Durable AI Agent Orchestration with OpenAI + Temporal

This video discusses building durable, production-ready AI agents using OpenAI's SDK and Temporal. It covers defining AI agents with prompts, models, and tools, and emphasizes the orchestration of micro-agents for robustness. The session highlights how Temporal's durable execution framework addresses challenges like flakey networks, rate limiting, and long-running operations in distributed AI systems.

**Durable AI Agent Orchestration with OpenAI and Temporal** is one of those topics that sounds abstract until you’ve actually tried to ship an AI system into the real world. Then it suddenly feels very… personal.

If you’ve ever built an AI agent that worked beautifully in a demo and then quietly fell apart overnight because of a flaky network call or a rate limit, you already understand the problem this video is tackling. And yes, most of us learn that lesson the hard way.

In this session, the speaker walks through how **OpenAI’s Agents SDK** can be combined with **Temporal’s durable execution framework** to build AI agents that don’t just think, but *persist*. Think of it like giving your AI a reliable memory and a calm nervous system. When something breaks, it doesn’t panic or restart from zero. It simply continues.

The core idea is surprisingly human. Instead of one massive AI doing everything, you orchestrate **micro-agents**, each with clear instructions, specific models, and well-defined tools. One agent plans. Another executes. Another checks results. Together, they behave more like a small team than a single genius locked in a room.

Temporal plays a critical role here. It handles the messy realities we usually ignore until production, things like retries, long-running workflows, intermittent failures, and waiting hours or days without losing state. The speaker even notes that **OpenAI itself uses Temporal** internally, which quietly says a lot.

What’s refreshing is that this approach isn’t locked to one SDK. Even if you’re not using OpenAI’s Agents SDK directly, the concept of durable execution still applies. Anywhere AI needs to operate over time, across systems, with real consequences, this model fits.

Watching this, you can almost see where things are heading. AI agents that feel less like scripts and more like dependable coworkers. Systems that can pause, recover, and keep going without constant babysitting.

If you’re building anything serious with AI, or planning to soon, this is worth your time.

You can watch the full session here:
https://youtu.be/k8cnVCMYmNc

And fair warning… once you start thinking in terms of durable agents, it’s hard to go back.

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