scaffolding-openai-agents

Multi-agent systems using OpenAI Agents SDK scaffold orchestrated architectures with Agent and Runner classes, async/await patterns, and tool-calling integrations to coordinate specialist agents and enable handoffs between workflows.

Async patterns in OpenAI agent development use async/await syntax to enable concurrent execution, streaming responses, and non-blocking function tool calls within Agent and Runner classes for scalable multi-agent orchestration.

Yes, OpenAI Agents support function tools and guardrails to constrain agent behavior, validate tool-calling outputs, and ensure robust execution within multi-agent workflows and streaming responses.

Create tutoring agents or specialist handoff workflows by defining Agent classes with specific instructions, integrating function tools for domain tasks, and using Runner patterns to orchestrate multi-agent handoffs and streaming outputs.

Yes, building with OpenAI Agents SDK requires a Python environment, understanding of async/await patterns, and familiarity with Agent and Runner class structures to implement tool-calling and streaming agent workflows.

Streaming responses in multi-agent systems require careful management of async concurrency, guardrail enforcement across tool calls, and state coordination between specialist agents to avoid race conditions or incomplete handoffs.