A crash is never a pass. Three rules that kept 1,095 eval runs honest.
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The scariest failure mode in an eval harness is not a wrong answer. It is a harness problem wearing a model problem's clothes. A test file that does not run looks exactly like a problem no model can solve. A sandbox flake looks exactly like a failed attempt. Before I trusted any number from my CS1 auditing tool, I had to make those confusions impossible, and it came down to three rules. Auditing AI-Solvability ยท Part 2 of 2 1 2 Part 1 of this series reported scores from 1,095 sampled solutions. This post is about why I believe those scores. The harness lives in one Python module, and its docstring is a contract I wrote before the code: