Finding Warsaw events by vibe, not keywords

Traditional search fails when you know how you feel but not what to search for.

I designed and prototyped a conversational guide that acts like a knowledgeable local friend — understanding mood, energy and context to suggest events worth attending.

Keyword search doesn’t work when you know how you feel (“quiet and reflective”, “playful and social”) but not what to search for. Discoverers miss meaningful experiences that match their current mood. Local curators and scene insiders have no easy way to share hidden gems.

We needed a system that combines AI’s ability to understand intent with human taste and local knowledge.

The experience supports both quick WhatsApp chats and a clean web interface, lowering friction while maintaining depth. Recommendations are curated and opinionated instead of exhaustive. The architecture is hybrid — WhatsApp plus web — with a foundation for future curator contributions.

Traditional filters assume users know exact genres or venues. Showing too many events feels noisy; too few feels empty. Long-term value also requires input from locals and insiders, not just AI scraping.

It is a base for exploring vibe-led search as a personal city tool. The project clarified which questions earn useful answers, and where event data quality still limits recommendations.

I learned that discovery UX is emotional before it’s informational. The interface has to honor that sequence, not fight it.

If I did it again, I would test with people who deliberately avoid social media, earlier — so edge cases in sourcing and trust show up before polishing UI states.