arXiv cs.AI· Julian Kunkel, Ali Doosthosseini·· 11 小时前AI 评分31
未来软件中的元访问能力：以 LLM 聊天界面与 Chat AI 为例
The Power of Meta Access in the Software of the Future --- Demonstrated on LLM Chat UIs and Chat AI
AI 导读
研究提出"元访问"（meta access）概念，让 LLM 聊天助手获得对界面本身的结构化、带权限的视图，并划分出功能引导、元数据与设置访问、摘要与消息检索、确认式变更、完整编排五级阶梯。
正文 · 原文
Abstract:Chat remains the default surface for many large language model (LLM) tasks, even as agentic tools such as OpenCode excel at coding and automation. Yet the model sees the current dialogue but not the workspace around it. We explore meta access---giving the assistant a structured, permissioned view of the interface itself and propose a ladder of levels: feature tutoring; metadata, settings, and preference access; retrieval over summaries and messages, confirmed mutation, and full orchestration. Meta access can turn a chat client from many screens into one entry point for finding, navigating, organising, and operating it, while raising risks around grounding, privacy, prompt injection, and trust. General-purpose agentic harnesses are runtimes; because they can change their own settings, meta access becomes reflexive and needs a separate control-plane boundary. We ground this in the Meta Chat prototype of the Chat AI client. It builds bounded context from, e.g., summaries, settings, and relevant messages; links references to conversations, topics, and personas; supports confirmed, reversible changes; offers a browsable tutorial library; and recommends personas as user-started conversations. By exposing application state in structured form, meta access can extend screen readers from widget descriptions to semantic workspace operations. Meta access thus turns chat from a window onto one conversation into a control layer for the whole workspace, extending chat toward agentic capability without surrendering user control. As assistants become embedded in IDEs, dashboards, office suites, and operating systems, AI-era interfaces should expose a structured, permissioned model of their state and capabilities, ideally by opening their existing metamodels through a debugger-like interface.
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2611.08428 [cs.AI] |
| (or arXiv:2611.08428v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2611.08428 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Julian Kunkel [view email]
[v1]
Thu, 5 Nov 2026 18:22:24 UTC (1,787 KB)
来源：arXiv cs.AI · arxiv.org