The article introduces Trivium, a new approach to improving agentic systems by incorporating long-horizon temporal regret as a key objective, alongside outcome and epistemic regret. This framework aims to systematically address the persistence of errors in causal models, potentially enhancing the reliability of AI systems in decision-making processes.