Lessons tagged “verification”
5 published lessons with this tag.
Supervise exceptions, not output
Toyota's jidoka principle — automation with a human touch — builds machines that stop the line and signal when something is out of spec, so humans supervise exceptions instead of inspecting everything. Applied to AI collaboration: define out-of-spec explicitly (missing provenance, no falsifier, contradiction flagged, format broken), let mechanical gates check every output, and spend your attention only on what stops the line.
Verification debt
Every AI output you accept without validation is verification debt: trust extended without collateral. Like financial debt it is sometimes the right trade — speed now, checking later — but it compounds quietly, concentrates in the claims you reuse most, and eventually some decision defaults on it. The discipline is not zero debt; it is visible debt: know what is unverified, cap it, and pay it down on the claims your decisions actually load-bear.
Verify delegation is working
Delegation without verification is abdication. Build lightweight checks to ensure delegated work meets your standards.
Trust but verify
Trust your agents and systems — but build verification into the process, not as an afterthought.
Workflow checkpoints
Build verification points into workflows to catch errors before they propagate downstream.