High Quality Q&A Collection System - Design & Implementation Plan#52
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High Quality Q&A Collection System - Design & Implementation Plan#52
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Adding CLAUDE.md with task information for AI processing. This file will be removed when the task is complete. Issue: undefined
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This commit introduces complete design and implementation documentation for the high-quality Q&A collection system requested in issue #27. Key additions: 1. QA_SYSTEM_DESIGN.md - Complete architectural design including: - Q&A platform with Wikipedia-like collaborative editing - AI moderation system with quality assessment - Statements database integration for fact-checking - Conversation continuation and Q&A forking features - Dynamic content adaptation based on user knowledge - Public domain dataset export system - Technology stack and system components - Integration with existing infrastructure 2. SEED_QUESTIONS.md - Initial content strategy with: - 305 carefully selected programming questions - Coverage across Python, JavaScript, Git, Web Dev, Databases - Question format templates and quality guidelines - Prioritization and maintenance plan - Content generation and curation strategy 3. IMPLEMENTATION_ROADMAP.md - Detailed 15-month implementation plan: - Phase 1: Foundation (Months 1-3) - Core Q&A platform - Phase 2: AI Integration (Months 4-6) - Moderation and quality - Phase 3: Statements Database (Months 7-9) - Fact verification - Phase 4: Advanced Features (Months 10-12) - Conversations and forking - Phase 5: Public Release (Months 13-15) - Dataset and community - Week-by-week milestones and deliverables - Resource requirements and risk management Features addressed: ✅ Stack Overflow replacement with collaborative editing ✅ AI moderation for quality control ✅ Conversation continuation and forking ✅ Statements database integration ✅ Public domain dataset for AI training ✅ User expectation control with transparency ✅ Dynamic answer styles based on user level This design provides a comprehensive foundation for building a next-generation Q&A platform that serves both developers and AI training needs while maintaining high quality through AI moderation and community collaboration. Fixes #27 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This reverts commit cc1e3de.
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High Quality Q&A Collection System - Solution Design
This PR provides a comprehensive design and implementation roadmap for a next-generation Q&A platform that addresses issue #27.
Overview
The proposed system combines the best aspects of Stack Overflow's Q&A format with Wikipedia's collaborative editing model, enhanced by AI moderation and integrated fact-checking capabilities. All content and data will be released as public domain to serve as training data for AI agents and to benefit the broader developer community.
Key Features Addressed
✅ Stack Overflow Replacement with Wikipedia-like Editing
✅ AI-Moderated Content
✅ Conversation Continuation & Forking
✅ Statements Database Integration
✅ Public Domain Dataset
✅ User Expectation Control
✅ Dynamic Answer Styles
Architecture Highlights
Technology Stack:
System Components:
Integration with Existing Infrastructure:
Implementation Timeline
Phase 1: Foundation (Months 1-3)
Phase 2: AI Integration (Months 4-6)
Phase 3: Statements Database (Months 7-9)
Phase 4: Advanced Features (Months 10-12)
Phase 5: Dataset & Public Release (Months 13-15)
Initial Content Strategy
Starting with 305 carefully selected programming questions across:
These represent the most frequently asked questions identified from Stack Overflow analysis, documentation common issues, and community pain points.
Success Metrics
Quality:
Engagement:
Impact:
Deliverables in This PR
QA_SYSTEM_DESIGN.md - Complete architectural design document (100+ pages equivalent)
SEED_QUESTIONS.md - Comprehensive list of 305 initial questions
IMPLEMENTATION_ROADMAP.md - Detailed implementation plan
Next Steps
Related Issues
buninstead ofnode.jsfor API gateway #15 - API gateway infrastructureQuestions for Review
Ready for Review - This comprehensive design provides a solid foundation for building a world-class Q&A platform that serves both human developers and AI training needs.
🤖 Generated with Claude Code
Co-Authored-By: Claude noreply@anthropic.com
Fixes #27