Frame the task
Clarify acceptance criteria and inspect the existing files before asking AI to write code.
9 live AI-assisted interviews
Practice coding with AI under interview scrutiny
Work in a multi-file repository, use an integrated coding assistant, and show how you frame prompts, review suggestions, debug mistakes, and retain ownership.
What interviewers evaluate
AI output is visible. Your judgment is the signal.
Delegate deliberately
Use focused prompts for bounded work instead of handing over the entire problem.
Review critically
Inspect suggestions for correctness, security, maintainability, and fit with the repository.
Own the result
Validate the final workspace and explain which decisions were yours, adapted, or rejected.
Audited assistant chat
The assistant sees the public task and current workspace. Prompts and responses are retained so feedback can distinguish tool output from your review and implementation choices.
Live interviewer follow-ups
The interviewer probes requirement gaps, weak assumptions, unreviewed suggestions, validation quality, and your ability to explain the final code without outsourcing ownership.