Blind Spots in AI: Why Your Traditional Monitoring Falls Short

Traditional monitoring measures what's easy—HTTP codes and uptime—but misses what actually matters for AI systems: response correctness, cost efficiency, and quality degradation over time. A 200 status code tells you nothing about whether your AI is generating nonsense. Organizations still operating AI in production without specialized observability will face mounting costs and user dissatisfaction, making AI-specific monitoring a competitive necessity rather than a luxury.