Sophia: A Persistent Agent Framework

The podcast explores Sophia, a persistent agent framework incorporating System 3, which adds metacognition, theory of mind, intrinsic motivation, and episodic memory to traditional System 1 and 2 architectures. This framework shifts agents from passive learning to active, self-directed development by using an executive monitor for process-supervised thought search and a structured memory graph. Deployment results show significant reasoning step reductions for recurring tasks and success rate boosts for complex tasks. Key to System 3 is narrative identity and explainable behavior, achieved through creed references, memory episode citations, and reward trade-off explanations, enhancing user trust through transparency.