AI-native candidate assessments

Assess how candidates work with AI.
Not without it.

ScreenStack gives candidates a real codebase, AI access, and a production-shaped problem—then shows you how they direct, verify, and improve the work.

Launch a candidate assessment See how it works

candidate-assessment

// Find the race condition. Verify the fix.
async function checkout(order) {
  await verify("concurrent requests");
  return explain(
    "the tradeoff in the pull request"
  );
}

Why hiring teams move to ScreenStack

Hiring signal that matches how software is actually built.

The task looks like the job

Every assessment is a focused, production-shaped task in a working codebase. AI is allowed, but the candidate still has to understand the problem, verify the fix, and ship code that actually works.

See how they work with AI

The shipped code is only half the story. You also see how carefully they framed the problem, how they steered the model when it drifted, and whether they checked its output before trusting it.

It fits in 45 minutes

The whole assessment takes one focused sitting. No weekend take-homes, and no reason for strong candidates to walk away from your loop.

Evidence over opinion

The scorecard is generated automatically from the work itself: functional results, AI direction, verification habits, and code quality. No senior engineer needed to grade it.

See how it works

Modernize your hiring signal

Evaluate AI-assisted engineering work before you make the hire.

Buy a candidate assessment