一个用于编排的开源规范：Symphony

We regularly use Symphony to orchestrate complex features and infrastructure migrations. For example, we might file a task asking the agent to analyze the codebase, Slack, or Notion and produce an implementation plan. Once we’re happy with the plan, the agent generates a tree of tasks, breaking the work into stages and defining dependencies between tasks.

Agents only start working on tasks that aren’t blocked, so execution unfolds naturally and optimally in parallel for this DAG (a sequence of execution steps). For example, we marked the React upgrade as blocked on a migration to Vite. As expected, agents started upgrading React only after the migration to Vite was complete.

Agents can also create work themselves. During implementation or review, they often notice improvements that fall outside the scope of the current task: a performance issue, a refactoring opportunity, or a better architecture. When that happens, they simply file a new issue that we can evaluate and schedule later—many of these follow-up tasks also get picked up by agents. While we oversee this process, agents stay organized and keep work moving forward.

This way of working dramatically reduces the cognitive cost of kicking off ambiguous work. If the agent gets something wrong, that’s still useful information, and the cost to us is near zero. We can very cheaply file tickets for the agent to go prototype and explore, and throw away any explorations we don’t like.

Because the orchestrator runs on devboxes and never sleeps, we can add tasks from anywhere and know an agent will pick it up. For instance, one engineer on our team made three significant changes from the Linear app on his phone from a cozy cabin on shoddy wifi.

An increase in exploration from working this way

When observing the effects of working with Symphony, the most obvious change was output. Among some teams at OpenAI, we saw the number of landed PRs increase by 500% in the first three weeks. Outside of OpenAI, Linear founder Karri Saarinen highlighted a spike in workspaces created⁠ as we released Symphony. However, the deeper shift is how teams think about work.

When our engineers no longer spend time supervising Codex sessions, the economics of code changes completely. The perceived cost of each change drops because we’re no longer investing human effort in driving the implementation itself.

That changed our behavior. It's become trivial to spin up speculative tasks in Symphony. Try an idea, explore a refactor, test a hypothesis, and only keep the results that look promising.

It also broadens who can initiate work. Our product manager and designer can now file feature requests directly into Symphony. They don’t need to check out the repo or manage a Codex session. They describe the feature and get back a review packet that includes a video walkthrough of the feature working inside the real product.

Symphony also shines in large monorepos (like the one we have at OpenAI) where the last mile of landing a PR is slow and fragile. The system watches CI, rebases when needed, resolves conflicts, retries flaky checks, and generally shepherds changes through the pipeline. By the time a ticket reaches Merging, we have high confidence the change will make it into the main branch without human babysitting.