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Anthropic·Software Engineer·Online Assessment (OA)·Intermediate

IntermediatePrefer not to say
Jul 2026Remote

Summary

Anthropic SWE interview, CodeSignal-style multi-level coding problem. Level 1 was a recipe service with two functions to implement. Felt manageable but the edge cases around case-insensitive matching and return values tripped me up more than I expected.

Questions Asked (1)

Q1

Implement a recipe service with two operations: one to register a new recipe owned by a user (with a name, timestamp, ingredients, and steps), and one to record a rating from a user for a named recipe. Handle duplicates and missing recipes with appropriate return values, and treat recipe names as case-insensitive.

API & IntegrationsData ModelingSystem Design
Author's notes

The core logic wasn't the hard part.

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AI HintsAI Generated

Suggested Approach

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.

1. Clarify Requirements and Edge Cases

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.

2. Design Data Model and API

Define data structures for recipes and ratings, and specify the API signatures for registerRecipe and rateRecipe, including return types and error handling.

3. Implement Core Logic

Write code to register a recipe (checking for duplicates case-insensitively) and to rate a recipe (checking existence and handling duplicates).

4. Handle Edge Cases and Errors

Ensure proper handling of duplicate registrations, missing recipes, and case-insensitive lookups, returning appropriate values or exceptions.

5. Discuss Trade-offs and Extensions

Talk about concurrency, persistence, scalability, and potential improvements like idempotency keys or rating aggregation.

Key Points to Mention

  • Case-insensitive comparison for recipe names while preserving original casing
  • Return values for duplicate registration (e.g., false or error) and missing recipe on rating (e.g., false or error)
  • Data structures: map for recipes keyed by lowercase name, list for ratings
  • Concurrency considerations: thread safety, locking, or atomic operations
  • Idempotency for duplicate registrations to avoid side effects
  • Potential extensions: rating aggregation, querying recipes, persistence

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.