Simple auditor agents can now intelligently craft prompts to find rare behavioral differences between two AI models. Google DeepMind's interpretability team shifted from static prompt distributions to an active search approach. This method identifies edge-case discrepancies that traditional benchmarks miss. It provides a more reliable way to audit model drift.