Personal OS Framework
A methodology and toolset for building a second brain that AI can understand and maintain.
The Core Idea
The human does the work. The AI records it. The AI reads the records. The AI understands the human. The AI helps more effectively.
This is not a standalone tool. It requires an AI collaborator that reads, updates, and maintains the system through ongoing conversation.
What This Framework Provides
Decision Log
Record important decisions with rationale and follow-up actions. Every significant judgment gets a permanent record.
Review Operator
Generate daily, weekly, and monthly reviews from project state. Surface stale projects, identify blockers, generate follow-up actions.
Routing Assistant
Classify incoming information by type and destination. Every piece of information has a canonical home.
Task Layer
Define what a task looks like. Track status, ownership, and aging.
Execution Layer
Record when work begins. Identify started tasks that have gone stale.
Decision Support Layer
Monitor decision follow-ups and task health. Proactive monitoring without manual recounting.
Memory Distiller
Convert accumulated raw captures into structured knowledge. Raw notes become permanent knowledge after a 7-day aging period.
Workflow
CODEBLOCK0
Information enters the system. It gets classified. Work happens. Regular reviews keep everything current.
How It Works
CODEBLOCK1
Key Principles
The AI does not wait for commands. The AI reads the system, understands the human, and acts proactively.
Reviews keep the system alive. Without regular reviews, the system becomes stale.
Decisions are the most valuable content. Log them with context.
Files
Every personal-os has these core files:
- -
STATE.md — current project states - INLINECODE1 — active tasks
- INLINECODE2 — decision log
- INLINECODE3 — blocked decisions
- INLINECODE4 — system activity log
For AI Collaborators
Read the personal-os after each conversation. Update relevant files. The system stays current because the AI keeps it current.
When to Use This Framework
Use when:
- - You want to build a personal OS that AI can understand and maintain
- You want decisions logged with context
- You want regular reviews that surface stale projects
- You want clear routing rules for information
- You want AI to collaborate proactively
Do not use when:
- - The work is too small to benefit from structure
- There is no commitment to regular reviews
- The human is not willing to work with an AI collaborator
Success Metrics
The framework is working when:
- - You can answer "what was the reasoning behind X decision?"
- Reviews surface real stale items
- Decisions have follow-up actions that get done
- The AI understands your context
- The system stays current without constant maintenance
个人操作系统框架
一种构建AI可理解与维护的第二大脑的方法论与工具集。
核心理念
人类负责执行。AI负责记录。AI读取记录。AI理解人类。AI提供更有效的协助。
这不是一个独立工具。它需要一个AI协作者,通过持续对话来读取、更新和维护系统。
本框架提供的内容
决策日志
记录重要决策及其依据和后续行动。每个重大判断都会留下永久记录。
回顾生成器
根据项目状态生成日、周、月回顾。发现停滞项目,识别障碍,生成后续行动。
路由助手
按类型和目的地对输入信息进行分类。每条信息都有其规范归宿。
任务层
定义任务形态。追踪状态、负责人和时效。
执行层
记录工作开始时间。识别已启动但已停滞的任务。
决策支持层
监控决策后续行动和任务健康度。主动监控,无需手动重述。
记忆提炼器
将积累的原始记录转化为结构化知识。原始笔记经过7天沉淀期后成为永久知识。
工作流程
捕获 → 结构化 → 执行 → 反思
信息进入系统。经过分类。工作得以开展。定期回顾保持一切更新。
运作方式
人类执行某项操作
↓
AI观察或被告知
↓
AI记录在个人操作系统中
↓
AI读取个人操作系统
↓
AI理解人类
↓
AI提供更好的协助
关键原则
AI不等待指令。AI读取系统、理解人类并主动行动。
回顾让系统保持活力。没有定期回顾,系统就会变得陈旧。
决策是最有价值的内容。记录时附带上下文。
文件
每个个人操作系统都包含这些核心文件:
- - STATE.md — 当前项目状态
- TODO.md — 活跃任务
- DECISIONS.md — 决策日志
- PENDING-DECISIONS.md — 受阻决策
- HEARTBEAT-LOG.md — 系统活动日志
给AI协作者
每次对话后读取个人操作系统。更新相关文件。系统保持最新,因为AI让它保持最新。
何时使用本框架
适用场景:
- - 你想构建AI能理解与维护的个人操作系统
- 你想记录附带上下文的决策
- 你想要能发现停滞项目的定期回顾
- 你想要清晰的信息路由规则
- 你想要AI主动协作
不适用场景:
- - 工作规模太小,无需结构化
- 无法承诺定期回顾
- 人类不愿与AI协作者合作
成功指标
框架生效的标志:
- - 你能回答X决策背后的依据是什么?
- 回顾确实发现停滞项目
- 决策有后续行动且得到执行
- AI理解你的上下文
- 系统无需持续维护也能保持最新