Ai Coding And Product Systems hard
Your support bot resolves 60% of tickets, but CSAT on escalated tickets is very low. Users must type 'agent' three times to escalate, and agents then ask customers to repeat everything. Which change best balances deflection and experience?
- A Trigger handoff on low retrieval confidence, repeated rephrasing, or account-risk intents, and pass the agent a structured summary.
- B Require three failed answer attempts before any handoff so deflection rises and the human agent queue volume stays flat.
- C Keep the bot answering while a human agent silently monitors, and let the model itself decide when it has exhausted its knowledge.
- D Forward the raw transcript with no summary, since any model-written summary risks dropping details the customer already gave.
Answer: A. Trigger handoff on low retrieval confidence, repeated rephrasing, or account-risk intents, and pass the agent a structured summary.
Good handoff trades some deflection rate for **early, signal-driven escalation with context transfer**. Models are poorly calibrated about their own limits, so letting the model decide (C) leads to confident loops instead of escalation. A raw transcript (D) keeps every detail but forces agents to re-read long threads. The best practice is a structured summary with a link to the transcript.
One system design question a day, with spaced repetition so the ones you miss come back.
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