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[2507.14447] Routine: A Structural Planning Framework for LLM Agent System in Enterprise

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Type: Web Article Original link: https://arxiv.org/abs/2507.14447 Publication date: 2025-09-04


Summary
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WHAT - Routine is a structural planning framework for Large Language Model (LLM) based agent systems in enterprise environments. It provides a clear structure, explicit instructions, and parameter passing to perform tool calling tasks stably.

WHY - Routine addresses the issue of lack of domain-specific knowledge in common models, improving the stability and accuracy of tool calls in enterprise agent systems.

WHO - The main authors are researchers from academic institutions and tech companies, including Guancheng Zeng, Xueyi Chen, and others.

WHERE - Routine positions itself in the market of AI solutions for business process automation, enhancing the integration and effectiveness of agent systems.

WHEN - Routine is a relatively new framework, presented in July 2024, but already shows promising results in real enterprise scenarios.

BUSINESS IMPACT:

  • Opportunities: Routine can accelerate the adoption of agent systems in enterprises, improving operational efficiency and the accuracy of automated operations.
  • Risks: Competition with other planning frameworks may increase, requiring continuous improvement and differentiation.
  • Integration: Routine can be integrated with the existing enterprise AI stack, improving the stability and accuracy of tool calls.

TECHNICAL SUMMARY:

  • Core technology stack: Uses LLM models and structured planning frameworks. It does not specify programming languages, but it is likely to use Python and Go.
  • Scalability: Routine is designed to be scalable, supporting multi-step tasks and efficient parameter passing.
  • Technical differentiators: The clear structure and explicit instructions improve the stability and accuracy of tool calls, making Routine a robust framework for enterprise environments.

Use Cases
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  • Private AI Stack: Integration into proprietary pipelines
  • Client Solutions: Implementation for client projects
  • Development Acceleration: Reduction in project time-to-market

Resources
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Original Links #


Article recommended and selected by the Human Technology eXcellence team, processed through artificial intelligence (in this case with LLM HTX-EU-Mistral3.1Small) on 2025-09-04 19:35 Original source: https://arxiv.org/abs/2507.14447

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