为智能代理设计新型企业API架构，解决动态任务协同难题。
AI Agentic workflows and Enterprise APIs: Adapting API architectures for the age of AI agents
- 提出支持自主智能体的API架构转型框架
- 构建可适应目标驱动行为的交互机制
- 适合企业AI系统集成与架构升级者参考
生成式AI的快速发展催生了自主智能体，对企事业单位计算基础设施带来前所未有的挑战。现有企业API架构主要面向人类驱动、预设交互模式设计，难以支撑智能体的动态、目标导向行为。本文系统分析现有API设计范式、代理交互模型及新兴技术约束，提出一套面向智能体工作流的API架构转型策略。研究结合理论建模、对比分析与探索性设计原则，应对标准化、性能与智能交互等关键挑战，构建下一代企业API的概念模型，使其能无缝融入自主智能体生态，对未来的企事业计算架构具有重要意义。
原文摘要 · Abstract (English)
The rapid advancement of Generative AI has catalyzed the emergence of autonomous AI agents, presenting unprecedented challenges for enterprise computing infrastructures. Current enterprise API architectures are predominantly designed for human-driven, predefined interaction patterns, rendering them ill-equipped to support intelligent agents' dynamic, goal-oriented behaviors. This research systematically examines the architectural adaptations for enterprise APIs to support AI agentic workflows effectively. Through a comprehensive analysis of existing API design paradigms, agent interaction models, and emerging technological constraints, the paper develops a strategic framework for API transformation. The study employs a mixed-method approach, combining theoretical modeling, comparative analysis, and exploratory design principles to address critical challenges in standardization, performance, and intelligent interaction. The proposed research contributes a conceptual model for next-generation enterprise APIs that can seamlessly integrate with autonomous AI agent ecosystems, offering significant implications for future enterprise computing architectures.
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