AI Skill Debt Doesn't Show Up Until You Need It
A worker who ships clean output and a worker who understands what they shipped look identical on a dashboard. They stop looking identical the first time something breaks.
The competence doesn't disappear when AI does the work. It migrates into the model, and the person looks just as capable right up until the moment you need someone who can explain what they shipped three different ways.
The nerve two pieces hit this morning is the same one: a "post-literate" workforce in one, "seductive, but ultimately ineffective" AI tutoring in the other, both describing passive consumption quietly replacing the effortful practice that builds durable skill. One end is the classroom, the other is the org chart. Same pipeline.
The output looks fine, and that's the trap. AI accelerates whatever you already do, so a team with real fluency gets more good, faster. A team that never built the fluency gets polished output it can't evaluate, and no way to tell which version is the one that needs to change.
A worker who understands the work and a worker who outsourced it look identical on a dashboard.
This is why adoption metrics lie to you. They count usage, not understanding. They can't see the difference between a person who got faster and a person who stopped learning.
I don't know how fast this compounds, whether the bill lands in two quarters or two years. But it's a debt, and it doesn't show up on the cost line. It shows up the first time something breaks and the only thing that knew how to fix it was the model.
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