AI 中文总结
针对工业中人工智能代理创建民主化带来的可靠性挑战，提出轻量级持续保障框架，结合依赖映射等多种方法评估代理运行状态，还展示了原型审核器及评估，为公民创建的组织代理提供保障。
AI 中文摘要
人工智能代理越来越多地由非工程用户通过低代码、无代码和对话式开发环境在组织内部创建。这种民主化促进了快速的本地创新，但也产生了可靠性差距：对用户来说看似简单生产力工具的代理可能依赖于不断变化的模型、工具、检索源、权限、提示、计划和外部服务。这些依赖关系可能在部署后很长时间导致无声退化，即使没有用户直接修改代理。本文识别了人工智能代理创建民主化带来的可靠性挑战，并为公民创建的组织代理提出了一个轻量级的持续保障框架。该框架结合了依赖映射、就绪合同、定期检查、诊断和生命周期治理，以评估代理在预期条件下是否仍可运行。我们还展示了一个初始原型审核器和基于场景的评估，展示了所提出的分类法如何转化为实际检查和可操作的补救指导。
英文摘要
AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments. This democratization enables rapid local innovation, but it also creates a reliability gap: agents that appear to users as simple productivity artifacts may depend on changing models, tools, retrieval sources, permissions, prompts, schedules, and external services. These dependencies can cause silent degradation long after deployment, even when no user directly modifies the agent. This paper identifies the reliability challenge created by democratized AI agent creation and proposes a lightweight continuous-assurance framework for citizen-created organizational agents. The framework combines dependency mapping, readiness contracts, scheduled checks, diagnostics, and lifecycle governance to assess whether an agent remains operationally ready under expected conditions. We also present an initial prototype auditor and scenario-based assessment showing how the proposed taxonomy can be translated into practical checks and actionable remediation guidance.
