AI & Technical question
Build the payment API for a charity event.
- DoorDash
- AI & Technical
- Medium
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What this question tests
Technical product thinking for a payments system, including compliance, reliability, and a scoped MVP.
How to approach it
- Clarify scope: one time donations for a single event, or a reusable API for recurring charity campaigns.
- Identify requirements: PCI compliance for card data, receipt generation for tax deduction purposes, and refund handling.
- Decide build versus buy: use a payment processor like Stripe for card handling rather than building raw payment infrastructure.
- Design the API surface: create donation, get donation status, issue refund, and generate tax receipt endpoints.
- Address reliability: idempotency keys to prevent double charges, and webhook handling for asynchronous payment confirmation.
- Define success as payment success rate, charge failure rate, and time to generate a tax receipt after donation.
What a strong answer includes
- Correctly chooses to build on top of an existing processor like Stripe rather than reinventing card handling and compliance.
- Names a specific real requirement, PCI compliance and tax receipts, that a generic 'build an API' answer would miss.
- Proposes idempotency keys explicitly, showing awareness of a common real world payment bug, duplicate charges.
- Gives an illustrative number, e.g. assumes targeting a 99.9 percent payment success rate excluding user declined cards.
Common mistakes
- Proposing to build raw card processing instead of using an existing PCI compliant processor.
- Ignoring double charge risk and idempotency, a classic and serious payments bug.
- No mention of receipts or compliance needs specific to charitable donations.
Likely follow-up questions
- Why would you build on Stripe instead of your own processor?
- How would you prevent duplicate charges?
- What would you do if a webhook confirming payment never arrived?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 1: Foundations: the model and the decisions it forces on you
- Chapter 8: Evals: define good and make the number defensible
- Chapter 6: Agents and agentic architecture