AI
AI Agent Production Dashboards: What to Monitor After Launch
A production dashboard should answer whether agents are working, becoming expensive, getting slower, or creating risk.
Section
Explore original reporting, analysis, product stories, and practical insights about monitoring for founders, developers, and independent builders.
7 stories
Stories and field notes
AI
A production dashboard should answer whether agents are working, becoming expensive, getting slower, or creating risk.
AI
Agent latency is distributed across model calls, tools, queues, databases, and external APIs.
AI
Not every failed agent run has the same cause.
AI
Successful HTTP requests do not prove that an agent completed the right task.
AI
Agent cost is difficult to control when model calls and external services are not tied to individual workflows.
AI
Alerting every time an agent fails creates noise and teaches teams to ignore monitoring.
AI
When agents use multiple MCP servers, debugging requires a clear trail of discovery and execution.