A methodology and toolset for building a second brain that AI can understand and maintain.
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.
Record important decisions with rationale and follow-up actions. Every significant judgment gets a permanent record.
Generate daily, weekly, and monthly reviews from project state. Surface stale projects, identify blockers, generate follow-up actions.
Classify incoming information by type and destination. Every piece of information has a canonical home.
Define what a task looks like. Track status, ownership, and aging.
Record when work begins. Identify started tasks that have gone stale.
Monitor decision follow-ups and task health. Proactive monitoring without manual recounting.
Convert accumulated raw captures into structured knowledge. Raw notes become permanent knowledge after a 7-day aging period.
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Capture → Structure → Execute → Reflect
Information enters the system. It gets classified. Work happens. Regular reviews keep everything current.
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Human does something
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AI observes or is told
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AI records in personal-os
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AI reads personal-os
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AI understands the human
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AI provides better help
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.
Every personal-os has these core files:
STATE.md — current project statesTODO.md — active tasksDECISIONS.md — decision logPENDING-DECISIONS.md — blocked decisionsHEARTBEAT-LOG.md — system activity logRead the personal-os after each conversation. Update relevant files. The system stays current because the AI keeps it current.
Use when:
Do not use when:
The framework is working when: