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Marco Argenti, Chief Information Officer at Goldman Sachs, writes about how 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. Therefore, having a crisp mental model around a problem is particularly important.
Zooming out a bit, the dependency of AI performance on the quality of the mental models expressed by the user prompting the AI suggests a fundamental shift in the relationship between authors and readers, and, in general, to our relationship to knowledge.
https://hbr.org/2024/04/why-engineers-should-study-philosophy
