""Devops should apply the same content and quality processes to AI agents as they do for people by leveraging AI-powered solutions that monitor 100% of interactions from both humans and AI agents.""
""The next step is observing, managing, and monitoring AI and human agents together because performance oversight and continuous improvement are equally critical.""
Organizations are pressured to transition AI agent experiments into production, necessitating DevOps teams to establish observability standards. These standards should encompass monitoring and agenticops practices. Teams need to define minimum observability requirements, integrating DevOps, DataOps, and ModelOps practices. As AI agents take on more complex tasks, centralizing observability data becomes crucial. A key question is tracking actions and decisions made by both AI and human agents. Experts emphasize the importance of defining success criteria and operational governance for effective observability.
Read at InfoWorld
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