verifier-based-training

Proposes a 'Truth Engine' architecture in which an environment synthesizer creates novel closed-loop micro-worlds, a frontier solver explores them without human demonstrations, and deterministic verifiers filter proven artifacts that get distilled into the base model — forming a self-compounding flywheel intended to push AI beyond the boundary of human knowledge.