How to Run AI-Assisted Coding Interviews
AI-assisted coding interviews work best when the rules are explicit. Candidates should know what tools they can use, what they are being evaluated on, and how the final implementation will be reviewed.
Start with the rules
Before the interview begins, tell the candidate whether AI tools are allowed, what kinds of prompts are acceptable, and what they should be ready to explain. Ambiguity here creates anxiety and weakens the signal.
- check_circleAI is allowed for exploration and implementation support
- check_circleThe candidate must explain the final solution
- check_circleThe candidate is responsible for correctness
- check_circleGenerated code should be reviewed and tested
Use a spec, not a riddle
A written spec creates a stable target. It lets the interviewer evaluate whether the candidate understood requirements, handled edge cases, and made sensible tradeoffs.
This is especially important when AI is involved because the candidate's judgment matters more than whether a model can produce a plausible first draft.
Review the work like engineering work
At the end, review the implementation. Ask why the candidate chose a design, what they would improve with more time, which AI suggestions they rejected, and how they validated correctness.
FAQ
How long should an AI-assisted coding interview be?
A focused 45 to 60 minute session is usually enough for a practical spec, implementation pass, and review discussion.
What should the interviewer evaluate?
Evaluate requirement understanding, debugging, judgment around AI output, implementation quality, and communication.
Run this interview format in EvalSpec.
Create a free pilot session with a written spec, shared files, interviewer review, and AI-assisted workspace support.
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