digital-brain

Digital Brain is a comprehensive, structured personal operating system designed for founders building in public, content creators, and professionals aiming to optimize their digital output and relationship management. The system employs a progressive disclosure architecture, ensuring that the AI agent only loads necessary context—such as voice guidelines, brand pillars, or contact history—at the precise moment required by the task. By organizing information into distinct modules like identity, content, knowledge, network, and operations, it minimizes context window degradation and maximizes model effectiveness.

• Content Generation Pipeline: Automates the creation of posts, threads, and newsletters by referencing identity/voice.md and brand.md to ensure consistent tone.

• Personal CRM & Network Management: Maintains relationship tiers (inner, active, network, dormant) with append-only logging in interactions.jsonl.

• Productivity & Operations: Tracks goals, manages meeting preparation through context briefs, and facilitates weekly reviews via custom automation scripts.

• Structured Data Strategy: Utilizes JSONL for append-only logs, YAML for configuration, and Markdown for narrative context to ensure high-fidelity retrieval.

• Always read identity/voice.md before performing any content generation tasks to maintain brand consistency.

• Use append-only practices for all JSONL files; mark entries as "archived" instead of deleting to preserve historical patterns.

• Activate modules on-demand: identity, content, knowledge, network, and operations are designed to be loaded independently to manage the attention budget.

• Expect inputs like "write a post," "prepare for meeting," or "who is [name]" and rely on the local repository structure for context-rich, reliable outputs.

• Designed for compatibility with Claude Code, Cursor, and various agent platforms supporting tool-calling and file-system-based context discovery.