Technical interviews for engineers who work with AI. Evaluate their decisions, inspect the evidence, and follow up on the tradeoffs that matter.
Both open without signup. Or book a walkthrough.
Illustrative scenario
Illustrative interview · not a candidate result
Keep deliveries tenant-isolated, retry safely, and explain what happens when delivery fails.
AI proposal
Retry failed requests.
Useful direction, but it leaves duplicate delivery and tenant boundaries unspecified.
Candidate decision
Scope idempotency to each tenant and event, bound every retry sequence, and expose delivery status instead of hiding uncertainty.
key = [tenantId, eventId]
maxAttempts = 5
status = 'pending'A strong engineer connects implementation to consequences: who can access it, what happens under load, and how someone recovers when it fails.
Review the evaluation methodWould you trust them to own this?
Use the work to guide the conversation. A polished demo is a starting point, not a hiring decision.
After the hiring decision is recorded, your team can approve a private growth report with evidence-backed strengths and a practical next step.
Candidate can receive
Demonstrated strengths, growth areas, and an approved closing note
Company data stays private
Scores, rank, hiring outcome, reviewer notes, and integrity events
Candidate report
Maya Chen · Backend engineer
Preview only · no data is being changed
Private candidate report
Demonstrated strength
You reproduced the failure before changing the implementation.
Growth focus
Compare cache invalidation strategies before accepting the patch.
Suggested next step
Write the test that would expose a stale read in an AI-generated data layer.
Keep evaluation anchored to work evidence. DevEval makes the reviewable inputs explicit, avoids behavioral inference, and leaves the hiring decision with your team.
Review security and data practicesThe assessment window lost focus three times. This may deserve a closer look, but it does not explain why it happened.
Make the policy call to see how DevEval handles the event.
Integrity events are review prompts. They are not proof of misconduct or a standalone rejection reason.
Human decision requiredOpen the candidate task and recruiter report without creating an account. Then review the evaluation method and trust documentation on your own time.
Maya Chen · Backend engineer
Review complete
One cache invalidation tradeoff is ready for live follow-up.
Candidate task
No signup required
Recruiter report
Demo data clearly labeled
Evaluation method
Measurement boundaries published
Hiring decision
Human review required
A credible hiring product should be specific about fit, limits, and who remains accountable.
Yes, when the screen is configured for AI use. The useful signal is what happens after generation: what the candidate trusts, what they challenge, how they verify, and whether they can explain the decision.
No. DevEval organizes work evidence, scoring context, reviewer notes, and follow-up prompts. Your hiring team remains responsible for advancing, rejecting, and communicating with candidates.
Repository work can add depth for finalists. Earlier in the funnel, bounded tasks with known evaluation criteria are easier to compare and require less company context before a candidate can demonstrate judgment.
A reviewable record containing the available task results, candidate decisions and reasoning, review outcomes, reviewer notes, and focused follow-up prompts. Replay and integrations depend on the selected workflow and plan.
Starter is designed for exactly that: one focused hiring need, 10 candidate sessions each month, one launch-ready work template, evidence packets, and candidate-safe shareback.
Bring one role. We will map the screen, the evidence, and the live follow-up your team actually needs.
