LLM Decoded
A bite-sized, no-code interactive learning app that demystifies how large language models actually work — from tokens to attention heads to hallucinations — through 5-minute animated lessons and hands-on widgets.
Students and working professionals who use AI daily but don't understand what is happening under the hood
- Interactive 'attention head' visualizer that shows which words a model focuses on, step by step
- Bite-sized 5-minute lessons (tokens, embeddings, attention, decoding, hallucinations) with quiz checkpoints
- Plain-English glossary that maps any AI buzzword to a one-sentence visual explanation
- A 'what would the model do?' sandbox where users type a prompt and see the token-by-token decoding
Public curiosity about how ChatGPT and similar tools actually work is exploding, while most educational content is still either dry math papers or 3-hour YouTube deep-dives — the GitHub repo with 120 stars and a 6-part blog series shows people are hungry for a friendlier on-ramp.
Multiple sources confirm surging interest in beginner-friendly explanations of LLMs — including an animated walkthrough featured on Hackaday, and beginner-targeted LLM courses like Simpliv's no-coding-required guide.An Animated Walkthrough Of How Large Language Models Work ↗Building Your First Large Language Model (LLM) - A Beginner's Guide (No Coding Required) ↗
Crowded landscape includes Decyphon's interactive visual guide, Towards Data Science visual explainers, full Coursera specializations, and long YouTube deep-dives — but no clear mobile-first, bite-sized, widget-driven app leader has emerged.How LLMs Work: A Visual Guide to Large Language Models ↗Visual Guides to understand the basics of Large Language Models ↗
Comparable educational products charge meaningfully (Coursera Plus at $59/mo or $399/yr), but this niche competes heavily with free YouTube visualizers and blog series, limiting willingness-to-pay for a 5-minute lesson format.Coursera Pricing (2026) → Plans & Cost Breakdown ↗Best Artificial Intelligence Courses & Certificates [2026] ↗
Transformer fundamentals (tokens, attention, embeddings) are architecturally stable for years, and continual new model releases keep refreshing interest in the underlying concepts.
Interactive widgets for tokens/attention are well-scoped and buildable with standard web animation libraries plus an LLM API for live hallucination demos; main cost is expert-reviewed content production.