AI Agent Output Quality: Why 90% Confidence Becomes 12% at Step 20

This article examines how AI agent reliability degrades exponentially across multi-step workflows: a 90% accurate agent running 20 steps achieves only 12% end-to-end success due to compounding errors. It argues that preventing bad outputs from becoming bad actions requires real-time governance layers, not just retrospective evaluation.