scaffolding-openai-agents

Build production-ready AI agents using the OpenAI Agents SDK by defining agent classes, configuring runners, and applying async/await patterns for asynchronous orchestration. This approach reduces boilerplate and enables scalable, modular AI assistants.

Multi-agent orchestration coordinates multiple AI agents to handle complex tasks. Handoffs allow one agent to transfer control to another, enabling modular workflows where agents act as tools for each other within a shared context.

Implement guardrails to validate agent inputs and outputs, ensuring robust interactions. Use streaming responses to deliver outputs continuously, paired with function tools to let agents execute specific operations asynchronously during conversations.

Yes, the OpenAI Agents SDK supports async/await patterns for scalable workflows. Asynchronous orchestration allows concurrent task execution, making it suitable for developers building production-ready tutoring, debugging, and automation agents.

Yes, Python tooling is required to scaffold these AI agents. The project structure relies on Python to define agents, configure runners, and manage modular components for multi-agent orchestration and streaming responses.

Structure a modular project by defining separate agent classes, sharing context across components, and using runner patterns for execution. This organization supports complex workflows where agents hand off tasks and operate as tools.