Log Analysis

Log analysis is the practice of systematically examining records of how a model has actually behaved in production — the real conversations users had with it, the inputs it received, and the outputs it produced. Unlike controlled evaluation, logs reflect true usage patterns: the weird phrasings, unexpected topics, and edge cases that no evaluation dataset fully anticipates. Reviewing logs can surface failure modes you didn’t know existed, reveal the most common user requests, or show that a policy is being triggered far more or far less often than intended. For behavior architects, log analysis is a core feedback loop: it connects behavioral design decisions to real-world outcomes, and it’s often where the most actionable improvements originate.