Towards Risk-free AI Agent Deployment
LLM-based agents are rapidly moving from research prototypes into the core business processes of organizations, but these agents pose deployment risks to security, compliance, and functionality. In this article, we argue that risk-free deployment must be grounded in the agent's trajectory: the recorded sequence of reasoning steps, tool invocations, and environmental observations. Trajectories are available for any agent, and many failures are visible only in the trajectory. To make agents deployable and sustainable, we advocate agent testing and debugging as a systematic research direction for detecting and mitigating these risks. This article begins with the challenges of testing agents,...
| Authors | Yintong Huo, Rangeet Pan, Abhik Roychoudhury |
|---|---|
| Primary category | cs.SE |
| Published | 17 August 2026 |
| Last updated at source | 17 August 2026 |
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