An interactive, vibe-coded guide to Dallas neighborhoods — built for D Magazine readers who want to explore by feel, not just census data. Live and driving traffic.
D Magazine's neighborhood coverage was sitting in static articles — rich editorial writing that didn't let readers interact or self-sort. Someone trying to figure out where to move in Dallas couldn't ask "which neighborhood fits my vibe?" They got a listicle and had to read through 15 entries to find the two that matched.
The editorial team wanted something that felt alive — a tool readers would actually share, spend time with, and return to. Not another roundup article. Something that used the existing neighborhood expertise in a way that let readers explore on their terms.
Vibe-First Data Model. Instead of leading with demographics and median home prices, each neighborhood was modeled around its character: walkable vs. car-dependent, gritty vs. polished, local-owned vs. chains, family-focused vs. nightlife. These qualitative dimensions became filterable attributes.
Interactive Filter UI. The interface lets readers select what matters to them — "I want walkable, local-feel, with good restaurants and not too loud" — and surfaces matching neighborhoods ranked by fit. It's not a search engine. It's a conversation about what kind of place someone wants to live.
Editorial + Product Hybrid. D Magazine's writers contributed the neighborhood descriptions and vibe ratings. The build translated that editorial judgment into structured data without losing the voice. Every neighborhood page reads like D Magazine — it just happens to also be filterable and interactive.
Media companies have more editorial expertise sitting unused than most realize. Static articles are a one-time read. Interactive tools built from that same expertise become durable assets — things readers bookmark, share, and come back to. The neighborhood guide turned a good article into a product. Same content, dramatically more utility and repeat engagement. That's the bet worth making for any publisher with deep subject matter expertise.
Explore the live guide at big-d-neighborhood-finder.lovable.app.