Technical assessments for the AI era
Candidates work on a real repo with their own AI tools. They clarify under-specified requirements via a PO chatbot and ship a PR. You score real work, not puzzles.
3 free pilots open for DACH engineering leaders.
The problem
Leetcode and take-homes stopped carrying signal.
Candidates finish them in 10 minutes with Claude or Copilot. You see who can operate a tool. Not who can solve problems.
The job of an engineer has shifted: read ambiguous requirements, work with AI, make decisions inside business constraints.
Classical assessments don't measure any of that.
How Arena works
From clone to rubric-scored review
- 1.Candidate clones a real repo.
- 2.Task is intentionally under-specified. A PO chatbot answers clarifications but leaves ambiguity on purpose.
- 3.Candidate works in their own IDE, with their own AI tools, at their own pace.
- 4.Pushes a feature branch, opens a PR.
- 5.You score commits, diff, tests, and PO transcript against a rubric.
What gets measured
Signals from real work
- ·Problem identification under ambiguity
- ·Requirements clarification and communication
- ·Code quality under real constraints
- ·Decisions, not syntax
Why now
Every company hires engineers who work with AI.
No company measures it properly. Arena closes that gap.
Founder
Dominik Opwis
Engineer
Previously shipped product and platform work at startups and SaaS teams; now building hiring assessments that match how engineers actually work with AI.
Based in Germany. EU hosting (Neon Frankfurt).
Pilot slots open
3 free pilot slots open. Trial on a real applicant or on an already-hired engineer as a calibration benchmark.