Choose an OpenAI agent runtime by operating responsibility

Start with the system your team must operate

Describe how work starts, how long it may run, and what must be preserved between steps. Identify the existing application that receives results and the team that will maintain the integration. These requirements are more useful than selecting a runtime because it appears in a current demo.

For a Nashville company using an external implementation partner, ask who owns each operating responsibility after handover. A managed service can reduce some infrastructure work while leaving business permissions, source quality, and acceptance decisions with your organization.

Compare the documented boundaries

OpenAI describes the Agents API as a managed agent runtime, the Agents SDK as an application-controlled agent loop, and Responses API integration as a more direct model interface. The current documentation explains differences in state and tool handling. Verify the specific capability needed for your task.

Our implementation recommendation is to turn those differences into a responsibility table for the project. List who maintains state, executes custom tools, handles interruptions, and investigates failures. The preferred runtime is the one that fits those responsibilities without unnecessary complexity.

Reference: OpenAI: Agent runtime options

Test a real tool and interruption path

Build a small experiment that reads the approved source, prepares the intended result, and handles a missing dependency. Include a stopped or interrupted task and confirm how it resumes or returns to staff. A hello-world response does not test the operating behavior that matters.

Keep model selection separate from runtime suitability. The project may need to revisit a model configuration as evaluations change, while the application’s ownership and integration boundaries remain stable. Avoid tying every business rule to an incidental model behavior.

Document the choice and its limits

Record the required capabilities, the alternatives considered, and the evidence from the experiment. Include the assumptions that would prompt a redesign, such as a new data boundary or a different execution environment. This gives the next maintainer a reasoned decision to inherit.

Agentix can make runtime evaluation part of a custom agent brief. The deliverable should explain how the selected architecture supports the workflow and what your team must still operate. A technology choice is complete when its practical responsibilities are understood.

Reference: Agentix (publisher): Agentix services

Common questions