According to God of Prompt on X citing @aarondotdev and Anthropic, a controlled study of 52 junior software engineers learning a new Python library found AI-assisted learners scored 50% on code comprehension versus 67% for hand-coders, with only a non-significant two-minute speed gain (p=0.01), as reported by X posts referencing the Anthropic paper. According to Anthropic’s earlier research cited by @aarondotdev, developer productivity can increase by roughly 80% when developers already possess the underlying skills, indicating the performance gap emerges during skill acquisition rather than expert execution. As reported by the X thread, developers who delegated end-to-end tasks to AI scored under 40%, while those who used the same tool for conceptual questions exceeded 65%, underscoring that tutoring-style prompts improve learning outcomes. Business takeaway: according to the cited Anthropic findings, enterprises should avoid placing day-one juniors on AI-assisted workflows before they build manual debugging fundamentals, and should train teams to use Claude for conceptual scaffolding rather than vending-machine style delegation to mitigate code quality and maintainability risks.