Glossary
Intuitive Systems Evaluation
Definition
A hybrid practice for evaluating complex AI systems that combines adversarial testing with trained intuition. Intuition is used as a hypothesis generator — Never as proof — And every impression is translated into prompts, controls, model comparisons, and reproducible experiments.
Why it matters
Most safety claims rest on benchmark pass rates that the model has been trained against. Intuitive Systems Evaluation surfaces what benchmarks miss: subtle model-state shifts, coherence breakdowns, hidden constraints, and loss of signal quality — Then translates those impressions into a structure that can actually be tested.
Example
While stress-testing a frontier model, the evaluator notices a rhythm change before any wrong answer appears. That impression is turned into a controlled probe — Repeated across models and contexts — That isolates an evasiveness pattern the model exhibits only under a specific kind of pressure.