Interactive Guide Uses Tic-Tac-Toe to Demystify Transformer Architecture

A developer has published an interactive educational guide that teaches Transformer model architecture using a game of fading Tic-Tac-Toe instead of traditional text prediction. The guide walks readers through every core component of a Transformer, including tokenization, self-attention, causal masking, residual connections, and feed-forward layers. Users can play the game while inspecting matrix multiplications and watching tokens flow through the network in real time. Interactive visualizations accompany each stage of the pipeline, from input tokens to the model's final move prediction. The guide also includes ablation experiments that demonstrate how removing key components — such as positional encoding or the MLP — affects model behavior.