AI Evaluation Is Falling Behind Agent Deployment in High-Stakes Domains
Vincent Chen of Snorkel AI argues that agent evaluation has not kept pace with the systems now being pushed toward real deployment. Drawing on more than 120 applications to Snorkel’s Open Benchmarks Grants, he lays out a framework for benchmarks that are rigorous enough to measure capability and opinionated enough to direct research. In Chen’s account, the next useful benchmarks will need validated tasks, intentional distributions, unsaturated headroom, and evaluation methods that capture realistic constraints, while also betting on richer environments, longer autonomy, and more complex outputs.
AI Engineer·Jun 4, 2026·11 min read
