Many chatbots stall for the same reason. Unanswered questions build up and nothing changes. Teams ship a release and move on. Users try again and give up. The way out is simple. Treat every miss as a signal. Capture it in a standard way. Decide whether it was noise or a real gap. Turn real gaps into small updates in guardrails or knowledge. Run that loop every week. Measure how fast it moves. Results improve without bigger models.
Start with lean instrumentation
Analytics only works if the trail is short and consistent. Capture the user message, the decision the assistant made, the sources it consulted, the final answer, and any fallback it used. Record time to first token and time to full answer. This gives a clear picture of what happened and why. Long logs feel thorough but slow teams down. A compact record gets read and acted on.
Define unanswered with clear rules
The question is in scope and relevant, yet the reply has no supporting citation or source
A fallback was needed to finish the turn such as clarify, retrieve, or hand off
Confidence is below your threshold or the reply uses hedging language like "not sure" or "I think"
The user reasks the same thing within a short window
Retrieval returns nothing useful or cannot locate the expected document
The reply conflicts with the current knowledge base
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