Alook 开源:用邮件编排 Claude Code 等 AI Agent 团队

AI Agent 协作编排层:Alook @alook_ai Alook 把 Claude Code、Codex、OpenCode 等本地 CLI agent 组织成一支「可管理的 AI 团队」—...

精选理由

Alook 解决了多 agent 协作中上下文碎片化和手动路由的痛点,做复杂自动化或管理多个 AI 编程助手的团队可以直接部署试试。

AI 摘要

Alook 是一个开源协作平台,将 Claude Code、Codex、OpenCode 等本地 CLI agent 组织成可管理的 AI 团队。它通过为每个 agent 分配角色、邮箱、任务板和日历,实现异步、持久化的上下文管理。核心创新在于以「角色」而非「项目」组织工作,agent 之间通过邮件协调,用户只需像 CEO 一样分配任务。系统采用本地执行 + 云端协作架构,支持 24/7 运行的守护进程,并具备共享记忆和自我学习 SOP 的能力。该项目完全开源,适合需要多 agent 协作的开发者团队。

原文 · shao__meng

AI Agent 协作编排层:Alook @alook_ai Alook 把 Claude Code、Codex、OpenCode 等本地 CLI agent 组织成一支「可管理的 AI 团队」—...

AI Agent 协作编排层:Alook @alook_ai Alook 把 Claude Code、Codex、OpenCode 等本地 CLI agent 组织成一支「可管理的 AI 团队」——有角色、邮箱、任务板、日历和可追溯的执行记录 。 开源地址: github.com/alookai/alook 核心命题:换一条组织轴 Alook 的出发点很清晰:现有工具按「项目」组织,工作却按「人/角色」组织。 一个项目往往需要规划、开发、审查、运营等多个角色,但工具只给单个 agent + 多个 context window。用户被迫在 tab、tmux、会话之间搬运上下文,自己当消息总线。 传统模式 · 1 项目 → 1 agent → 多 session · 上下文在 session 内 · 用户是 router Alook 模式 · 1 人 → 多 agent → 各持角色 · 上下文跨天、跨任务持久化 · 用户是 CEO,agent 是员工 Email 被当作异步、持久、可线程化的上下文层——人机、机机通信都走邮件,底层共享记忆不断累积,而不是每次从零开始。 架构:本地执行 + 云端协作 · 本地优先:代码、工具、文件系统都在本机,agent 有完整 repo 访问权。 · 云端协作:Dashboard、任务调度、邮件路由、多设备可达、团队共享。 记忆系统:三层叠加 · 指令层:AGENTS.md( symlink 到 CLAUDE.md),角色定义、同事列表、CLI 工具手册 · 记忆层:memory.md + experiences/*.md,短记忆索引 + 长经验文档 · 时间线:.context_timeline/YYYY-MM-DD.jsonl,全任务历史:prompt、响应、session_id、status Sumanth @Sumanth_077 Run your personal AI company with a team of AI agents! Alook is an open-source collaboration platform for AI coding agents. Self-hosted and local-first. The setup: Define an org structure. Give each agent a role - dev, ops, research, whatever you need. Set reporting lines. Alook gives each agent an email address. How it works: Assign a task to the right agent. They take it from there. Agents coordinate through email - passing deliverables, asking questions, updating status. You see everything in your inbox but you're not routing anything manually. Runs as an always-on daemon. Close your laptop, agents keep working. Come back to finished tasks. Shared memory across all agents. Every agent knows what every other agent worked on. You never re-explain context. After each task completes, Alook logs what worked and builds SOPs. The whole team gets sharper over time. Works with Claude Code, Codex, and OpenCode. Mix and match or run multiple agents from one runtime. Built-in Kanban for task tracking. Calendar for scheduling. Email for all communication. Agents pick up tasks autonomously, update their own calendars, close issues when done. Chat or email with agents like any AI tool. Install the runtime once, runs in the background. No terminal needed after setup. Key capabilities: • Email-based agent coordination with real inboxes • Org structure with roles and reporting lines • Shared memory and self-learning SOPs • Always-on daemon for 24/7 operation • Works with Claude Code, Codex, OpenCode • Built-in Kanban, calendar, and email • Self-hosted and local-first 100% open source. I've shared the Github Repo in the replies! 🔗 View Quoted Tweet 💬 1 🔄 0 ❤️ 4 👀 326 📊 2 ⚡

Alook 开源:用邮件编排 Claude Code 等 AI Agent 团队 · AI 热点