This source critiques the current state of AI programming, characterizing it as a repetitive process where AI rewrites code for similar tasks instead of reusing existing modules, unlike human programmers who leverage modularity and shared libraries. The author argues that true AI intelligence in programming requires the ability to abstract, reuse, and adapt code components across different projects, envisioning a future where AI systems possess their own "function libraries" and can intelligently assemble and optimize code. This shift from code generation to intelligent reuse is presented as the key to advancing AI from a "code generator" to a genuine "code engineer." The text emphasizes that this capability of knowledge transfer and application is fundamental to intelligence itself.