@shanselman Scott, the paper frames the problem well but undersells one angle: the mid-tier. There is a huge population of devs who are not senior by title or years but have deep domain knowledge from living inside a product or industry for a long time. Those people get just as much of a boost as seniors, sometimes more, because they know exactly what to ask for and what to reject. The binary of "senior vs EiC" misses that.
The preceptorship model is solid in theory but I am not sure it addresses the deeper problem. My wife teaches first semester procedural programming and second semester OOP at university level. She switched to an inverse classroom model, students are engaged in lectures, homework comes back looking good, no questions, no pushback. Then exam time hits and the majority fails. My suspicion is that LLM generated homework mimics what a professor would expect closely enough that it does not flag as plagiarism, but the students never actually internalized the material. The cognitive debt from the paper is already showing up in education before these people even enter the workforce.
And from what I see with EiC colleagues who are already working: they use LLMs heavily on a daily basis with the same prompt-and-accept pattern. If that habit is already baked in by the time they start their first job, I am not confident a preceptorship program changes the dynamic. The mentor can explain and guide, but if the junior has no instinct to question AI output because they never built that muscle in school, you are fighting uphill.
The core thesis is right: stop growing juniors and you run out of seniors. But the pipeline problem might start earlier than the paper assumes, at the education level, not the first job.
Piotr Gaszewski
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