← Anthropic Interview Insights
Start by clarifying the requirements and edge cases, then design the data model and API contracts. Implement the operations with proper error handling and case-insensitive name handling, and discuss trade-offs and potential improvements.
Pro tip: Demonstrate maturity by discussing how you would handle concurrency and data consistency, and by suggesting idempotency for duplicate registrations.
Ask questions to understand expected return values for duplicates and missing recipes, and confirm that recipe names are case-insensitive but should preserve original casing.
Define data structures for recipes and ratings, and specify the API signatures for registerRecipe and rateRecipe, including return types and error handling.
Write code to register a recipe (checking for duplicates case-insensitively) and to rate a recipe (checking existence and handling duplicates).
Ensure proper handling of duplicate registrations, missing recipes, and case-insensitive lookups, returning appropriate values or exceptions.
Talk about concurrency, persistence, scalability, and potential improvements like idempotency keys or rating aggregation.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.