Temporal

The OpenAI Agents SDK paired with Temporal gives you a production-ready foundation where LLMs handle reasoning and Temporal handles durability — auto-retries, crash recovery, and state persistence included. Without Temporal, 76% of real-world agent deployments fail. With it, your agent survives Kubernetes restarts, rate limits, and multi-hour workflows. Why 76% of AI Agents Fail in Production (And What the Data Tells Us) An analysis of 847 AI agent deployments in 2026 found that 76% failed in production, with 62% of those failures tied directly to authentication and state management issues — not model quality or prompt design. The math is brutal: an agent with 85% per-step success rate running 8 sequential steps has only a 27% end-to-end success rate. Every additional step compounds the failure probability, and long-running tasks make it worse. Research confirms that after 35 minutes of execution, every agent experiences measurable success rate degradation — and doubling the task duration quadruples the failure rate. Most developers build agents that work in notebooks and break in production because notebooks never handle crashes, partial completions, or mid-run restarts. The root problem is architectural: agents need a runtime that persists state, retries failures, and resumes from where they stopped. Temporal was designed exactly for this, and its March 2026 General Availability integration with the OpenAI Agents SDK makes the combination the production baseline for serious workloads. ...