How to add “workplace agents (agents that handle tasks for you)” to ChatGPT

Why Read This from an HCI Perspective

This article clearly shows that AI agents are not just a feature, but an interaction in which users hand off work, review it again, and step in when needed. For HCI and UX practitioners, it prompts a key question: it’s less about whether the model is smart, and more about when users can trust it—and when they can stop or intervene. In particular, for agents that carry out tasks on a user’s behalf, transparency, control, and failure handling are core design challenges.

CIT's Commentary

AI agents that operate in a workspace are convenient, but they can also easily become “invisible automation.” If users can’t tell what they’re doing right now, how far the process has gone, or why it stopped, trust breaks down quickly. That’s why, beyond improving performance, these systems need interfaces that make state visible. For example, if you clearly show progress stages, uncertainty, and paths to roll back, users can use agents more actively. Also, because such products are likely to be more sensitive in contexts where quick verification and immediate fixes matter—like Korea’s collaborative work environment—research is needed to adapt elements such as intervention buttons, approval flows, and notification density to local working styles rather than simply transplanting global patterns.

Questions to Consider While Reading

• Q.What visual representation would be most effective for helping users understand an agent’s current status and its next action at a glance?
• Q.How should we distinguish between tasks that proceed automatically and moments when user approval or intervention is required?
• Q.In Korea’s collaboration culture, which failure modes are most critical, and what interface patterns can reduce them?