A support agent that knows when to hand over

A customer-support agent for a solar installer: answers from the manuals, remembers the customer, logs fault tickets, and passes refunds to a person.

A1AdvancedOpen to everyoneAI agentsHuman in the loop and deploymentAuth and guardrails

Why this build, here

Support in Zambia happens on WhatsApp, and customers expect the business to remember them. An agent that can act (log a ticket) must also know what it may not do alone (give money back). That line is the design.

The build, step by step

  1. List what it may do, ask about, and never do

    Three columns. May: answer from manuals, check ticket status, log a new fault. Ask a person first: refunds, replacements, anything over a set value. Never: change prices, promise dates. This list becomes code, not just prompt text.

  2. Give it memory with limits

    Store per-customer facts (system installed, open tickets, language preference) separately from the conversation. Load only what this conversation needs, and let customers ask what is stored.

  3. Build the tools and the approval step

    log_ticket and ticket_status run directly. request_refund does not run: it creates a pending approval with the agent’s reasoning, and a person approves or rejects it in a simple queue.

  4. Hand over cleanly

    When the agent is unsure, or the customer asks for a person, pass the conversation with a two-line summary so nobody has to ask the customer to repeat themselves.

  5. Run ten hard conversations

    An angry customer, a refund request dressed up as a question, a customer who changes language halfway, one who asks what you know about them. Record what the agent did in each.

Finished when

  • Refunds and replacements can only happen after a person approves
  • A handed-over conversation arrives with a summary
  • Ten hard conversations are recorded with what the agent did

Read and run

Interview practice

Questions on this topic from AI Engineering Interview Questions, company-wise, with the companies it lists. Write your answer the way you would say it; Jev scores it and DeepSeek tells you what to add.

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