[KongchangAI]
ModelDeepSeek SuperAgent

SuperAgent

An open-source agent research prototype from the DeepSeek Harness team that adopts a Router-Worker architecture separating scheduling from execution. It decouples message triggering, task acceptance decisions, work items, and execution, and is oriented toward long-running workflow management.

Timeline (last 90 days)

Nov 1

The DeepSeek Harness team has published a SuperAgent design article and GitHub repository, released under the MIT license and explicitly labeled as a research prototype.

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Nov 1

SuperAgent adopts a Router-Worker architecture that separates message triggering, task-acceptance decisions, long-term work items and actual execution: the Router decides whether to accept a task and whom to assign it to, and the Worker completes the task in an independent session and directory and writes back the result.

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Nov 1

The official deployment documentation states that Workers execute with operating-system user permissions, recommends isolating them in a dedicated account, and warns that the prototype must not be connected directly to a company's production repository.

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Nov 1

In simulated tests, SuperAgent's median task completion time was 12.4 minutes and its 95th percentile was 15.7 minutes; under a neutral prompt, the 95th percentile for a single session plus a SubAgent was 29.5 minutes.

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Nov 1

In the above benchmark tests, coding work used a stand-in tool that only consumes time, so the tests measure scheduling, concurrency and interruption management, not the actual speed, quality or success rate of the model in completing code.

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Nov 1

The control Agent under the neutral prompt never proactively delegated subtasks in any of the 5 tests.

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All Facts (6)

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