A PWA for exploring movies and TV shows that uses user-interest signals to improve discovery and recommendations over time.
The problem
Search alone is not enough for personal discovery: the product needs a model that gathers progressive signals about preferences.
The solution
I designed an engine that combines catalogue exploration, taste profiles and explicit signals to make suggestions more relevant.
What I built
I built a React and Vite experience with Node and Express APIs, MySQL persistence and Claude and TMDB integrations.
How it works
Discovery ? interest signals ? taste profile ? ranking and recommendations ? personal lists.
Engineering choices
Separating PWA UI, application APIs, catalogue data and user signals keeps the recommendation engine evolvable.
Outcome
A discovery product that uses each interaction to improve the user profile, not only to return search results.
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