In AI agent infrastructure, telemetry refers to the collection and analysis of performance data from agent runs. This includes metrics like execution time, token usage, cost per task, success rate, error frequency, and output quality scores.
Telemetry is essential for teams running agents in production because it enables optimization. Without visibility into what agents are doing, how much they cost, and where they fail, teams cannot improve agent performance or justify the investment.
Codegen provides built-in telemetry across agent runs, including cost tracking and performance analytics. Most standalone tools like Claude Code and Cursor do not offer comparable telemetry at the organizational level.