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What "AI Oversight" Actually Means (And What It Doesn't)

Notes from the practice

"AI oversight" gets used loosely enough that it's worth being specific about what it isn't, first.

It isn't a compliance checkbox — a policy document nobody reads, signed off once a year. It isn't a slower process bolted onto a fast one, where every AI-assisted change waits in a queue for a committee. And it isn't a tool you buy that watches everything and alerts on nothing actionable.

What it actually is: a specific, small set of checks — security scan, test coverage, a named reviewer, a record of the decision — that run as part of shipping, not after it. The goal isn't to slow down AI-assisted work. It's to catch the handful of things that actually go wrong — a secret committed in plaintext, a test that got skipped, a change nobody can explain six months later — before a customer or an auditor finds them first.

Done right, oversight is close to invisible day-to-day. You notice it exists mainly when it catches something — which is the point.