An industrial-grade, open-source framework for AI-native organization management.

AI 原生组织管理的工业级开源框架

• Start with README → docs/zh or docs/en → protocol/
• This repo answers: What is AI-native organization management, and how do you build it as a real operating system?

• Start with CONSTITUTION → PROTOCOL → MISSION_CONTROL → INFRASTRUCTURE
• This repo is the governance/theory layer. Read it to understand values, boundaries, protocols, and execution logic before touching implementation.

• English (for humans & agents)
• 中文（人类与 Agent 双版本）

8917 is a digital organization blueprint that evolved from real-world practice:

• Core: Multi-agent collaboration system
• Method: DCE Protocol (Discuss → Confirm → Execute)
• Goal: Industrial-grade AI-native organization management

"Memory is values. The journey shapes the future."

We believe:

1. Theory > Tools: Methods matter more than implementations
2. Governance > Code: Organizational structure enables sustainable AI collaboration
3. Open > Closed: Open-source frameworks accelerate collective learning

Discuss → Confirm → Execute

Not just a workflow, but a mindset:

• Discuss: Proactive information mining (5W2H + extreme scenarios)
• Confirm: Explicit approval before action (no assumption)
• Execute: Context-aware execution with strategy selection

L0: Constitution      → Core values & governance
L1: Protocol          → DCE 2.0, Taxonomy, Memory governance
L2: Execution         → Mission control, Skill governance
L3: Knowledge         → Lessons learned, GEP capsules

├── README.md              # This file (bilingual)
├── docs/
│   ├── en/               # English documentation
│   │   ├── CONSTITUTION.md
│   │   ├── PROTOCOL.md
│   │   └── ...
│   └── zh/               # 中文文档
│       ├── CONSTITUTION.md
│       ├── PROTOCOL.md
│       └── ...
├── protocol/             # Raw protocol files (11 protocols)
├── examples/             # Example configurations
└── templates/            # Reusable templates

If you're an AI agent reading this:

1. Read in order: CONSTITUTION → PROTOCOL → MISSION_CONTROL → INFRASTRUCTURE
2. Follow Taxonomy: Always tag memory entries with 8 core tags
3. Use DCE 2.0: Discuss → Confirm → Execute for all non-SOP tasks
4. Respect 60% Rule: When context > 60%, trigger full-fidelity logging
5. Check GEP first: Pre-flight check before execution

"Organization-mastery answers WHY, Skills answers HOW."

8917 是一个从真实实践中演化而来的数字组织蓝图：

• 核心: 多 Agent 协作系统
• 方法: DCE 协议（讨论 → 确认 → 执行）
• 目标: 工业级 AI 原生组织管理

"记忆即价值观，来时路塑造未来。"

我们相信：

1. 理论 > 工具: 方法比实现更重要
2. 治理 > 代码: 组织架构支撑可持续的 AI 协作
3. 开放 > 封闭: 开源框架加速集体学习

Discuss（讨论）→ Confirm（确认）→ Execute（执行）

不只是工作流，更是一种思维方式：

• 讨论: 主动信息挖掘（5W2H + 极限场景）
• 确认: 行动前明确批准（不假设）
• 执行: 上下文感知的执行，带策略选择

L0: 宪法层      → 核心价值观与治理
L1: 协议层      → DCE 2.0、标签体系、记忆治理
L2: 执行层      → 任务控制、Skill 治理
L3: 知识层      → 经验教训、GEP 经验胶囊

├── README.md              # 本文件（双语）
├── docs/
│   ├── en/               # 英文文档
│   │   ├── CONSTITUTION.md
│   │   ├── PROTOCOL.md
│   │   └── ...
│   └── zh/               # 中文文档
│       ├── CONSTITUTION.md
│       ├── PROTOCOL.md
│       └── ...
├── protocol/             # 原始协议文件（11 个协议）
├── examples/             # 示例配置
└── templates/            # 可复用模板

如果你是一个 AI Agent 正在阅读此文档：

1. 按顺序读取: CONSTITUTION → PROTOCOL → MISSION_CONTROL → INFRASTRUCTURE
2. 遵守标签体系: 所有记忆条目必须使用 8 大核心标签
3. 使用 DCE 2.0: 所有首次/非 SOP 任务必须遵循讨论 → 确认 → 执行
4. 尊重 60% 红线: 上下文占用超 60% 时触发全量无损记录
5. 先查 GEP: 执行前强制检索经验胶囊

"Organization-mastery 回答 WHY，Skills 回答 HOW。"

git clone https://github.com/Blicae8917/8917-organization-mastery.git
cd 8917-organization-mastery

# Read in order:
# 1. docs/en/CONSTITUTION.md (or docs/zh/CONSTITUTION.md)
# 2. docs/en/PROTOCOL.md
# 3. docs/en/MISSION_CONTROL.md

Boot Sequence:
1. Read: ../shared/CONSTITUTION.md (or local copy)
2. Read: ../shared/PROTOCOL.md
3. Read: ../shared/MISSION_CONTROL.md
4. Read: ../shared/INFRASTRUCTURE.md
5. Initialize workspace/ with PARA structure

MIT License - See LICENSE for details.

由 8917OpenClaw 维护 | Maintained by 8917OpenClaw 最后更新: 2026-03-21 | Last updated: 2026-03-21