Daily brief · 23 September 2026
Pilots do not fail on accuracy
The post-mortems blame the model. The transcripts almost never do. What actually kills a working pilot.
What happened
Reviewing a year of abandoned AI pilots, the stated reason is usually model performance. The actual reason almost never is.
Why it matters
The pattern is consistent. The pilot worked. The person whose job it touched kept checking every output, because nothing told them when the system was unsure.
Without an uncertainty signal, a human has to verify everything — which means you added a step rather than removing one.
What to learn
Three questions for any model going near a workflow:
- How does it signal that it is unsure?
- Who set the threshold where it stops and asks?
- What does the audit trail show six months later?
What to try
Find a pilot that quietly stopped being used. Ask the user what made them go back to the old way. It will not be accuracy.
Worth stealing
The scoring sheet: adoption odds can veto the whole score, whatever the other columns say.