Anthropic·Software Engineer·Technical Phone Screen·Senior

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Jun 2026Remote

Summary

Coding round at Anthropic for a software engineer role, focused on web crawler implementation. They pushed for a multithreaded version after the basic solution, which is where things got interesting.

Questions Asked (1)

Implement a web crawler that starts from a given URL and visits all reachable pages sharing the same hostname. You have access to an API that returns all URLs found on a given page. Walk through both a single-threaded and a multithreaded solution.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

The single-threaded BFS part was fine, queue plus visited set, pretty standard.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases, then present a BFS-based single-threaded crawler using a queue and a visited set. For multithreading, discuss a thread pool with a concurrent queue and synchronization, and compare trade-offs like speed, complexity, and politeness.

Pro tip: Emphasize the importance of politeness (rate limiting, robots.txt) and avoiding duplicate work; this shows you consider real-world constraints beyond just correctness.

1. Clarify Requirements and Edge Cases

Ask about scope: same hostname only, handling redirects, robots.txt, rate limiting, and error handling. Confirm whether the API is synchronous and if there are any constraints on concurrency.

2. Design Single-Threaded Solution

Use BFS with a queue and a visited set to avoid cycles. Start from the given URL, fetch URLs via API, filter by hostname, and enqueue unvisited ones.

3. Design Multithreaded Solution

Use a thread pool and a thread-safe queue (e.g., concurrent queue) with a shared visited set protected by locks or a concurrent set. Workers dequeue URLs, fetch, filter, and enqueue new URLs.

4. Discuss Synchronization and Termination

Explain how to avoid race conditions (e.g., double-checked locking for visited set) and how to detect completion (e.g., using a counter of active tasks or a poison pill).

5. Compare Trade-offs and Optimizations

Compare single vs multithreaded in terms of speed, complexity, and resource usage. Mention optimizations like connection pooling, rate limiting, and distributed crawling.

Key Points to Mention

BFS vs DFS: BFS is more suitable for crawling due to level-order traversal and easier rate limiting.
Visited set: must be thread-safe in multithreaded version; consider using a concurrent hash set or locking.
Hostname filtering: ensure only URLs with the same hostname are enqueued; handle subdomains carefully.
Politeness: implement rate limiting and respect robots.txt to avoid overloading servers.
Termination detection: in multithreaded crawler, use a counter of pending tasks or a poison pill to know when to stop.
Error handling: handle network errors, timeouts, and malformed URLs gracefully.

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