SIMBY - Soon, In My Backyard

Inspiration

Richmond residents often find out about developments too late to meaningfully shape them, and the loudest voices (classic “NIMBY”) aren’t representative of the broader community. SIMBY was inspired by the need to help people engage earlier in the planning process, especially making participation more accessible for marginalized communities (including Spanish speakers) who are under-represented in civic feedback today.

What it does

SIMBY is a mobile app concept that:

• Shows planned development projects on a map (and optional list view), with quick access to understandable project details (status, drawings, dates, owner/city contact, etc.).
• Lets any resident upvote/downvote a project and participate in a discussion thread.
• Lets residents create “PIMBY” requests (“I want X in my neighborhood”) by dropping a pin, choosing a category, and adding a comment—while also encouraging them to upvote/downvote existing similar requests before posting a new one.
• Supports accessibility via translation so more residents can both understand what’s happening and share feedback in their preferred language.
• Envisions notifications for updates to projects/areas residents care about.

How we built it

• Designed the core UX around two main map layers:
  • Planned developments (SIMBY)
  • Resident requests (PIMBY)
• Defined primary user flows:
  • Signup/auth (lightweight profile + zip code/area)
  • Add a request via map pin + category + comment
  • Browse requests/projects via map and list views
  • Engage via votes and comments
• Outlined data/interaction needs (projects, requests, categories, votes, discussions, subscriptions/notifications), plus a roadmap for “nice-to-haves” like recommendations and AR.

Challenges we ran into

• Category design: deciding a usable category taxonomy (and how typeahead maps “pizza” → “restaurants” while still capturing intent).
• Information clarity: planned development details are often complex, inconsistent, and hard to summarize (the need for an “AI summary” is explicitly identified).
• Inclusion/translation: supporting multilingual understanding and participation is essential but non-trivial in content quality, moderation, and workflow.
• Avoiding duplicate requests: encouraging users to discover and vote on existing requests before creating new ones while keeping the flow fast.
• Sustained engagement: defining meaningful notifications/subscriptions without spamming users and while respecting neighborhood boundaries.

Accomplishments that we're proud of

• A clear, end-to-end civic engagement concept that flips “too-late NIMBY” into earlier, more constructive participation.
• A map-first experience that makes both “what’s being built” and “what residents want” visible and actionable in one place.
• Built-in emphasis on equitable participation (translation + lowering barriers to entry).
• Defined concrete MVP flows and a realistic set of “nice-to-haves” (recommendations, AR, city-facing analytics).

What we learned

• Civic participation problems are as much about timing and accessibility as they are about information availability.
• Map UX is powerful, but it needs strong supporting structures (categories, summaries, moderation, subscriptions) to stay useful at scale.
• “Requests” and “developments” are complementary: residents want to both react to plans and proactively express needs—connecting those loops is where value compounds.

What's next for SIMBY

• Finalize and validate the category system (including typeahead behavior and how requests are deduped/merged).
• Define the development data pipeline (where project status/drawings/dates come from) and add AI-generated plain-language summaries.
• Implement the engagement model (votes + threaded comments) with moderation and community guidelines.
• Build subscriptions/notifications tied to zip code or drawn neighborhood areas (and to user-created requests).
• Expand “nice-to-haves”:
  • Recommendation layer (what a neighborhood needs based on business inventory/AI search)
  • Link projects to public meetings/town halls
  • City-council analytics views (most-engaged projects, reconsideration signals, top resident needs)
  • AR “what am I looking at?” camera experience

Built With

• mobx
• python
• react
• supabase
• typescript
• vite