This episode presents agentic loops as a way to make AI continue working toward a measurable finish line, then shows how multiple loops can be composed into work graphs. The discussion covers task selection, verification, convergence, cost controls, failure modes, human gates, model assignment, and the importance of redesigning work around agent capabilities rather than copying existing human processes.