From Lab to Life: Guarding Against AI Model Decay in Production

Deploying an AI model is only the beginning, as real-world data often triggers rapid performance degradation that static training metrics fail to capture. To maintain system reliability, developers must implement continuous online monitoring and behavioral testing to detect 'silent failures' before they impact end-users.