How do you design an AI customer support agent for a system design interview?

Place a controlled orchestrator around the model: verify identity and risk, retrieve versioned support passages, let the model propose an answer or typed tool, enforce deterministic policy, require approval for write actions, and hand low-confidence or sensitive cases to a human.

When should an AI support agent require human approval?

Require approval before actions that move money, cancel service, change customer or security data, or create another material effect. Treat proposal, approval, execution, and confirmation as separate states.

How should an AI customer support agent be evaluated?

Evaluate complete journeys using grounded-claim rate, correct tool choice and arguments, unsafe-action rate, approval-policy compliance, handoff quality, resolution rate, repeat contacts, p95 latency, and cost per safely resolved conversation.

Design an AI Customer Support Agent

hardNewAIAI AgentGuided AnswerCustomer Support

Problem statement

AI customer support agent system design interview guide covering RAG, citations, safe tool execution, order and refund actions, approval gates, confidence routing, human handoff, cost limits, agent evaluation, architecture diagrams, and a live example.

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Design an AI Customer Support Agent

Problem statement

The full solution is part of HelloFrontend Pro

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