Autonomous AI systems at scale cannot rely on synchronous governance for every decision without collapsing under latency and coordination overhead. The solution is distinguishing fast paths (preauthorized, bound execution that proceeds without per-step approval) from slow paths (reserved for irreversible or high-stakes decisions). Control planes should observe continuously but intervene selectively, using feedback mechanisms like tightening thresholds or narrowing tool access rather than blocking execution. This approach treats governance as a feedback system rather than an approval workflow, allowing autonomy to scale while preserving safety and trust.
Table of contents
The question we can’t avoid anymoreWhy universal mediation fails in practiceAutonomy requires fast pathsWhere slow paths become necessaryObservation is continuous. Intervention is selective.Feedback without blockingThe cost curve of controlWhat changes for architectsGoverning outcomes, not stepsSort: