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AI CURATED HOT STORY · 10/30/2026

Bi Xuan: Vertical Agents' Moat Lies in Business Modeling and Data Loops

1 reports archived1 independent sourcesupdated 10/30/2026, 19:36:13
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Bi Xuan, CEO of Beilianzhuguan, argues that as LLMs improve, long-horizon task execution and generic tool use are no longer the core moats for vertical agents. True long-term competitiveness stems from deep understanding of specific business contexts and the ability to build data pipelines, business models, and self-evolving systems around proprietary data. Using SREAgent as an example, he emphasizes that solving non-standardized 'dirty work' in enterprise IT operations and ensuring systems evolve with business changes are key to avoiding replacement by general-purpose LLMs.

LATEST/Bi Xuan, CEO of Beilianzhuguan, argues that as LLMs improve, long-horizon task execution and generic tool use are no longer the core moats for vertical agents. True long-term competitiveness stems from deep understanding of specific business contexts and the ability to build data pipelines, business models, and self-evolving systems around proprietary data. Using SREAgent as an example, he emphasizes that solving non-standardized 'dirty work' in enterprise IT operations and ensuring systems evolve with business changes are key to avoiding replacement by general-purpose LLMs.

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  1. InfoQ 中文T2·68 pts

    Bi Xuan: Vertical Agents' Moat Lies in Business Modeling and Data Loops

    • Enhanced native capabilities of LLMs are eroding traditional agent barriers based on long-horizon tasks and generic tool use.
    • The core moat for vertical agents lies in processing proprietary data and building self-evolving business models.
    • The SREAgent case demonstrates that solving non-standard data integration and mapping business logic in specific enterprise scenarios is the key challenge for deployment.