Question
What does it mean that trust but verify?
Quick Answer
Trust your agents and systems — but build verification into the process, not as an afterthought.
Example: You delegate weekly reporting to an automated dashboard that pulls from three data sources. For the first month, you spot-check the numbers against the raw data every Monday. Week two, you find a silent API change that's been undercounting one metric by 12%. Without the verification checkpoint, that error would have compounded for months — and you'd have made decisions on bad data without ever knowing it. The dashboard earned more trust after you caught the bug and fixed the pipeline. Verification didn't undermine the delegation. It completed it.
Try this: Pick one system, tool, or person you've delegated a recurring task to. Define three things: (1) What does 'working correctly' look like in concrete, observable terms? (2) What is the cheapest verification check you could run — something that takes under 5 minutes? (3) At what frequency does that check need to happen — daily, weekly, monthly? Write these down. You now have a verification protocol for that delegation. Run the first check this week.
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Go beyond the answer
This topic is part of Delegate to AI Without Losing Judgment — a guided sequence of 16 lessons.
After completing this path you will run a working delegation boundary: a criteria framework for what goes to AI versus what stays with your judgment, specifications clear enough that AI output comes back usable, a verification practice that catches errors without redoing the work, and the warning signs of over-delegation before your judgment atrophies.
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