AI chat tools are shifting problem-solving and brainstorming conversations away from colleagues and into private AI interactions, reducing the shared awareness that supports team coordination. We introduce InquiryBits, a system that shares minimal summaries of AI conversations within configurable trust boundaries, separating AI-only analysis from human-visible sharing. In a study with 80 professionals, we find that people are broadly willing to share these traces to support collaboration and avoid duplicating work - but only within bounded groups. Comfort drops sharply as audience expands beyond close teams; the level of detail shared matters less than who can see it, with a preference for more detail over less within trusted groups. These findings suggest that trust boundaries, more than information granularity, may be the most impactful design parameter.

翻译：AI聊天工具正将问题解决和头脑风暴对话从同事间转向私密的AI交互，削弱了支撑团队协调的共享意识。我们提出InquiryBits系统，该系统可在可配置的信任边界内共享AI对话的极简摘要，将仅限AI的分析与人类可见的共享隔离开来。在一项涉及80名专业人士的研究中，我们发现人们普遍愿意共享这些轨迹以支持协作并避免重复工作——但仅限于有界群体内。当受众扩展至亲密团队之外时，舒适度急剧下降；共享细节的详细程度不如谁能看到它更重要，且在受信任群体内人们倾向于更多而非更少细节。这些发现表明，信任边界而非信息粒度可能才是最具影响力的设计参数。