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Anthropic·Software Engineer·Technical Phone Screen·Senior

Senior
May 2026

Summary

Interviewed for a software engineering role at Anthropic and got hit with the classic LRU cache design question. Not a bad experience, but the follow-ups on thread-safety and extending to TTL or LFU caught me a bit flat-footed.

Questions Asked (1)

Q1

Design and implement an LRU cache with get and put operations both running in O(1) average time. Walk through the data structure choices and implementation.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

I knew the hashmap plus doubly-linked list answer cold, so the base implementation went fine.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a hash map combined with a doubly linked list to achieve O(1) operations. Walk through the design, explaining how get and put maintain the LRU order, and discuss edge cases and potential optimizations.

Pro tip: Mention that using a doubly linked list with sentinel nodes simplifies edge cases and reduces bugs, and discuss how this design can be extended to handle concurrency or persistence if needed.

1. Clarify Requirements

Ask about cache size, eviction policy, thread safety, and expected operations to ensure alignment with the interviewer.

2. Propose Data Structures

Explain that a hash map provides O(1) access to nodes, and a doubly linked list maintains recency order for O(1) updates.

3. Detail Operations

Describe how get moves a node to the front, and put inserts or updates while evicting the least recently used node when capacity is exceeded.

4. Handle Edge Cases

Discuss scenarios like updating an existing key, cache size of 1, and null keys/values, and how sentinel nodes simplify implementation.

5. Analyze Complexity and Trade-offs

Confirm O(1) average time for both operations, and mention space complexity O(capacity) and potential trade-offs with alternative designs.

Key Points to Mention

  • Hash map for O(1) key lookup, mapping keys to nodes in the linked list.
  • Doubly linked list to maintain access order, with most recently used at the head and least recently used at the tail.
  • Sentinel nodes (dummy head and tail) to avoid null checks and simplify insertion/removal.
  • Eviction policy: when capacity is reached, remove the tail node and its corresponding hash map entry.
  • Thread safety considerations: mention that a single-threaded implementation is typical, but locks or concurrent data structures can be added if needed.
  • Alternative implementations (e.g., using OrderedDict in Python) and their trade-offs.

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