Hello HN, I’m the solo developer behind ScrollMind. I built this because I was frustrated with the two extremes of learning AI: Academic Textbooks: 50 pages of Greek notation before you write a single line of code. Hype Twitter/YouTube: "Build an LLM in 5 minutes" tutorials that skip all the engineering fundamentals. I wanted something in the middle: Engineering intuition. What is it? ScrollMind is an interactive guide to Neural Networks that works like a social media feed. Instead of 2-hour lectures, the content is broken down into bite-sized "posts"—diagrams, interactive quizzes, and short explainers. The goal is to turn "doom-scrolling" muscle memory into learning time. You can finish a concept (like Embeddings or Backpropagation) in the 5 minutes you have between meetings. What’s under the hood? The Content: It covers the full "Intro to AI" stack: Vectors, Layers, Non-Linearity, Loss Functions, and Optimization. The Approach: Visuals first, notation second. We visualize high-dimensional concepts so you understand what the math is doing before you memorize the formula. The Stack: React/Vite frontend with Firebase for the backend. Content is structured as a DAG (Directed Acyclic Graph) of micro-concepts rather than linear chapters. The "Business Model" The entire "Intro to AI" course (12 concepts, 100+ posts) is free. I plan to release advanced, paid courses later (e.g., "Building LLMs from Scratch"), but the foundational knowledge should be accessible to everyone. I’d love your feedback on: Does the "feed" format actually help you retain info, or is it too fragmented? Are the visual explanations for concepts like "Vectors" and "Embeddings" intuitive enough? Check it out here: [Link to your deployed app] Thanks!