The Productive Half-Life of AI Agents
Every executive asks the same question in different words: how long can we let the agent run before someone has to look over its shoulder? Call that interval the productive half-life—the span of time where an AI agent remains helpful, safe, and aligned without human intervention. There is real research to stand on here: METR’s time-horizon studies measure how long agents can pursue a task at 50% reliability and how that varies by domain; OSWorld, RealWebAssist, TOOLATHLON, and SWE-bench Verified all probe long, messy task chains rather than single steps. Human–automation trust work (Lee & See; CHI 2019 Guidelines for Human–AI Interaction) and decades of mixed-initiative research (Horvitz; Hearst; Bradshaw) show when people should re-enter the loop. The longer the half-life, the more the team can focus on higher-order choices instead of mechanical supervision—and the clearer the protocol for when to step back in.
