypothesis, conduct an experiment, analyze the result (even if incorrect), and refine. AI needs this same iterative capability with the real world to make genuine discoveries.