Turn YouTube videos into language lessons with transcript-based vocab and phrases
Lingooso is a web app that lets users paste a YouTube video URL and get a structured language lesson from its transcript. It breaks the transcript into digestible chunks, extracts vocabulary and phrases, and presents them for study. The app solves the problem of learning real, spoken language from authentic content rather than textbook phrases, targeting self-learners who want to learn from videos they already enjoy.
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Chrome extension turns Netflix into language learning tool
A Chrome extension that overlays language learning features on Netflix, allowing users to learn English, French, or Spanish while watching shows. It uses LLMs to provide translations, explanations, or interactive subtitles, making passive viewing into active learning.
AI tool that converts Korean cooking videos into step-by-step recipes
KRecipes is a web app that takes a YouTube cooking video URL and uses AI to generate a structured recipe with ingredient list, step-by-step instructions, serving size adjustments, and timestamps linked to the video. It supports English, Korean, and Spanish, aiming to make Korean cuisine more accessible to home cooks worldwide.
PrismClip: Search for moments in long videos
PrismClip is a tool that lets users search for specific moments in long videos, giving more editorial control than automated clipping tools like OpusClip. It uses LLMs to understand natural language queries and find relevant scenes. Built for creators who want to extract specific clips without dealing with complex editing software.
YouTube title and thumbnail declickbaiter using transcript context
Face Value is a browser extension that rewrites YouTube video titles and thumbnails to remove clickbait. It uses transcript context to generate accurate, descriptive titles and neutral thumbnails, making the feed easier to browse.
Interactive app teaching LLM pipeline from pattern matching to transformer training
An interactive web app that walks through every stage of the LLM pipeline, from basic pattern matching to training a transformer from scratch. It includes working code that users can run locally, making it an educational tool for developers and learners.

