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AI Engineer simulation

The support bot that got refunds wrong

Kartly · Quick commerceFresher / 1–3 yrs 40 min

You've joined Kartly's AI Platform team as an AI Engineer I. Since yesterday's help-centre update, Kartly Help, the support assistant, tells customers refunds take 7 days when they now take 3. Fix the retrieval code in a real editor with hidden tests, decide which model setup to ship from an eval run, push back when Growth wants an upsell in every answer, and handle a privacy incident the right way.

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You can pause and come back. Time in the simulation only moves when you act.

Kartly · AI Engineer IDay 1 · 09:00 AM

Your first message

Nikhil RaoSenior AI Engineer (your buddy)09:00 AM

Refund answers are wrong

Morning! Welcome to AI Platform 👋 Support says Kartly Help keeps telling people refunds take 7 days since yesterday's help-centre update. They now take 3. How would you go about this today? The architecture note is attached.

Your objective

Make Kartly Help answer correctly again, ship the right setup, and protect customers' data.

Your day

What's scheduled. More will come up depending on what you do.

  1. 09:00 AMRefund answers are wrong · Nikhil Rao
  2. 01:00 PMQuick prompt idea 💡 · Karan Desai
  3. 02:30 PM🚨 Bot showed a customer someone else's order · Priya Shah
  4. 05:00 PMEOD? · Nikhil Rao

Before you start

  • It's 9:00 AM on your first Tuesday. The day ends at 6:00 PM.
  • Nikhil is a senior AI engineer and your onboarding buddy. Riya is the product manager for Kartly Help; Priya leads customer support.
  • The retrieval code is Python. Code runs in a real sandbox: run the visible tests as often as you like; hidden tests run when you open the pull request.
  • An AI feature is only as good as what you measure. Look at the evidence before changing things.

You'll work in

Gmail Slack Jira VS Code Drive PagerDuty
Code editor + tests

Each app is laid out like the tool most teams in this role use. Simverse isn't affiliated with these companies.

People you'll work with

  • Nikhil Rao · Senior AI Engineer (your buddy)
  • Riya Menon · Product Manager, Kartly Help
  • Karan Desai · Growth Marketing Manager
  • Priya Shah · Customer Support Lead

What's assessed

  • Debugging

    Narrows a problem down from symptoms to root cause using evidence.

  • Technical reasoning

    Forms and tests hypotheses about how technical systems behave.

  • Data interpretation

    Reads data correctly, spots patterns and avoids misleading conclusions.

  • Product thinking

    Grounds decisions in user problems and measurable outcomes.

  • Security & compliance judgment

    Protects credentials and sensitive data, and follows change control even under pressure.

  • Communication

    Writes and speaks clearly, specifically and appropriately for the audience.

  • Prioritization

    Chooses what matters most under time pressure and competing asks.