The Science of Understanding AI-Generated Code
VibeUniv is not just an educational platform. By combining an ontology-based knowledge system with an adaptive learning engine, we deliver an optimized learning experience for each user.
Knowledge Graph System
Even with thousands of books in a library, you can't find what you need without a classification system. VibeUniv's knowledge graph is the classification system for the programming world.
Concept Classification by Technology
Core concepts for each technology like Next.js, React, and TypeScript are systematically classified.
Prerequisite Mapping
Automatically identifies prerequisite relationships like "You need to know Components before learning React Hooks."
Individual Mastery Tracking
Tracks how well you understand each concept individually and automatically identifies areas that need improvement.
π‘ Thanks to the knowledge graph, contextual learning recommendations like "You've mastered App Router, so you're ready to learn Server Actions" become possible.
Adaptive Curriculum Engine
Even with the same technology, every project's code is different. VibeUniv analyzes your actual code and generates learning content tailored to it.
Project Analysis
Analyzes source code to automatically identify technologies, patterns, and architecture used.
Auto Difficulty Adjustment
Automatically determines beginner/intermediate/advanced level based on project complexity and technology usage. Beginners get more analogies and visual explanations.
Your Code as Textbook
Explains by referencing the code you actually built, not abstract examples. Like "In your layout.tsx, this part..."
Diverse Learning Activities
Reinforces understanding through various formats: concept explanations, code walkthroughs, multiple-choice quizzes, code challenges, and reviews.
Local-First AI Architecture
When connected via MCP (Model Context Protocol), AI analysis and content generation are performed directly in your local environment. Your code is never sent to external servers.
Code Privacy Guaranteed
Analysis is performed by your local AI, and only the results (tech stack list) are stored on the server. Your source code is never transmitted to the server.
Cost Efficient
By minimizing server-side AI calls, we've drastically reduced operational costs. These savings translate to affordable pricing for you.
Multi LLM Support
No vendor lock-in to a single AI model. With 11 LLM providers supported, you can choose the best model for each task.
Code analysis & learning content
General-purpose AI tasks
Large context processing
Fast and economical processing
π‘ BYOK (Bring Your Own Key): On the Pro plan, register your own API key to freely use any model you prefer. Keys are securely stored with AES-256-GCM encryption.
Content Quality Assurance
AI-generated learning content goes through automatic quality validation. If it falls below standards, it's automatically regenerated, ensuring a consistently high-quality learning experience.
Difficulty-Specific Standards
Beginners get more detailed explanations, more code examples, and more diverse quizzes. Advanced learners get concise, focused content.
Auto Validation & Regeneration
If generated content doesn't pass quality standards, it's automatically regenerated. Users always see validated content.
Multilingual Content
Native-quality learning content in both Korean and English. Not translations, but content optimized for each language.
How We Differ from Traditional Learning
Traditional
- β Learning with generic example code
- β Same curriculum for everyone
- β Random learning without prerequisites
- β Content unrelated to my project
- β Difficult to track learning progress
VibeUniv
- β Learn with your actual code as textbook
- β 1:1 curriculum tailored to your project
- β Systematic learning based on knowledge graph
- β AI tutor answers in your code's context
- β Concept-level mastery + streak tracking
Experience the Difference
Connect your AI-built project and start ontology-based personalized learning.