Anthropic·Software Engineer·Technical Phone Screen·Senior

Senior

Jun 2026

Summary

Debugging-focused technical screen for a software engineer role at Anthropic. The question was a single scenario-based problem and the whole conversation basically lived or died on how deep you could go with it.

Questions Asked (1)

You're debugging a production issue and the captured stack trace is incomplete. Only the bottom few frames are visible and there's no context about what called into them. Walk through how you'd investigate.

Root Cause AnalysisTechnical Trade-offs

Author's notes

This one had more layers than I expected.

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AI HintsAI Generated

Suggested Approach

Start by acknowledging the challenge of incomplete stack traces and emphasize a systematic, hypothesis-driven approach. Walk through how you'd gather additional data from logs, metrics, and recent changes, then form and test hypotheses to isolate the root cause. Conclude by discussing how you'd prevent similar issues in the future.

Pro tip: Mention that you'd check if the incomplete stack trace is due to inlining or tail-call optimizations, and consider using debug symbols or a debug build to get more context. Also, highlight the importance of correlating with deployment events or feature flags.

1. Gather Context

Collect all available information: full logs around the error, metrics (CPU, memory, latency), recent deployments, configuration changes, and any related alerts. Identify the affected service and its dependencies.

2. Reproduce and Isolate

Try to reproduce the issue in a staging environment or with a targeted test. If not possible, use production debugging tools (e.g., dynamic tracing, profilers) to capture more detailed stack traces or execution flow.

3. Analyze the Visible Frames

Examine the bottom frames to identify the functions and modules involved. Look for patterns: are they in a specific library, handling a particular input, or part of a known problematic code path?

4. Form and Test Hypotheses

Based on the context and visible frames, hypothesize what could have called into them. Use binary search or instrumentation to narrow down the caller. Check for common issues like null pointers, race conditions, or resource exhaustion.

5. Implement Fix and Prevent Recurrence

Once root cause is identified, apply a fix (hotfix or rollback) and monitor. Then, improve observability (e.g., better logging, stack trace capture) and add tests to prevent similar issues.

Key Points to Mention

Correlate with recent code changes or deployments using version control and CI/CD logs.
Use distributed tracing (e.g., OpenTelemetry) to reconstruct the call path across services.
Check for compiler optimizations (inlining, tail calls) that may truncate stack traces; use debug builds or symbols.
Leverage production debugging tools like eBPF, dynamic instrumentation, or core dumps if available.
Consider environmental factors: load spikes, memory pressure, or network issues that could trigger the error.
Document the investigation and share findings to improve team knowledge and incident response.

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