The freedom to pick any language felt like a gift until I realized it just meant the burden of justifying my choice was entirely on me.
Start by clarifying requirements and constraints (e.g., expected scale, authentication, persistence) to show you think before coding. Then outline a minimal but extensible design: choose a stack (e.g., Node.js/Express or Python/Flask), define REST endpoints for questions, and plan data storage (in-memory or lightweight DB). Finally, walk through implementation details, trade-offs, and how you'd document and test the API.
Pro tip: Demonstrate production-awareness by discussing how you'd handle edge cases (e.g., pagination, input validation, error responses) and by mentioning how the design could evolve (e.g., adding answers, users, or full-text search) without over-engineering the initial version.
Ask questions to understand expected scale, authentication needs, persistence requirements, and whether tags are free-form or predefined. This ensures you build the right thing and shows you avoid assumptions.
Define resource-oriented endpoints: POST /questions, GET /questions (with query params for keyword/tag filtering), and GET /questions/{id}. Specify request/response formats, status codes, and error handling.
Select a lightweight framework and storage (e.g., in-memory for simplicity, or SQLite for persistence). Justify trade-offs between speed of development and production readiness.
Write handlers for each endpoint, including input validation (e.g., title/body required), tag parsing, and search logic. Ensure proper error responses for invalid input or missing resources.
Create a README with setup, run instructions, and example curl requests. Add basic tests (unit or integration) to verify endpoints and edge cases.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.