AI Answer Monitoring and Auditing
The routine of querying multiple assistants on a schedule with real customer questions and recording the answers, the ordering of recommendations, and the sources cited.
Analogy Mental model
Sending a mystery shopper to every salesperson in town each week to ask which three products they recommend, why, and where they heard about them.
In practice What you actually do
Build a tracking set of a hundred prompts in three groups: category recommendations, head-to-head comparisons against named competitors, and brand questions about pricing and reputation. Run them weekly and store the raw answers, because the trend in the source list is where the actionable signal lives.
Where people get burned Pitfalls
Doing this by hand does not scale past a few dozen prompts. Script it against the provider APIs with retrieval enabled, or use a monitoring platform, and keep the raw responses so you can re-analyse them when the question changes.
This entry was written in English from the Chinese original, not machine-translated. Read the Chinese version →