I'm finding the best way to use @bot, for me, is as an administrative layer. It surfaces issues for me across my client base, and then it creates a @linear "task" when it warrants real work. I've now set up a "project" (really a "client manager) inside of @cursor_ai, and the projects each "subscribe" to changes in Linear, and they "wake up" when my grok bot and I agree that a Linear issue should be created. As soon as something…
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@MatthewBerman @bot @SpaceXAI My Grok Bot: AI CTO. It watches my GitHub repos, server health, logs and agent activity. When something breaks, it investigates across the stack, correlates what changed, proposes the most likely root cause and gives me the exact next action
Grok Bot 工程实践指南：如何让 AI Bot 团队管理 200 个 Coding Agent 来自 SpaceXAI 团队 @lingxi 分享的三层 Agent 组织，用于替代人工管理大规模 Coding Agents，人类只在顶端处理高风险审查和优先级判断。 https://t.co/2H8U5zdzCk 三层 Agent 组织 1. 执行层：Cursor Cloud Agents - 短生命周期，按需启动，携带个性化技能执行具体任务 2. 管理层：5 个常驻工程师 bot - 各管一块领地：Baltata（iOS/移动共享层）、Shaoruru（桌面端/CI-CD）、Hogan（基础设施）、Craig（Android）、Quill（harness），各有独立记忆，只在单一领域表现最佳 3. 运营层：Jenny - 唯一不写代码的 bot：每天 5 点与各 bot 开 1:1 过 playbook；错误做根因分析、更新制度并广播；负责新 bot 入职…