AI-assisted

Structured

Evidence-first

Vibe coding interviews.

Candidates build with an AI assistant. You see every prompt, review, and fix — then your team decides.

One round, twenty seconds.

A real task, an AI assistant, and the working trace your team reviews.

Your team sets the bar.

A real task from your backlog, a rubric, and the AI assistant switched on.

Task45 min · AI assistant on
Assignment
Repair a rate-limited API endpoint
Keep the public interface, handle concurrent requests, add tests for the boundary cases.
Rubric
Prompt clarityCode reviewDebuggingTool judgment

Your team sets the task and the bar.

Four signals. One rubric.

Score the decisions you can see — never intent.

Prompt clarity

Goals, constraints, and edge cases stated before the tool acts.

Look for · constraints made explicit

Code review

Output challenged with reasons — not accepted on faith.

Look for · assumptions caught

Debugging

Cause isolated and verified — not retried blindly.

Look for · diagnosis before retry

Tool judgment

Accept, revise, or reject — each call made deliberately.

Look for · deliberate overrides

Where it fits.

Screen first. Run the assisted round. Review with evidence.

Screen
AI screening round
Vibe coding round
this format
Your review
humans decide

Vibe coding questions.

The direct answers before you bring us a role.

What is a vibe coding interview?

A structured technical round where the candidate uses an AI coding assistant on a realistic task. It evaluates the prompts, review decisions, debugging steps, and final result — not only whether the code runs.

Should candidates use AI in interviews?

When AI-assisted development is part of the job, a dedicated structured round reveals real tool judgment. Add an unassisted round when you also need to assess fundamentals directly.

Does it replace the coding interview?

No — they answer different questions. This round shows how a candidate directs and corrects AI; an unassisted round shows how they reason alone. Many teams run both.

Can it detect over-reliance on AI?

The trace shows when output is accepted unchecked, decisions can't be explained, or failures go undiagnosed. Treat those moments as evidence for human review — not proof of intent.

Best for.

AI-native engineering teams

Senior + staff roles

Platform & backend

Agencies & staffing

Any role where building with AI is part of the actual job.

See judgment in the open.

Watch a candidate prompt, review, debug, and decide — live.