BrainPatch is an intelligent, LLM-powered learning platform that creates personalised courses based on individual knowledge gaps and learning needs. By leveraging advanced assessment techniques and adaptive content generation, BrainPatch bridges the gap between where learners are and where they want to be.

Traditional learning platforms use a one-size-fits-all approach that doesn't account for individual knowledge levels or learning gaps. Learners often:

• Waste time on concepts they already understand
• Miss foundational knowledge that prevents deeper understanding
• Lack personalised pathways that adapt to their specific needs
• Face generic courses that don't align with their current competency level

BrainPatch employs intelligent assessment and adaptive course generation to create truly personalised learning experiences:

1. Dynamic Knowledge Assessment: Multi-layered evaluation system that quickly identifies knowledge gaps
2. Intelligent Course Construction: LLM-powered curriculum generation tailored to individual needs
3. Adaptive Learning Modules: Content that adjusts based on real-time performance and understanding
4. Targeted Gap Filling: Focus on areas where learners need the most improvement

• Rapid, high-level multiple-choice questionnaires
• Smart question selection based on previous responses
• Comprehensive knowledge mapping across topic domains
• Efficient evaluation that respects user time

• LLM-driven curriculum creation based on assessment results
• Dynamic topic selection focusing on knowledge gaps
• Modular course structure allowing for flexible learning paths
• Real-time course adjustment based on progress

• In-depth assessment within each course module
• Content difficulty adjustment based on user responses
• Progressive revelation of concepts building on confirmed knowledge
• Continuous refinement of learning path

• Software developers seeking to improve specific technical skills
• Career changers transitioning into technology roles
• Students supplementing formal education
• Professionals requiring upskilling in new technologies

ReactJS developers and learners, providing a focused scope for initial validation and iteration.

"Learn exactly what you need to know, when you need to know it. BrainPatch eliminates wasted learning time by creating courses that start precisely where your knowledge ends."

• Time-to-course-completion rates
• Module completion percentages
• User retention and return rates
• Assessment accuracy and user satisfaction

• Knowledge improvement scores (pre/post assessment)
• Real-world application success rates
• User-reported confidence improvements
• Career advancement attributable to learning

• Assessment accuracy and relevance
• Course personalisation effectiveness
• LLM response quality and speed
• Platform scalability and reliability

• Frontend Framework: Next.js in static export mode for optimal performance and deployment flexibility
• Deployment Strategy: Automatic GitHub Pages deployment with CDN distribution and static hosting
• CI/CD Pipeline: Comprehensive GitHub Actions workflow with automated testing, building, and deployment
• Client-Side State Management: React-based state handling for assessment flows and user progress
• LLM Strategy: Multi-provider architecture with initial focus on in-browser LLM execution for privacy and offline capabilities

• Initial Implementation: In-browser LLM execution using WebAssembly/WebGPU for local processing
• Multi-Provider Support: Extensible architecture supporting cloud-based providers (OpenAI, Anthropic, etc.)
• Privacy-First Approach: Local processing ensures user data never leaves the device initially
• Fallback Strategy: Graceful degradation from local to cloud providers based on user preference and device capabilities

• Knowledge assessment engine with adaptive questioning
• Multi-provider LLM integration layer for course generation and content creation
• User progress tracking and analytics (client-side storage with optional cloud sync)
• Content delivery and management system

• Support for multiple subject domains beyond ReactJS
• Efficient LLM usage optimisation across local and cloud providers
• Real-time assessment and course adjustment capabilities
• Multi-user concurrent assessment and learning
• Static export compatibility for edge deployment and offline capabilities
• Browser-based LLM performance optimisation for resource-constrained devices
• Seamless provider switching based on performance and availability

• Core assessment engine
• Basic course generation for ReactJS topics
• Simple progress tracking
• User feedback collection

• Advanced adaptive learning algorithms
• Improved assessment accuracy
• Multi-level course complexity
• Performance analytics dashboard

• Additional programming languages and frameworks
• Cross-domain knowledge correlation
• Advanced learning path optimisation
• Community and collaboration features

• Team learning and management features
• Integration with existing learning management systems
• Advanced analytics and reporting
• White-label solutions

Based on proven concepts in adaptive learning and personalised education, with inspiration from successful knowledge assessment platforms. The approach addresses the fundamental inefficiency in traditional learning: the mismatch between course content and individual knowledge levels.

• In-browser LLM performance limitations on lower-end devices
• LLM accuracy and consistency across different providers (local vs cloud)
• Scalability of personalised content creation with resource constraints
• Browser compatibility for WebAssembly/WebGPU LLM execution
• Integration complexity with learning management systems

• User adoption of AI-driven learning platforms
• Competition from established educational technology providers
• Maintaining engagement with adaptive content

• Iterative development with continuous user feedback
• Strong focus on MVP validation before expansion
• Partnership opportunities with educational institutions
• Clear differentiation through personalisation capabilities

The application is automatically deployed to GitHub Pages on every push to the main branch:

1. Quality Gates: All tests, linting, security audits, and builds must pass
2. Static Export: Next.js generates optimized static files for deployment
3. GitHub Pages: Automatic deployment using GitHub Actions with custom domain support
4. CDN Distribution: Global content delivery through GitHub's infrastructure

For local testing of the production build:

npm run build # Generate static export npx serve out # Serve locally on http://localhost:3000

npm run dev # Development server npm test # Run tests npm run coverage # Generate coverage report npm run lint # Check code quality npm run build # Production build

BrainPatch represents a significant opportunity to revolutionise personalised learning by eliminating the inefficiencies of traditional educational approaches. By focusing on individual knowledge gaps and adaptive course generation, the platform can deliver unprecedented learning efficiency and user satisfaction.

The initial focus on ReactJS provides a contained environment for validation and iteration, with clear expansion opportunities across the broader technology education market.