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The ability to develop crisp mental models around the problems you want to solve and understanding the why before you start working on the how is an increasingly critical skill, especially in the age of AI. Coding is one of the things AI does best and its capabilities are quickly improving. However, there’s a catch: Code created by an AI can be syntactically and semantically correct but not functionally correct. In other words, it can work well, but not do what you want it to do. Having a crisp mental model around a problem, being able to break it down into steps that are tractable, perfect first-principle thinking, sometimes being prepared (and able to) debate a stubborn AI — these are the skills that will make a great engineer in the future, and likely the same consideration applies to many job categories.
I recently told my daughter, a college student: If you want to pursue a career in engineering, you should focus on learning philosophy in addition to traditional engineering coursework. Why? Because it will improve your code.