⚠️ Disclaimer: All information in this article comes from publicly available online materials and is for learning and reference purposes only. Please use the technical solutions mentioned in the article with caution after fully understanding the security risks.

🦞 Building a Virtual AI Team with OpenClaw

Deep Dive into the Practical Playbook of an "Unmanned Company"

5W2H Framework Full Breakdown · Implementation Checklist · Replicable SOP

📌 TL;DR Too Long; Didn't Read Version

1 Core Discovery: Someone used OpenClaw (formerly Clawdbot) to build a virtual team of 10 AI agents to take over company operations.

2 Key Technologies: Heartbeat mechanism (wake up every 15 minutes) + Docker isolation + Mission Control collaboration platform

3 Cost Control: API costs approximately $50-80/day, which can be reduced by 90% through heartbeat + caching optimization.

4 Actual Output: Continuous output of competitor comparison pages, email sequences, social content, blog articles, etc.

5 Security Warning: High permissions + viral growth = significant security risks, requiring careful configuration.

Unmanned companies are becoming a reality.

Recently, the founder of AI customer service company SiteGPT shared his experience on social media of building an AI agent team using Clawdbot (now renamed OpenClaw). This system, called "Mission Control," includes 10 AI agents with different roles that can work together like a real team.

✦ ✦ ✦

One What: What is this thing anyway?

🦞 What is OpenClaw?

OpenClaw (formerly Clawdbot, later renamed Moltbot) is an open-source AI personal assistant framework developed by PSPDFKit founder Peter Steinberger.

"OpenClaw is a personal AI assistant you run on your own devices."

"OpenClaw is a personal AI assistant you run on your own devices."

It's not just a regular chatbot, but an Autonomous Agent - capable of executing shell commands, managing files, automating browser operations, sending messages, and even proactively waking itself up to check tasks.

🔥 Viral Growth Data

✦ Gained 60,000+ Stars on GitHub within 72 hours

✦ Currently has over 180,000+ Stars

✦ Became one of the fastest-growing repositories in GitHub history

✦ Covered by mainstream media such as Wired, CNET, Axios, and Forbes

🎯 Mission Control System Architecture

This developer built the "Mission Control" collaboration platform on top of OpenClaw. The core insight is:

"Each agent is just a separate session of OpenClaw."

"Each agent is just a separate session of OpenClaw."

Each session has its own:

✦ Unique Personality

✦ Memory Files

✦ Cron Schedule

✦ Tool Access

✦ ✦ ✦

Two Who: Who are these 10 agents?

The system includes 10 distinctive AI agents, all named after Marvel characters (here comes the meme!):

🤖 Jarvis · Team Leader

Coordinator and main interface, similar to Iron Man's AI butler, responsible for task assignment and team coordination

👩‍🔬 Shuri · Product Analyst

Skilled at discovering edge cases and user experience issues, as smart as Black Panther's sister

🕵️ Fury · Customer Researcher

Deeply researches competitors, insightful like the director of S.H.I.E.L.D.

👁️ Vision · SEO Analyst**✍️ Loki · 内容撰写者**

对文字有严格标准，像恶作剧之神一样狡黠而精准

📋 其他团队成员

Quill · 社交媒体经理 · 擅长制作吸引人的内容

Wanda · 设计师 · 负责视觉内容创作（集成 DALL-E/Midjourney）

Pepper · 邮件营销专家 · 处理生命周期邮件

Friday · 开发者 · 负责代码相关任务（拥有 GitHub API 权限）

Wong · 文档管理员 · 确保信息不丢失

✦ ✦ ✦

三 Why：为什么要这么做？

😤 单一 AI 助手的局限性

这位开发者经营着一家 AI 客服公司，日常大量使用 AI 工具。但他发现现有 AI 工具存在一个共同问题：

❌ 核心痛点：缺乏连续性

每次对话都是全新的开始，昨天的上下文、上周的研究成果，都会消失在难以找回的聊天记录中。

他想要的是：

1能够记住工作内容的智能体

2多个具有不同技能的智能体协同工作

3共享的工作空间

4分配任务和跟踪进度的能力

💡 OpenClaw 的独特之处

"OpenClaw can initiate interaction. Traditional agents wait for prompts. OpenClaw is proactive."

