AI is automating the hands-on work that used to train junior engineers, severing the implicit supply chain that produced senior engineers with judgment. Historically, hiring juniors delivered both productive labor and on-the-job apprenticeship; AI splits that bundle by taking the labor while erasing the training subsidy. Industry leaders already flag an apprenticeship crisis, and the trajectory mirrors recent DRAM shortages - demand can explode while supply takes years to grow, so senior talent will become scarce and expensive when everyone tries to buy finished seniors at once.
The practical hedge is to grow seniors internally now rather than maximize short-term leverage by having a few seniors run fleets of agents. The high-leverage move is “fan out through people”: have each senior mentor several juniors and teach them to drive their own agents, giving juniors contained, testable real work that builds judgment. The fast-path nine-agent-per-senior model (e.g., 5 devs, 45 agents reporting 3x output) boosts throughput but accelerates the training collapse. Startups chasing immediate product-market fit should favor raw speed; any organization that intends to be here in five years must treat mentoring as strategic insurance, because a senior’s most valuable output in the agentic era is more people who can produce with judgment.
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