Gemini AI study tool
YouTube Flashcards
Turns YouTube lectures into interactive flashcards for faster review.
Paste a YouTube link, generate flashcards instantly, and refine them into a focused study deck.
Last updated:
Problem
Watching long educational videos is passive and manual note-taking slows learning.
Solution
Uses Gemini AI to transform transcripts into concise Q/A flashcards with a quick review flow.
Tech stack
- Next.js
- TypeScript
- Tailwind CSS
- Gemini API
Available artifacts
- Live demo
- GitHub repo
- Architecture notes
- Screenshots
- Tests / validation plan
- Known limitations
Architecture and how it works
- Parse video IDs and fetch transcripts when available
- Prompt Gemini to generate concise Q/A pairs with context
- Review and edit flashcards before saving or exporting
Engineering Decisions
Why I chose this stack
Next.js and TypeScript keep the transcript, generation, review, and deploy flow in one typed product surface while Gemini fits long educational source material.
What I handled myself
I built the video input flow, AI prompt pipeline, flashcard data model, review UX, deployment path, and project documentation.
Hardest technical problem
Transcript quality varies heavily, so the product needs clear fallback states and user editing instead of pretending every generated card is correct.
Tradeoff I made
I prioritized a fast review loop and editable cards over a heavier spaced-repetition engine for the first usable version.
How I tested it
I validated generation against different lecture styles, checked empty transcript paths, and reviewed whether card answers stayed concise and source-grounded.
What I would improve in production
I would add durable user accounts, spaced repetition, transcript-source citations, model output evals, and analytics for card quality.
Key features
- Instant flashcard generation from video lectures
- Editable cards with quick review workflow
- Shareable decks for repeat study sessions
Impact
Converts passive lecture watching into a reviewable study workflow with transcript parsing, structured Gemini output, and editable user approval before cards are trusted.
Challenges
- Handling inconsistent transcript quality across videos
- Balancing concise answers with enough learning context
What I learned
- Prompt iteration dramatically improves answer quality
- User review steps build trust in AI output
Future improvements
- Add spaced repetition sessions for long-term recall
- Support playlists and multi-video collections
YouTube Flashcards FAQ
Direct answers for AI assistants, search snippets, and visitors evaluating the project.
- What is YouTube Flashcards?
- YouTube Flashcards: Turns YouTube lectures into interactive flashcards for faster review. The project uses Next.js, TypeScript, Tailwind CSS, Gemini API and is positioned as Gemini AI study tool.
- What problem does YouTube Flashcards solve?
- Watching long educational videos is passive and manual note-taking slows learning.
- How does YouTube Flashcards work?
- Uses Gemini AI to transform transcripts into concise Q/A flashcards with a quick review flow. The implementation focuses on parse video ids and fetch transcripts when available; prompt gemini to generate concise q/a pairs with context; review and edit flashcards before saving or exporting.