AI Benchmarks: Climbing the Wrong Hills

What it is

A Contrary Research deep dive (updated October 19, 2026) by Michael Kim and Claire Schultz on how benchmarks shape model training, the problems with error-ridden benchmarks and "benchmaxxing," and the case for expert-built evaluations.

Topics