Every résumé is AI-polished and every take-home is AI-assisted. We vet engineers on the one thing a model can't fake for them in the room: explaining and defending code they actually shipped, under adversarial questioning.
You can't tell who's real anymore.
Résumés are polished by AI, take-homes are done by AI, and leetcode is gamed. The signals you relied on now measure the tools, not the engineer. And a senior mis-hire — someone who can ship but can't reason about what they shipped — is one of the most expensive mistakes a team makes.
Each candidate sits a Defensible Work Review on their own or open-source work, defended interview-style — not a synthetic puzzle, and never their employer's proprietary code.
Every load-bearing decision, in order, each motivated by the problem the last one created. Understanding, not recall.
The hardest questions a staff engineer would ask about the design — asked live. We watch whether they can defend or fold.
You get the write-up, not just a pass/fail — the decisions, the trade-offs, how they answered. Judge the signal yourself.
A model can write the code and polish the résumé. It can't sit in the room and defend the reasoning for them.
Stack, seniority, and what "good" means for your team.
Each has passed a Defensible Work Review on their real work — with the write-up so you see the evidence.
Start from a shortlist that's already demonstrated it can defend real work — skip the candidates who only look good on paper.
| Signal | What it measures | AI-proof? |
|---|---|---|
| Leetcode | Synthetic puzzle-solving | No — gamed / memorized |
| Take-home | Output quality | No — AI does it |
| Résumé / portfolio | Claims | No — AI-polished |
| Defensible Work Review | Can they defend real shipped work, live | Yes — AI can't do it for them in the room |
We're onboarding our first cohort of hiring teams. Tell us your open role and what a good-fit hire is worth to you — we'll go from there. No upfront cost to look.
Request first lookA working engineer who works on JVM internals and the problem of why code ends up the way it does — by hand, not a generator. The review is a real adversarial conversation about the candidate's own code.
We expect a success-fee model — you pay when you actually hire, nothing upfront to look. We're setting the exact number with our first cohort, so tell us what a good-fit hire is worth to your team.
Mainstream backend/full-stack and systems roles, mid-to-senior. Tell us the role and we'll say honestly whether we can vet for it.
Honestly: we're early and the pool is small and growing. This is first-look access to a vetted cohort, not a volume firehose — we'd rather undersell it.