The Invisible Crisis in AI Evaluation

Standard LLM evaluations silently fail whenever models achieve qualitative shifts or emergent capabilities, since they assume only incremental progress. This creates a dangerous blind spot: we cannot reliably detect when systems cross into new capability regimes. As a result, evaluation infrastructure—not training or architecture—is actually the bottleneck limiting the next AI breakthrough.