Our process tests architecture judgment, code quality under review, and AI-readiness — all on real production cases.
THE PROBLEM
Four dimensions our vetting is built to measure — each one tested on real, production-grade work.
We evaluate the work your product depends on — maintaining an API that handles 50,000 requests per hour, not solving a graph puzzle in 45 minutes. Different skills, and we test the one that ships.
An active CTO can assess whether an architecture decision is sound or a mistake that will cost months — judgment a keyword screen can't reach.
Remote delivery runs on communication, documentation, and autonomy — so we test exactly those, on real async scenarios.
Across our engagements, an engineer fluent in AI tools delivers 30–40% faster. We measure that fluency directly, applied to real engineering tasks.
5 PILLARS
Real scenarios with real constraints: scale, budget, team size, existing technical debt. We evaluate reasoning about trade-offs and the ability to communicate technical decisions to non-technical stakeholders.
We review the candidate's real code — something built in production, not an interview exercise. We look at clean structure, error handling, testing discipline, separation of concerns, and readability.
We evaluate effective use of GitHub Copilot, Cursor, Claude, and similar tools. Prompt engineering applied to real engineering tasks. And most importantly: judgment for knowing when AI output needs human review.
Written clarity, verbal fluency, ability to raise issues proactively, and timezone discipline. Remote work doesn't fail due to lack of technical skill — it fails when communication breaks down.
Employment verification, real professional references, and cultural alignment with startup and scale-up environments. We look for engineers who have worked on products with real users.
THE FUNNEL
Each stage eliminates profiles that don't fit — not people, but profiles that couldn't deliver in the context of our clients.
100% of candidates enter the process.
40% pass. Initial screening of experience, stack, and production work.
20% pass. Written clarity, verbal fluency, timezone discipline.
12% pass. Pair programming with an active CTO on real problems.
10% pass. Employment history, confirmed professional references.
Final 4%. Ready to deploy on client projects.
final acceptance rate