Technical interviews for the AI-native engineering era.
Meritoso helps engineering teams run AI-transparent work-sample interviews that measure how candidates solve, verify, and own real software work with AI.
From task to hire signal
Debugging
Testing
Tradeoffs
Interview follow-up ready
The old technical screen is losing trust.
AI assistance is now normal in software work, but many hiring loops still treat it as invisible cheating or try to solve it with surveillance-first controls.
LeetCode-style tasks reward memorization.
Teams need evidence of debugging, testing, code review, and tradeoff judgment.
AI bans are brittle.
Hidden AI use, overlays, and second-screen help make simple pass/fail screens noisy.
Take-homes create candidate friction.
Unbounded assignments can feel like unpaid labor and still leave authorship unclear.
Make AI use observable, legitimate, and scored.
Meritoso reframes the interview around real work samples where candidates can use AI transparently and hiring teams evaluate the human judgment around the output.
Problem framing
AI steering
Debugging
Testing
Tradeoffs
Code ownership
How a Meritoso interview works
A focused 60–90 minute work sample, built for signal without turning the process into surveillance.
Run a realistic repo task.
Debug, extend, review, or triage code that resembles day-to-day engineering work.
Set an explicit AI-use policy.
Candidates know what is allowed, what must be disclosed, and what will be evaluated.
Capture process evidence.
Review the solution, tests, reflection, AI interaction summary, and follow-up prompts.
Score with a human rubric.
Hiring teams evaluate judgment and ownership instead of outsourcing the decision to AI.
Built for teams actively rethinking SWE hiring.
Meritoso is for engineering-heavy companies where TA and engineering leaders need a better signal than puzzles, proctoring, or oversized take-homes.
VP Engineering / CTO
See whether candidates can reason, verify, and own AI-assisted code.
Technical recruiting leaders
Reduce ambiguity around AI use while protecting candidate experience.
Talent operations
Create structured evidence packets that support calibration and process analytics.
Questions buyers are asking
If AI is allowed, what are we evaluating?
Problem decomposition, AI steering, testing, debugging, tradeoffs, and ownership.
Is this proctoring?
No. The goal is higher-quality evidence, not pretending hidden AI can be perfectly detected.
Is Meritoso making automated hiring decisions?
No. The concept centers human review with structured evidence and clear rubrics.
Help shape AI-transparent technical interviews.
We’re speaking with engineering and talent leaders adapting software interviews for a world where AI is part of real work. If this is on your roadmap, schedule a short call and let’s compare notes.
Schedule a call