「OpenClaw 能主动发起交互。传统代理等待提示词，OpenClaw 是主动的。」

关键差异：

✦ 传统 AI：被动响应（Reactive）—— 你问它答

✦ OpenClaw：主动出击（Proactive）—— 它会自己醒来检查任务

✦ ✦ ✦

四 How：技术架构与实现方式

🏗️ 技术栈概览

运行环境：Docker 容器 · 每个智能体独立隔离

配置方式：JSON 配置文件 · 定义角色特征和权限

通信协议：REST API + WebSocket · 实时数据同步

消息队列：Redis · 处理智能体间异步任务分发

数据库：Convex 实时数据库 · 多智能体数据一致性

AI 模型：Claude / GPT-4 · 通过 API Key 接入

💓 心跳系统（Heartbeat）—— 核心机制

为避免持续运行带来的高额 API 费用，系统采用了「心跳」机制：

✅ 心跳机制工作原理

1每个智能体通过定时任务每 15 分钟唤醒一次

2唤醒时间错开安排，避免同时运行

3先进行轻量级状态检查

4只有检测到新任务才启动完整 AI 推理

Heartbeat checklist

• Scan inbox for urgent emails
• Check calendar for events in next 2h
• Review any pending tasks
• Light check-in if quiet for 8+ hours

🎛️ Mission Control 协同平台

为使独立智能体能够团队协作，开发者构建了 Mission Control 平台，相当于智能体团队的「共享办公室」：

📋 Mission Control 核心功能

✦ 共享任务看板 · 所有智能体可见的任务列表

✦ 评论线程 · 智能体间的讨论和协作

✦ 活动动态流 · 实时追踪团队动态✦ Notification System · Slack/Discord Webhook Push

✦ Vector Database · Semantic Search and Context Retrieval

🔄 Example of Actual Workflow

Taking creating a competitor comparison page as an example:

Step 1 After the task is created, it is assigned to Vision and Loki

Step 2 Vision provides keyword research data

Step 3 Fury supplements competitor intelligence

Step 4 Shuri tests user experience differences

Step 5 Loki is responsible for drafting content

✅ Key Advantages: All communication is centralized under a single task, and the complete history is preserved.

✦ ✦ ✦

Five How Much: Cost and Expense Analysis

💰 API Cost Estimation

⚠️ Important Reminder: OpenClaw itself is free and open source, but you need to pay for LLM Tokens.

After using the heartbeat mechanism to control, the API cost is approximately $50-80/day

💵 Claude API 2026 Pricing Reference

Opus 4.5**$5/$25** · Input/Output per million Tokens

Sonnet 4.5**$3/$15** · King of Cost-Effectiveness (Recommended)

Haiku 4.5**$1/$5** · First Choice for Lightweight Tasks

📉 Cost Optimization Strategies

✅ Can Save Up to 90% of Costs

1Prompt Caching: Only 10% of the original price after caching

2Batch API: Enjoy a 50% discount for asynchronous batch processing

3Model Layering: Use Haiku for simple tasks and Sonnet for complex tasks

4Heartbeat Mechanism: Avoid continuous operation generating invalid costs

🖥️ Server Costs

Recommended deployment method (calculated monthly):

DigitalOcean Droplet · $12-24/month · Official Recommended 1-Click Deployment

Vultr VPS · $10-20/month · Docker Compose Deployment

Local Mac Mini · One-time investment · Suitable for heavy users

✦ ✦ ✦

Six Where & When: Deployment Location and Timeline

🌍 Supported Messaging Channels

OpenClaw supports over 10+ mainstream messaging platforms:

✦ Instant Messaging: WhatsApp · Telegram · Signal · iMessage

✦ Work Collaboration: Slack · Discord · Microsoft Teams · Google Chat

✦ Extended Channels: Matrix · BlueBubbles · Zalo · WebChat

📅 Project Timeline

End of 2025 Peter Steinberger releases Clawdbot

Within 72 Hours GitHub gains 60,000+ Stars

Two Months Later Renamed Moltbot due to Anthropic trademark request

Early 2026 Finally renamed OpenClaw, Stars exceed 100,000+

✦ ✦ ✦

⚠ Security Risk Warning (Must Read)

❌ Core Risks

OpenClaw requires high-privilege operation (executing shell commands, accessing files, storing credentials). Once breached, attackers can obtain all accessible resources.

