AI & Technical question

An enterprise customer says the agent resolves routine cases quickly, but in high-stakes conversations it sometimes gives incorrect or off-brand answers. How would you investigate root cause, choose immediate mitigations, and decide whether the fix belongs in configuration, prompts/policies, workflow design, retrieval/data, or a new platform feature?

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What this question tests

Tests root cause investigation for a high stakes conversational failure and the judgment to route the fix to the right layer of the system.

How to approach it

  1. Pull the specific failing high stakes conversations and review them with a human evaluator to categorize the failure, wrong fact, off brand tone, or wrong policy applied.
  2. Check if the failure correlates with conversation complexity or ambiguity, since high stakes cases often involve more nuanced multi step reasoning.
  3. Rule out a configuration or prompt issue first, since it is usually the fastest fix if the agent is misapplying an existing policy.
  4. Check retrieval and data quality for the specific topics involved in the failing conversations.
  5. If the issue persists after prompt and data fixes, consider it a workflow design gap, meaning these cases need a different flow or a human handoff.
  6. Apply an immediate mitigation, such as adding a lower confidence threshold that triggers escalation for this case type, while the root cause fix is built.

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