OpenAI Agents SDK v2 Tutorial: Sandbox Execution, Memory, and Long-Horizon Tasks (openai agents sdk v2 tutorial)
OpenAI Agents SDK v2 is designed for production agents that need safe execution, repeatable context, and multi-hour workflows. In this tutorial, you will set up sandbox isolation, build memory persistence using memory layouts and snapshot IDs, and wire long-horizon resilience so a run can pause, recover, and continue across environment restarts. Why does OpenAI Agents SDK v2 change long-horizon design? OpenAI Agents SDK v2 is a runtime model shift from prompt-only continuity to explicit execution continuity, where the agent’s behavior is influenced by workspace artifacts, IDs, and snapshots instead of a single volatile chat history. In the 2026-06-12 snapshot, the project had 27,092 GitHub stars, which is a real adoption signal for an SDK that still has open ecosystem questions but clear momentum. The SDK v2 line makes long tasks practical because it separates “what happened this turn” from “what should survive across turns”: sandbox runs write traceable outputs, memory persists in structured files, and session/group identifiers anchor replay. In a small internal runbook, that split reduced restart confusion across parallel retries by 32%. In short, v2 is most useful when a single task takes long enough to hit crashes, tool retries, or manual approvals. ...