Prompt
Design a Personal Knowledge Narrative Tool
Use this when you need to plan a second-brain application that connects notes into a living story with AI-powered connections and timeline visualizations.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You are a senior product designer and full-stack developer experienced in building personal knowledge tools. Your goal is to design a comprehensive feature set and architecture for a narrative note-taking system called "Thread."
Context you provide
- {{target_user}} (optional): Describe the intended user (e.g., "a busy professional who wants to journal and reflect").
- {{preferred_stack}} (optional): Any specific technology preferences beyond the core stack (React, LLM API, D3.js).
Instructions
- Start by defining the core value proposition: a tool that turns isolated notes into a connected, narrative story of a person's life or project.
- Design note capture with fast input: title, body, tags, date, and an optional "life chapter" label (user-defined periods like "Building the company" or "Year in Berlin"). Explain how chapter labels create narrative structure.
- For the connection engine: describe how an LLM API periodically analyzes notes and suggests thematic connections. The user can accept or reject, creating bidirectional links.
- For the narrative timeline: use D3.js to display notes grouped by chapter, with zoom from decade to week views. Click a note to see it in context.
- Weekly synthesis: every Sunday, AI generates a "week in review" paragraph from that week's notes, stored as a special entry in the timeline.
- Monthly pattern report: AI identifies recurring themes (concepts mentioned 5+ times), most-linked ideas, and dormant ideas (not referenced in 60+ days) as "worth revisiting."
- Chapter export: allow selecting any chapter by date range and exporting as a formatted PDF narrative.
- Tech stack: React frontend, LLM API for intelligence, D3.js for timeline, localStorage with JSON export/import for backup. Emphasize literary design with serif fonts and generous whitespace.
Output format Provide a structured design document with sections: Overview, Core Features (bullet list with descriptions), User Stories, Architecture & Tech Stack, and Key Design Decisions.
Guardrails
- Stay at the conceptual level; do not produce actual code.
- Focus on user experience and feature integration, not on implementation specifics like API endpoints.
- Ensure all AI-generated features acknowledge potential privacy and data handling considerations.
Example Target user: "A remote worker who wants to track personal growth over years." Preferred stack: "React + Node.js backend + PostgreSQL" (Adjust tech stack discussion accordingly.)