"High privilege + viral adoption + identity confusion = highly attractive target."

「High privilege + viral adoption + identity confusion = highly attractive target.」

The main risks pointed out by security researchers:

✦ Prompt Injection Attacks: Malicious instructions may be executed✦ 凭证泄露：API Keys 存储在本地配置文件

✦ 供应链风险：第三方 Skill 模块可能包含恶意代码

✦ 暴露的管理界面：不当配置可能被远程访问

✅ 安全建议

1在隔离的沙盒环境中运行

2避免连接生产系统或敏感凭证

3使用 Docker 容器隔离每个智能体

4定期轮换 API Keys

5审核所有第三方 Skill 模块

✦ ✦ ✦

📋 落地 Cheatsheet · 可直接复制执行

Phase 1：环境准备（1-2 天）

☐ 准备云服务器（推荐 DigitalOcean / Vultr）

☐ 安装 Docker 和 Docker Compose

☐ 获取 Claude / OpenAI API Key

☐ 配置域名 A 记录（可选）

Phase 2：OpenClaw 部署（半天）

克隆仓库

git clone https://github.com/openclaw/openclaw.git cd openclaw

运行安装向导

npm install -g openclaw@latest openclaw onboard --install-daemon

Phase 3：智能体配置（1-2 天）

☐ 为每个智能体创建 JSON 配置文件

☐ 定义角色 Prompt 和工具权限

☐ 配置心跳间隔（建议 13-17 分钟随机）

☐ 设置 Docker 容器隔离

☐ 连接消息渠道（Slack/Discord/Telegram）

Phase 4：Mission Control 搭建（2-3 天）

☐ 部署 Convex 实时数据库

☐ 搭建 Next.js 前端界面

☐ 配置任务看板和评论系统

☐ 集成 Webhook 通知

☐ 设置向量数据库用于语义搜索

Phase 5：测试与优化（持续）

☐ 从 2-3 个智能体开始，逐步扩展

☐ 监控 API 费用，调整心跳频率

☐ 启用 Prompt Caching 降低成本

☐ 记录每个智能体的产出质量

☐ 迭代优化角色 Prompt

✦ ✦ ✦

✓ 执行 SOP · Checklist

🔹 部署前检查

☐ 确认服务器配置 ≥ 2GB RAM

☐ 确认 Node.js ≥ 22 版本

☐ 确认防火墙规则已配置

☐ 确认 API Key 已安全存储（非明文）

☐ 确认备份方案已就绪

🔹 智能体配置检查

☐ 每个智能体有明确的角色定义

☐ 权限范围遵循最小化原则

☐ 心跳时间已错开配置

☐ 工具访问权限已分配

☐ 内存文件路径已配置

🔹 安全检查

☐ Docker 隔离已启用

☐ 非 root 用户运行

☐ DM 配对已配置（防止未授权访问）

☐ 管理界面不暴露公网

☐ 第三方 Skill 已审核

🔹 运行后检查

☐ 心跳正常触发

☐ 任务可正常分配和完成

☐ API 费用在预期范围内

☐ 日志无异常错误

☐ 智能体间协作正常

✦ ✦ ✦

∞ 写在最后

透过这个案例，进一步清晰了未来企业的模式。

"The value is not in any single deliverable, but in the compound effect of continuous accumulation and the elimination of management friction."

「价值不在于任何单一交付物，而是持续积累的复合效应和管理磨损的消除。」

当你在处理其他工作或者休息时，你的智能体团队却正在按照你的指示推动任务——不知疲倦，不打折扣地持续前进。Developer Suggestions:

✦ Start with 2-3 agents and gradually expand

✦ Treat AI agents as team members and assign clear roles

✦ Provide memory capabilities and allow collaboration

✦ Maintain accountability