The rapid development of prototypes using AI tools has created a misconception that the hard work of software development is reduced, when in fact, the critical judgment and expertise required to build production-grade systems remain unchanged. Learning computer science fundamentals is still essential to understand and critique AI-generated code, and engineers who master both the new tools and the old skills will be better equipped to build reliable software. This shift requires operating at a higher level of abstraction while maintaining a deep understanding of the underlying systems. AI summary
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