Most AI Observability Dashboards Miss the Actual Problem
中文摘要
大多数AI监控仪表盘仅关注延迟和状态码，难以识别出那些指标正常但实际存在语义或逻辑错误的隐蔽性AI故障。
English Summary
Most AI observability dashboards focus on technical metrics like latency, failing to detect subtle semantic or logic errors that appear "healthy" on traditional monitoring tools.
Original Excerpt
The hardest AI failures are the ones that look healthy on a dashboard. The request finished, the status code was fine, the latency stayed… Continue reading on Medium »