The TrustLab Blog

As AI agents become autonomous decision-makers, simple "vibe checks" are no longer enough to ensure reliability. Adjudication provides a structured human + AI partnership to resolve disagreements and create defensible evidence for every action. Move beyond basic metrics to an evidence-based system that builds trust through accountability and continuous calibration.

Drawing on years of content moderation experience, this post distills four core lessons—clear, reliable policies; iterative refinement; separating policy from implementation; and human oversight for edge cases—and shows why they matter just as much for evaluating AI systems and agents using LLM-as-a-judge approaches today.

As AI agents transition from tools to autonomous decision-makers, traditional pre-launch testing is no longer enough. These non-deterministic systems require continuous oversight to manage drift and ensure quality. By turning opaque behaviors into observable signals, organizations can automate with confidence and build lasting trust.