AI agents are entering their rebuild era as enterprises confront the reliability problem

Enterprises deploying AI agents are rebuilding early systems to improve reliability for long-running workflows.

Temporal Technologies says many production agents fail without durable execution, state tracking, observability, and recovery.

Crashes, retries, and multi-step orchestration can expose reliability gaps and drive up inference costs.

The lesson for enterprises: production agents need strong workflow design, not just good model outputs.