The Challenge
Job searching involves overwhelming information processing, repetitive application workflows, and cognitive load from reviewing countless similar postings.
Solution & Architecture
Swipe-style interface with local AI summarization reduces cognitive load while aggregating multiple job sources into streamlined discovery and application workflow.
Technical Architecture:
React frontend communicating with Python backend, local GPT4All server for AI processing, and SQLite database for job storage and user preferences.
Key Features
Swipe-style job browsing interface
Local GPT4All AI summarization for privacy
Multi-source job aggregation with deduplication
Apply Later queue and research mode
Enhanced filtering and preference management
Skip button functionality with state management
Implementation Highlights
- Full-stack development coordination with AI integration
- Local AI implementation for data privacy
- Multi-source API integration and deduplication logic
- Skip button bug resolution demonstrating debugging skills
- Practical problem-solving for personal productivity enhancement
Results & Impact
Showcases full-stack development capabilities, AI tool integration, and practical application of technology to solve real workflow challenges.
Lessons Learned & Next Steps
🔍 Technical Learnings:
API integration strategies, local AI deployment, React state management, debugging complex user interactions, and privacy-focused AI implementation.
🚀 Future Enhancements:
Cloud deployment strategy, additional job source APIs, advanced filtering algorithms, and team collaboration features.