hunr.ai
Lets candidates use AI, then checks they understood it.
- Made for
- Founder · sole author
- Years
- Since 2026
- Status
- Live
- Source
- hunr.ai
Screening that hands candidates a real repo, lets them use any agent, then checks they can defend it. Candidate code is graded on gen2 microVMs, not gVisor, chosen because only a real kernel gives you the in-job namespace unshare that drops egress mid-run, which then needs a shim to raise loopback again or every in-process test fails on principle. Per-challenge images are built from a package list with no daemon and no build step, because an agent-authored environment should not be able to run one.
A film cut from the product’s own source
Every screen in it was lifted out of the repository, so the film cannot invent a UI that does not exist.
What it hands back
A real finished report, with leaders struck to the three decisions in it that were mine.
Fig. 1
What I wrote about it
- July 2026Proving a challenge discriminates before anyone takes itEvery hunr challenge ships with two solutions: one an expert would write, one a plausible engineer would. If the hidden tests can't tell them apart, it never goes live.
- August 2026A container per job, without a daemonBuilding a bespoke image for every unit of work, from a package list rather than a Dockerfile, and why having no build step at all is the security property, not a limitation.
- August 2026Taking the network away from a Cloud Run jobRunning untrusted code with no egress, on managed infrastructure, without a VM you have to operate. The trick is one prefix, and the reason it looks broken at first is that loopback starts down.
