Post by Sama

Production AI models don’t fail all at once. Most degrade gradually — through shifting data, evolving user behavior, changing taxonomies, and edge cases that didn’t exist during training. Our latest guide breaks down what effective model maintenance actually looks like in production: → Monitoring and drift detection → Evaluation workflows and quality control → Data refresh and retraining strategies → Safe release and rollback practices → Human-in-the-loop evaluation for long-term reliability As AI systems become more deeply embedded into business operations, maintaining model performance is becoming an operational discipline. Read the full guide here: https://lnkd.in/gKFdGinT