2/22/26 Devlog
Project Vision
I really wanted to build something to help me learn faster and excel with less effort in school.
So I started building serify: A context-aware learning reflection engine designed to move beyond simple testing. It uses AI to analyze conceptual depth, identify misconceptions, and map knowledge gaps in real-time.
Core Features Implemented
1. AI-Powered Diagnostic Engine
- Content Processing: Extracts hierarchical concept maps from raw text, YouTube URLs, or PDFs using Gemini 2.5 Pro.
- Dynamic Question Generation: Creates retrieval, application, and misconception-probe questions tailored to the extracted concepts.
- Real-time Answer Analysis: Analyzes student responses for factual accuracy and conceptual depth without blocking the user flow.
- Feedback Synthesis: Generates a comprehensive report including a summary of grasp, strength maps, and actionable focus suggestions.
2. Data & Persistence
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Session History: Persistent tracking of all historical and active sessions in
localStorage. - Knowledge Gaps: A centralized summary of identified conceptual gaps rendered on the main dashboard.
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Storage Utility: Centralized
lib/storage.tsfor managing the lifecycle of learning sessions.
Technical Architecture
- Framework: Next.js (Pages Router)
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AI Backend: Google Gemini API (using 2.5 pro) via
@google/generative-ai - Styling: Vanilla CSS with modern CSS variables for theming and Glassmorphism effects.
- Icons: Lucide React
- Authentication: Firebase/Custom integration (ready for bridge to Supabase).
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