Developers learning transformer architectures often hit walls with abstract mathematical explanations lacking visual grounding.
Create an interactive web app that lets users explore transformer components, data flows and attention mechanisms through animated diagrams and hands-on tweaking.
AI startups would pay to license this as internal training material, and individual practitioners would subscribe for ongoing learning.
Start with a single transformer variant (like BERT) showing encoder/decoder flow, then expand to different architectures.
Risk: Academic papers and existing blog posts already explain transformers, so differentiation is key.