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In Prasad Rane’s coding interview, an AI assistant was available but could not help debug or implement the solution. The task was to fix bugs in an unfamiliar codebase under time pressure. Rane’s account points to a practical lesson for candidates: being able to read the repository, follow a failing test, and explain a focused change mattered more than simply having an AI tool nearby.
This is one person’s experience, not a description of every AI-assisted interview or a known scoring rubric.
What happened in the interview?
Rane describes an interview in which he had to find and fix bugs in code he had not written. The assistant could not help with debugging or implementation, so he had to investigate the repository himself. As he put it, “The AI assistant was right there in my coding interview. It wasn’t allowed to help me debug.”
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesThe challenge was not just spotting a suspicious line. Code only makes sense in context: what calls a method, what assumptions the caller makes about its inputs, and where the method’s results go. Rane’s takeaway was that “A line can look suspicious in isolation and still be doing exactly what its caller expects.”
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He does not disclose the interviewer’s complete scoring rubric. His account therefore supports a lesson about his own experience, not a claim about what employers generally evaluate.
What should you practise for an AI-assisted coding interview?
Practise diagnosing a reproducible bug in a small repository with a working test suite. The aim is to build a repeatable way to understand behavior before changing code—not to memorise a particular fix. Rane recommends practising within the expected tool restrictions when debugging help may be unavailable.
- Establish the baseline. Run the existing tests and note which pass and which fail before making changes.
- Read the relevant test. Inspect its setup, inputs, dependencies, and assertions. A failing assertion tells you where behavior differs from expectation; the surrounding setup can help explain why.
- Trace the behavior. Follow the code involved in the failure: identify what calls the relevant method, what inputs it receives, and how its result is used. You do not need to read the entire repository first. As Rane puts it, “Reading every file isn’t a prerequisite.”
- Form a possible cause. State what you think is wrong, then compare that explanation with the test and execution path before editing.
- Make a focused change. Rerun the relevant tests and inspect nearby behavior that could be affected.
- Review and explain the diff. Be ready to connect the change to the cause you identified. A passing test is useful evidence, but explaining why the change addresses the failure shows how you reasoned about the code.
How do you debug an unfamiliar codebase?
Start from the observed failure and follow the narrowest path that can explain it. Read the failing test closely, then move between the test and the code it exercises. Check how the relevant function is called, what inputs it can receive, what assumptions surrounding code makes, and where its output goes. That context helps distinguish a real defect from behavior that only looks wrong when one line is viewed alone.
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Keep the investigation tied to evidence: compare your explanation with the test setup and code, make one focused change, and rerun the relevant tests. Then look for nearby behavior the change could affect. This approach avoids both extremes—editing after a quick glance and trying to understand every file before making any progress.
What should you ask about AI permissions?
“AI available” does not by itself explain what assistance is permitted. Before the exercise begins, ask what the assistant may do in that specific interview. For example:
- Can it explain unfamiliar code or repository structure?
- Can it suggest or write code changes?
- Can it investigate a failing test or debug the issue?
Clarifying those boundaries helps you prepare for the actual task rather than assuming that the presence of an assistant means it can participate in every part of the work. Rane says, “I don’t know the interviewer’s complete scoring rubric.” His account does not establish a universal set of permissions or evaluation criteria.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What does this experience establish—and what does it not?
It establishes what Rane reports about one interview: he faced an unfamiliar codebase and a time limit, and the assistant could not help debug or implement the fix. He recommends practising repository orientation, test interpretation, focused investigation, and clear explanations of changes.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11It does not show how common this interview setup is, what other employers allow, or how any particular hiring team scores candidates. Rane’s reflection captures the personal lesson: “The part of this interview that stayed with me was having to make sense of code I hadn’t written under time pressure.”
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