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NewsMaterial3 min readDisconfirmAI Editorial

openJiuwen Releases RSI-Native AgentOS: Enabling Agents to Add Features to Themselves via Layered Extension Points

openJiuwen has released an RSI-native AgentOS, shifting AI applications from "developer-friendly" to "RSI-friendly." The system provides extension entry points across three layers—Web client, Gateway, and Agent execution. Agents generate extension packages based on user descriptions, which are loaded into the event bus to take effect. This supports hot-swapping, version management, and fault rollback without modifying the application's original code.

2026-11-13 14:54 GMT+8

When using WorkSwarm to handle tasks, can you simply tell the Agent about a new feature you want, letting it build and install it for a test? openJiuwen’s answer is yes, and this mechanism is called RSI-Native AgentOS. It provides a runtime environment for Recursive Self-Improvement (RSI), advancing the extension mechanism from "conveniently allowing developers to integrate new capabilities" to "enabling Agents to proactively improve themselves based on task feedback."

Architecturally, openJiuwen divides the system into three layers: the Web client handles the interface display and receives user operations; the Gateway handles request access and forwarding; and the Agent layer consists of the AgentServer managing sessions and the Harness organizing task execution and tool calls. Each of these three layers retains extension entry points. Following this architecture, extension capabilities are divided into five segments—the Client can add buttons, panels, and settings items; the Gateway can integrate authentication or adjust request routing; the AgentServer can handle sessions, messages, and server-side commands; Swarm can customize multi-Agent collaboration rules; and the Agent can adjust prompts, integrate tools, or sub-Agents.

These modifications are delivered via extension packages. The manifest.json within the package specifies the package ID, version, dependencies, and code entry point; when involving interfaces, it can also declare where components should be displayed, such as in the input area, sidebar, or settings page. During installation, the system reads and verifies the manifest, saving the extension package by its ID and version. During loading, the Gateway and AgentServer respectively select packages running under their own control, determine the versions and order, and register the processing functions from the extension code into their respective event buses. When a user clicks an interface button, the gateway receives a request, or the Agent begins assembling a prompt, the corresponding component emits an event, the event bus finds the matching processing function, and invokes it.

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In practical use, WorkSwarm does not default to a desktop pet form. A user tells the Agent the requirement—'Add a desktop pet to WorkSwarm so I can chat with you by clicking on the desktop'—and the Agent generates an extension package based on the description, then installs it into WorkSwarm as a system plugin. Once enabled, the workbench can be collapsed, leaving only the desktop pet on the screen; double-clicking the pet returns the user to the workbench, preserving the previous conversation. Another example is Token Weather: the user says 'Add a status bar above the input box showing the current session's token usage,' and the Agent writes the code, packages it, and installs it. After trying it out and finding it takes up too much space, the user says 'Make it more compact, but keep the usage percentage.' The Agent modifies it according to the feedback and reloads it. Throughout this cycle, new features are hot-pluggable, requiring no changes to the application's original code upon integration; extension packages are managed by version, and if a new version causes issues, it can be rolled back to a saved checkpoint.

Looking further ahead, openJiuwen believes that as more segments become open to extensions, individual usage habits, team collaboration rules, and enterprise operational requirements can all serve as bases for Agents to adjust themselves. Initially, it has a default appearance; what it becomes later, it can modify itself through actual work tasks piece by piece. openJiuwen summarizes this state as 'What the Agent thinks is what you get.'

Sources

  • qbitai.com量子位↗
  • kx.umi6.com↗
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