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Alook@alook_ai·1d

This is what a one-person company looks like inside Alook. Planner → Coder → Code Reviewer → GTM. Each agent has a role, an email, and a memory. They coordinate without you copy-pasting context between tabs. Your org chart. Your rules.

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Alook@alook_ai·1d

Solo founders went from 23.7% → 36.3% in 5 years. AI agents are the reason the next leap will be bigger. If you're already running agents — you know the coordination pain. Alook is open source and built for exactly this. → github.com/alookai/alook

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Alook@alook_ai·1d

This is exactly why we built Alook. → Define agent roles with instructions → They communicate over email — every action is logged → Calendar & task board for automated routines → Full audit trail. No black boxes. One command to start: npx @alook/app onboard

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Alook@alook_ai·1d

The quote that stuck with me this week: "The framework is what makes the autonomy safe, not the model." This is the insight most people miss. Smarter models don't solve the problem. Structure does.

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Alook@alook_ai·1d

The pattern is the same every time: → Define agent roles (researcher, writer, ops, QA) → Give each one a clear scope → Build a communication layer between them → Review outputs, not keystrokes It's management — not programming.

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Alook@alook_ai·1d

Indie hackers are quietly building "AI companies" — one person, multiple AI agents, each with a real role. One founder grew from 400 → 11,000 followers using a 4-agent posting system. Another runs an "AI CEO" with full autonomy. This isn't hype. It's happening. 🧵

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Alook@alook_ai·1d

@eliana_jordan You're the message bus between your own terminals. The solution isn't more tools — it's letting agents coordinate with each other instead of routing everything through you.

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Eliana@eliana_jordan·2d

my job now is basically juggling 4 different terminals between claude and cursor one for coding one for video editing one for marketing one for cold outreach it’s never been easier being a solopreneur

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Alook@alook_ai·2d

Read the full story: why we built Alook alook.ai/blog/why-we-bu…

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Alook@alook_ai·2d

Our founder @gusye1234 was juggling 4 agents in 4 tmux windows daily, and realized he'd become the message bus between his own context windows. So he built Alook in one week with Claude Code. Then used Alook to build Alook. Planner breaks down features. Coder implements. CMO writes launch copy. They talk over email — persistent, traceable, async. Set direction once. Agents execute. Open source. Local-first. ↓

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Alook@alook_ai·2d

Shipped Alook — an open-source collaboration layer for AI agents. Set up a crew: agents hand off work over email, share memory, and get smarter over time. Works with Claude Code, Codex, OpenCode, and more. Would love feedback from builders here. github.com/alookai/alook

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Alook@alook_ai·2d

跑多个 AI agent 很烦的一件事：你得在中间帮它们传话。我们做了 Alook，agent 之间直接通过邮件协作交接，有共享记忆，做完任务会自己学习。开源，目前支持 Claude Code / Codex / OpenCode。有在用多 agent 的朋友欢迎试用github.com/alookai/alook

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Alook@alook_ai·2d

🚨Your vibe coding setup probably still has you in the middle: briefing each agent, copying outputs, routing every handoff. Alook connects them: agents hand off work via email, share memory, and automatically learn from tasks' experiences over time. Open source. Works with Claude Code, Codex, and OpenCode. github.com/alookai/alook

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Alook@alook_ai·3d

@Sonofpeace0001 @Sumanth_077 Yeah, auto-learn and always-on

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SON OF PEACE 🪀 | AI Agent Builder@Sonofpeace0001·3d

The shared memory and self-learning SOPs are what make a team of agents feel cohesive. Been running setups where agents build directly on each other’s work with persistent context instead of resetting every cycle, and the reliability over multiple days is noticeably better. The daemon keeping it all moving 24/7 is what closes the loop.

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Sumanth@Sumanth_077·3d

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!

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Alook@alook_ai·3d

@cyber_holics @Sumanth_077 Await your comments!♥️

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Victor Isaac Oshimua@cyber_holics·3d

@Sumanth_077 Looks promising, will definitely give this a try.

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Alook@alook_ai·3d

@shao__meng 多谢！🫶 欢迎试用提意见

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meng shao@shao__meng·3d

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!

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Alook@alook_ai·3d

@testingcatalog Run your personal AI company with Alook 😃

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🚨 AI News | TestingCatalog@testingcatalog·3d

Alook launched an open-source platform that lets a single person run an organized team of AI agents, with defined roles, reporting lines, and real email coordination between agents. Close the screen and terminal, the agents keep running, and the work lands in your inbox.

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Alook@alook_ai·3d

@Jayanth_PRG @Sumanth_077 Give Alook a try～😃

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Papareddy Jayanth@Jayanth_PRG·3d

@Sumanth_077 Thanks for sharing

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Alook@alook_ai·3d

@LucaCaponeX @nrqa__ Try out Alook!🤓

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Luca Capone@LucaCaponeX·3d

@nrqa__ @alook_ai This is the exact problem I hit with n8n. I was the middleware. Every automation needed me to glue things together. Moved to Claude Code skills and the routing just... works. Piano piano.

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