这篇论文搞清楚了为什么非工程师造的AI代理容易悄悄坏掉，还给了个轻量级的自动检查框架，适合搞企业级agent落地的人看看。
这篇论文指出，组织内非工程用户通过低代码/无代码平台创建的AI代理，依赖不断变化的模型、工具、检索源、权限、提示、调度和外部服务，导致部署后长期无声退化。作者提出了一个轻量级持续保证框架，包含依赖映射、就绪契约、计划检查、诊断和生命周期治理组件。他们还开发了原型审计器，并通过场景评估展示了该框架如何转化为实用检查和可操作的修复指导。
Toward Continuous Assurance for the Democratization of AI Agent Creation in Industry
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.