Errors spread fastest in the shadows. When no one's watching, distortions compound silently—until the damage is already done.

That's why human oversight in AI training matters so much. It's not about slowing things down; it's about catching problems early, before they metastasize. A human-guided feedback loop keeps models grounded, ensures they actually align with what users need in the real world, not some abstract ideal.

The difference? Models that stay dependable. Systems you can trust, because someone was paying attention all along.