150 million Americans play unorganized sports. Zero data infrastructure exists for them.

BIBI-5 is an agentic AI companion that learns which courts you love, which NBA players shape your style, what brands define your off-court identity — then curates a bespoke experience around public basketball. Not a scheduling tool. A companion that knows you. The technical challenge: personalization when users don't exist in any database yet.

Our content pipeline ingests from five sources — Google News RSS, NewsData.io, YouTube, podcasts, direct feeds — 3,143 items categorized daily for under $4/day. That feeds BIBI-5's understanding of basketball culture: sneaker drops, player fashion, music, social moments. The moat is bidirectional — athletes influence rec players (LeBron's style shapes what people wear to the park), and rec players predict which athletes trend nationally. No one else captures this signal.

I'll walk through the live architecture — multi-source ingestion design, cold-start personalization strategy, and why cultural data (fashion, music, court preferences) beats game stats for engagement. Includes a live demo of the content pipeline processing articles in real time. Real costs, real tradeoffs, real code on screen.

You'll walk away able to build personalization without existing user profiles, design near-zero-cost content pipelines at scale, and identify bidirectional data moats in consumer products.