The goal was not speed. It was correctness under pressure.
What I learned surprised me.
Autonomous fixes can work reliably in some cases — but there are classes of failures where allowing automatic execution is actually more dangerous than slow human intervention, even with full test coverage.
Some examples:
- Tests that validate behavior but not in-variants - Implicit contracts that aren’t encoded anywhere - Fixes that restore correctness locally while degrading system-wide guarantees - “Successful” patches that narrow future recovery paths
In several cases, the correct action for the system was to stop entirely, even though a patch existed and tests were green.
I ended up introducing hard constraints where autonomy must halt, and treating refusal as a valid outcome — not a failure.
I’m curious how others reason about this boundary:
Where should autonomous systems stop, even if they can technically proceed?
How do you encode that line without just re-introducing humans everywhere?
