scaffolding-openai-agents

To scaffold multi-agent workflows with the OpenAI Agents SDK, define individual agents and use the Runner to orchestrate tool calls and handoffs. This enables coordinated, modular execution across specialized agents for complex tasks.

Async execution with the OpenAI SDK relies on native Python async/await patterns managed by asynchronous Runners. This allows concurrent agent tasks and streaming outputs, ensuring observable and efficient interactions during orchestration.

Yes, you can build tutoring assistants and debugging bots using the OpenAI Agents SDK. It provides structured patterns for tool integration and multi-agent handoffs, enabling coordinated specialists for information retrieval and code explanation.

Yes, you need the openai-agents library and a Python runtime to implement guardrails and streaming outputs. These features ensure safe, observable interactions by validating outputs and streaming data progressively during execution.

The best way to orchestrate coordinated tool calls across multiple AI agents is using the Runner component in the OpenAI Agents SDK. It structures multi-agent handoffs and tool execution, ensuring reliable and modular workflows for complex scenarios.

Async runners are used for building production AI agents to handle concurrent operations without blocking. Native async/await patterns enable efficient streaming outputs and multi-agent orchestration, which synchronous execution cannot support effectively.