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Anthropic·Software Engineer·Technical Phone Screen·Senior

Senior
May 2026

Summary

Anthropic SWE interview with an iterative debugging exercise on a tokenizer. You fix one bug, they immediately ask what breaks next. Kept me on my toes the whole time.

Questions Asked (1)

Q1

A tokenizer implementation has already had one bug fixed. Run it again, find the next defect, explain how the first fix exposed it, show what input now fails, and describe the correct behavior.

Algorithms & Data StructuresRoot Cause AnalysisTechnical Trade-offs
Author's notes

This one tripped me up more than I expected.

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AI HintsAI Generated

Suggested Approach

First, explain how the previous fix changed the tokenizer's behavior, likely by altering control flow or state, which exposed a latent defect. Then, construct a minimal input that triggers the new failure, trace through the tokenization steps to pinpoint the root cause, and describe the expected correct output. Finally, propose a robust fix and discuss how to prevent similar issues.

Pro tip: Demonstrate that you understand the tokenizer's contract and invariants; show that you can reason about edge cases and state transitions, not just patch symptoms. Mention that you would add regression tests for both the original and new bugs.

1. Understand the previous fix

Review the code change that fixed the first bug. Determine what behavior was altered and how it might affect other parts of the tokenizer.

2. Identify the new failure

Run the tokenizer with a variety of inputs, focusing on edge cases related to the previous fix. Find a minimal input that produces incorrect output.

3. Trace the root cause

Step through the tokenizer's logic for the failing input. Identify the exact condition or state that leads to the defect, and explain how the previous fix exposed it.

4. Describe correct behavior

State what the tokenizer should output for the failing input, referencing the tokenizer's specification or expected invariants.

5. Propose a fix and prevention

Suggest a code change that addresses the root cause without breaking existing behavior. Recommend tests to cover this and similar cases.

Key Points to Mention

  • The importance of understanding the tokenizer's specification and invariants.
  • How the previous fix might have introduced a regression by changing state or control flow.
  • The need to find a minimal reproducible input that isolates the defect.
  • Tracing through the code to identify the exact root cause, not just symptoms.
  • Describing the correct output with reference to the tokenizer's contract.
  • Proposing a fix that is minimal, safe, and accompanied by regression tests.

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