Building SRE Error Budgets for AI/ML Workloads: A Practical Framework

Here's a problem I've seen happen far too often: your recommendation system is functioning, spitting out results in milliseconds, and meeting all its infrastructure SLAs. Everything is looking rosy in the dashboard world. Yet engagement has plummeted by 40% because your model has been pointless for several weeks. On behalf of your traditional error budget? You're golden. According to your product team? The system is broken.