What is AI observability?
AI observability is the practice of monitoring and understanding what AI systems do in production, tracing inputs, retrieved context, outputs, tool calls, latency, costs and quality, so teams can debug failures, catch regressions and improve performance.
What to track
| Signal | Why |
|---|---|
| Traces | See each step and tool call |
| Quality scores | Accuracy and helpfulness |
| Escalations | Where the agent gives up |
| Latency | User experience |
| Cost | Tokens and credits |
| Feedback | User ratings |
Observability vs evals
Evals test before release; observability monitors live behavior. Both feed each other.
