Unverified50% confidenceFactExact time
Super Agent identifies environmental information that needs handling through two layers of filtering—programmatic filtering (machine learning or code rules) and model judgment—to support proactive execution capability.
1
Sources
50%
Confidence
Long-term
Relevance
11/1/2026
First Seen
Sources
Deepseek Open-Sources Super Agent Architecture: Letting Agents Manage Agents
bilibili林卡比V2-511/1/2026
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UnverifiedSuper Agent adopts a low-interruption design orientation, disturbing people little during normal work and sending messages back only when results are available for review or when a human decision is needed, and it targets teams with review processes rather than individual users seeking full automation.71% similarUnverifiedWhen building LLM-based Agent applications, first validating core feasibility through a spike, then comparing approaches through experiments, and finally using visualization to aid decisions can significantly reduce development risk; handing the building phase to an Agent can improve efficiency.70% similarUnverifiedThe system features a dual-review mechanism: before user review, the Agent first conducts a self-review based on built-in rules, capable of detecting issues such as cropped faces and proactively correcting them.70% similarVerifiedThe observability of Agent systems requires handling information at the semantic level—not only knowing which APIs were called and the latency, but also understanding the reasons behind Agent decisions and the quality of reasoning—therefore evaluation engines must be deeply coupled with tracing systems.69% similarVerifiedAn Agent's tool-invocation decisions rely entirely on the large model's semantic understanding and logical reasoning capabilities, and are not hardcoded by programmers using if-else logic.68% similar
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