Research agents need explicit feedback mechanisms to evolve their understanding of tasks—not just bigger models—to avoid error propagation when working through complex, interdependent information.
VeriTrace is a framework that helps AI research agents maintain accurate mental models by explicitly tracking and correcting their understanding as they work through complex problems. Instead of letting language models implicitly manage their reasoning, it uses three feedback loops to catch errors early and prevent them from cascading through the agent's work.