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Ai-Evals

I went looking for AI-resistant CS1 problems. The search came up empty.

··1244 words·6 mins
For six weeks this summer I hunted for a CS1 programming problem that an AI model could not solve. I found exactly one candidate. It scored 0.00 against the weaker model, the stronger model solved it, and my fairness checks came back clean. Then I reworded the problem statement in plain English, changed nothing about the hidden tests, and the resistance evaporated. Auditing AI-Solvability ยท Part 1 of 1 1 What I was measuring # The tool is called cs1-auditor. It is a Python command-line tool that audits how solvable one CS1 problem is for a named model. You point it at a problem folder holding a plain-English spec, a hidden test suite, and a reference solution. It samples N candidate solutions from the model, runs each one in a sandbox against the hidden tests, and reports two things. The first is an AI-solvability score, which is pass@k for that model on that date. The second is a construct check, which asks whether any resistance comes from a real skill or from a trick in the wording. A problem only earns the label AI-resistant when the score is below a threshold and the construct check is clean.