What makes an AI agent trustworthy enough to act for you?
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Seeing more AI products move beyond chat into execution: browser agents completing transactions, cloud agents opening pull requests, and analysts generating ready-to-share reports.
The demos are increasingly convincing. The harder question is whether these agents remain dependable when the workflow becomes ambiguous, permissions change, or a step fails midway.
When evaluating an agent, what matters most to you: successful completion, visibility into each action, or the ability to review and recover from mistakes?
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for recovery/reliability being able to review and recover from mistakes matters most to me. Completion looks great in a demo, but the real test is what happens when a step fails midway.
I think visibility and recoverability matter more than just successful completion. A human assistant becomes trustworthy not because they never make mistakes, but because you can understand their decisions, catch issues early, and correct course.
For AI agents, I’d want clear logs of what actions were taken, why certain choices were made, and easy ways to approve high-impact steps before they happen. The best agents will probably feel less like autonomous replacements and more like reliable teammates who know when to act and when to ask.