When AI is the judge, the biggest risk is putting all trust in a single model. Quoting @GenLayer's post because the design choice that stands out to me is the Equivalence Principle. Human experts rarely use the exact same words, yet we can still recognize when they reached the same conclusion. AI consensus should work the same way. GenLayer's approach combines: • Randomly selected validators • Different AI models reasoning independently • Agreement on meaning, not wording • Appeals that expand the validator set • Real stake backing every vote The staking piece is especially important. Consensus is stronger when validators have something to lose for being wrong or dishonest. Trust is not based on reputation alone. It is backed by economic incentives. That feels far more resilient than asking a single AI system to hold the gavel.