How to Design AI Agent Handoffs That Preserve Context and Require Human Input

When an AI agent reaches a decision boundary it cannot safely cross alone, the interface must clearly communicate the decision needed, the reasoning behind it, and the consequences of each possible answer. Unlike a simple chat message, a human-input request changes task state, may pause resource consumption, and requires an explicit rule for resuming work. Notifications should carry enough detail for the user to prioritize the request, while sensitive evidence and irreversible actions must remain behind authenticated access. Designers must also account for scenarios involving expired context, closed tabs, time zone gaps, and unauthorized users, ensuring the task can recover gracefully. The agent's paused state, saved progress, teammate permissions, and expiry conditions should all be visible to the user before a timeout occurs, not after the task silently disappears.