OpenAI has introduced an exciting new open-source framework called “Swarm” on GitHub. Still in its experimental phase, this tool is designed to make the creation and orchestration of multi-agent systems more accessible, efficient, and controllable. The aim is to help developers build complex systems without facing a steep learning curve.
Swarm is built on two core concepts: routines and handoffs. Routines are composed of instructions and the necessary tools to execute tasks, formulated in natural language for agents to handle effectively. Handoffs, on the other hand, allow one agent to pass control of a conversation or task to another agent, similar to how calls are transferred in a customer service setting. This allows specialized agents to step in for specific tasks, making the system more flexible and adaptable.
OpenAI has already provided several examples of how Swarm can be applied in practice. Demonstrations on GitHub show how a triage agent works alongside a specialized weather agent to handle requests efficiently, or how a customer service agent for an airline intelligently delegates tasks to specific service bots. These examples highlight Swarm’s potential for seamless task delegation and execution.
Swarm also serves as a scalable and highly customizable alternative to the Assistants API. While Assistants offers hosted threads and integrated memory management, Swarm is optimized for developers who want full control and transparency over their AI agents’ context, steps, and tool calls. Swarm allows systems to be tailored specifically to the developers’ needs without the limitations of a hosted solution.
One notable feature of Swarm is that it operates almost entirely on the client side. Similar to the Chat Completions API, it doesn’t store state between calls, making the framework particularly lightweight and giving developers the ability to build flexible, scalable solutions without having to worry about maintaining state.
Although Swarm is not intended for production use and doesn’t receive official support, it’s still a promising tool that offers developers the chance to design and test innovative multi-agent systems. With routines and handoffs as key mechanisms, OpenAI is showcasing what the future of agent-based AI could look like: a network of specialized units working together to tackle complex tasks.
For those interested in working with multi-agent systems, GitHub offers extensive documentation as well as numerous examples to get started. While Swarm is still experimental, there are already many use cases that demonstrate how the framework can be applied to solve real-world problems and build cutting-edge solutions.
