Build with OpenAI Agents API on Vercel
Vercel pairs OpenAI-managed agent sessions with isolated, persistent Sandboxes, using signed webhooks and queues for reconnection and scaling workers to zero.
The integration runs long-lived, tool-using agents with an **OpenAI-managed loop and session state**, while Vercel hosts the app and attaches each session to an **isolated Sandbox** with persistent files. Signed webhooks and Vercel Queues handle creation and reconnection.
Builders can separate agent orchestration from execution infrastructure: let OpenAI retain the session while Vercel provides code execution, file access, and a workspace that survives follow-up instructions. The worker architecture can scale to zero.
The integration runs long-lived, tool-using agents with an **OpenAI-managed loop and session state**, while Vercel hosts the app and attaches each session to an **isolated Sandbox** with persistent files. Signed webhooks and Vercel Queues handle creation and reconnection. Builders can separate agent orchestration from execution infrastructure: let OpenAI retain the session while Vercel provides code execution, file access, and a workspace that survives follow-up instructions. The worker architecture can scale to zero. The material does not state persistence duration, sandbox limits, retry semantics, pricing, or recovery behavior when either provider is unavailable, so those boundaries need validation before production use.
This confirms the emerging brain-versus-hands architecture with a concrete cross-provider integration: managed orchestration and session state are separated from persistent isolated execution. It reduces application-owned lifecycle machinery, but shifts reliability into the seam between providers, making webhook integrity, retries, persistence limits, recovery, and partial-outage behavior essential validation work.