Entry-level work is also training infrastructure. I think AI adoption needs to account for that.

I think the entry-level AI debate is also an apprenticeship debate. A lot of junior work was not only cheap output. It was training infrastructure. Drafting the memo, cleaning the spreadsheet, writing the first version, fixing the obvious bug, summarizing the research: these tasks taught people what good work looks like, where assumptions fail, and how a team makes trade-offs. If AI absorbs that layer, companies may get faster output while weakening the path that creates future senior people. So the question is not only "can AI do the junior task?" It is: "If AI does it, where does the junior learn the judgment this task used to teach?" That probably means beginner work shifts toward reviewing AI output, tracing sources, checking assumptions, scoping tasks, finding exceptions, and explaining decisions. "Learn AI" is too vague. Apprenticeship needs actual loops.