The use of artificial intelligence (AI) in software engineering and engineering more broadly has generated considerable discussion. While initial focus often centers on code generation as a primary application, it is important to note that various forms of automated code generation have existed for more than 20 years without making a meaningful impact on software engineering. AI-driven code generation, while capable of producing relatively simple functions, shares limitations with its predecessors and does not substantially address the more complex challenges inherent in software engineering. The protracted timelines and potential delays in software projects are typically attributable to factors such as complexity, errors, and communication inefficiencies, rather than solely the speed of code production.