The updated Agents SDK helps developers build agents that can inspect files, run commands, edit code, and work on long-horizon tasks within controlled sandbox environments.

We’re introducing new capabilities to the Agents SDK⁠(opens in a new window) that give developers standardized infrastructure that is easy to get started with and is built correctly for OpenAI models: a model-native harness that lets agents work across files and tools on a computer, plus native sandbox execution for running that work safely.

For example, developers can give an agent a controlled workspace, explicit instructions, and the tools it needs to inspect evidence:

Developers need more than the best models to build useful agents—they need systems that support how agents inspect files, run commands, write code, and keep working across many steps.

The systems that exist today come with tradeoffs as teams move from prototypes to production. Model-agnostic frameworks are flexible but do not fully utilize frontier models capabilities ; model-provider SDKs can be closer to the model but often lack enough visibility into the harness; and managed agent APIs can simplify deployment but constrain where agents run and how they access sensitive data.

Here’s what some of the customers who tested the new SDK with us had to say:

With today’s release, the Agents SDK harness becomes more capable for agents that work with documents, files, and systems. It now has configurable memory, sandbox-aware orchestration, Codex-like filesystem tools, and standardized integrations with primitives that are becoming common in frontier agent systems.

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