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I've encountered problems with my AI agents in production, where they sometimes behave unpredictably. How can I effectively monitor and manage their behavior to quickly identify deviations and maintain stability? I'm particularly interested in approaches to deeply analyzing their performance.
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AI unpredictability is always a challenge, so I understand your concerns. For monitoring, I would recommend focusing on metrics that directly reflect agent health and setting up alerts for anomalies.
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Try implementing the llm observability concept. This will allow you to track every step of an agent in production and quickly identify anomalies. For in-depth analysis, I recommend looking at the platform It automates problem detection without manually combing through logs. The best price/quality ratio is currently offered by ready-made solutions with alerts for deviations, rather than custom-built systems.