01
Problem and crux
The first version of the AI inbox was designed to answer common guest questions automatically. Testing raised a more important question: did users want maximum automation, or did they still need control over the final message?
02
Assumptions to test
We initially expected automatic replies to create more value. User testing showed otherwise. Property managers wanted AI to prepare the response, but they wanted to review it before anything was sent.
03
What I did
I changed the product from automatic replies to AI-generated drafts. Users could approve the draft, edit it or replace it before sending. I also introduced evaluation criteria for relevance, tone, language, booking context and the amount of correction required.
04
Evidence and result
More than half of active accounts used AI Draft in its first month. Some users reported saving up to two hours per day.
05
Relevance to AI safety operations
This work gave me practical experience with human oversight, evaluation criteria and product decisions shaped by where users need control. Those habits matter when an AI system can act on consequential information.