# files-driven-governance: A Document-Driven Governance Approach for AI Agent Systems

> files-driven-governance provides a systematic project governance methodology. Through document layering and structural family definition, it helps AI Agent projects establish stable fact sources and clear responsibility boundaries.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-03-30T06:46:13.000Z
- 最近活动: 2026-03-30T06:55:22.006Z
- 热度: 159.8
- 关键词: AI Agent, 项目治理, 文档管理, 多代理系统, 治理方法学, Spec-Driven, Kanban, 控制论
- 页面链接: https://www.zingnex.cn/en/forum/thread/files-driven-governance-ai-agent
- Canonical: https://www.zingnex.cn/forum/thread/files-driven-governance-ai-agent
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: files-driven-governance: A Document-Driven Governance Approach for AI Agent Systems

files-driven-governance provides a systematic project governance methodology. Through document layering and structural family definition, it helps AI Agent projects establish stable fact sources and clear responsibility boundaries.

## Background and Problem Awareness

Against the backdrop of the rapid development of AI Agents and multi-agent systems, project governance faces new challenges. Traditional software development governance methods often assume that projects are led by human developers, while AI Agent projects involve complex collaboration between humans, agents, tools, documents, and processes. This new collaborative form calls for new governance ideas.

The files-driven-governance project is a methodology proposed to address this need. It focuses not on "how many documents there are" but on more fundamental questions: Where are facts defined? How does information flow? How is distortion detected? How is order restored?

## Core Idea: From Documents to Governance Carriers

The core idea of files-driven-governance is to elevate documents from "passive explanations" to "active governance carriers". It believes that documents are not only explanatory materials for people to read but also governance tools that define facts, promote execution, help restore order, and display externally.

This methodology emphasizes that in AI Agent projects, the following questions must first be answered:

- **Where is the truth source**: Which files define facts, rules, and boundaries?
- **How to advance the process**: Which files carry tasks, discussions, decisions, and handovers?
- **How to summarize status**: Which files help quickly restore the current situation?
- **How to project for display**: Which files are only responsible for external explanation and reporting?

## Four-Layer Document Model

files-driven-governance proposes a clear four-layer document model:

## Layer 1: Truth Source (truth_source)

The truth source is the material that defines facts, rules, and boundaries. It is the "constitution" of the project, and all other documents should be derived from it. In AI Agent projects, the truth source may include:

- Skill definition files (SKILL.md)
- Rules and policy documents
- Object boundary definitions

The key features of the truth source are stability, clear versioning, and controlled modifications.

## Layer 2: Execution Object (execution_object)

The execution object is the carrier for advancing tasks, discussions, decisions, reviews, and handovers. It includes:

- Task lists and workflow definitions
- Discussion records
- Decision documents
- Review checkpoints

The characteristics of this layer of documents are high fluidity, but they must be traceable back to the truth source.

## Layer 3: Status Projection (status_projection)

Status projection is a summary document that helps quickly restore the current situation. It cannot rewrite upstream content; it can only summarize and present. Examples include:

- Project status reports
- Progress summaries
- Handover guides

## Layer 4: Display Projection (display_projection)

Display projection is only responsible for external explanation, reporting, or display, and does not participate in actual governance. Examples include:

- README.md (as an entry point)
- External promotional materials
- User manuals