mic: Micro prediction markets for what matters

What if prediction markets existed for your life? mic is a micro prediction market for localized communities—letting users trade on meaningful events and aggregate shared expectations in real time.

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Inspiration

Prediction markets are one of the best ways to aggregate information, but most platforms are built for finance professionals. We wanted to make that same “collective intelligence” experience accessible to students in a campus-friendly format. The goal was to let communities ask meaningful yes/no questions, express conviction with bets, and learn from market sentiment over time.

What it does

mic is a micro prediction market platform for student communities.

  • Users sign in, join channels, and participate in yes/no markets.
  • Markets include clear metadata: title, rules, resolution source, close time, and expected resolution time.
  • Users can place and adjust positions (buy/sell behavior), track sentiment, and discuss markets.
  • Admins can create/manage channels and markets, then resolve outcomes.
  • The app separates active vs resolved markets and keeps role-specific experiences for admins vs non-admins.

How we built it

We built the product as a full-stack web app with:

  • Next.js (App Router) for frontend + API routes
  • TypeScript for safer, maintainable code
  • Tailwind CSS for a clean, minimal UI
  • Supabase Auth + Postgres for authentication and persistence Architecture highlights:
  • Role-aware access control in API routes (admin vs non-admin actions)
  • Structured schema around profiles, channels, channel_members, markets, bets, and positions
  • Real-time-ish market updates and sentiment visuals on market pages
  • Admin tooling for market lifecycle (creation → monitoring → resolution)
  • UI flows tuned for clarity: channel browse/join, market detail, bet entry, resolve confirmation

Challenges we ran into

  • Keeping role-based behavior consistent across UI and API as features expanded.
  • Avoiding confusing market language and simplifying user-facing terminology.
  • Handling schema/implementation drift while iterating (field consistency, endpoint behavior).
  • Balancing live sentiment with stable resolved-market display semantics.
  • Supabase setup issues (env/auth config and permission alignment) during integration.

Accomplishments that we're proud of

  • Built a coherent end-to-end prediction market experience with strong admin/non-admin separation.
  • Designed a schema-backed workflow that supports market creation, participation, and resolution.
  • Added richer market context (rules, resolution source, timeline fields) for trust and clarity.
  • Delivered a polished UI with consistent yes/no visual semantics and cleaner user flows.
  • Iterated fast on feedback and kept the app buildable and deployable throughout.

What we learned

  • Product clarity matters as much as technical correctness in market apps.
  • Rapid prototyping works best when data model and API contracts stay tightly aligned.

What's next for mic: Micro prediction markets for what matters

  • Add stronger market integrity features (audit logs, resolution notes/history, dispute windows).
  • Add notifications, watchlists, and better discovery across channels and topics.
  • Expand social features (comments ranking, creator profiles, credibility tracking).
  • Add analytics dashboards for market quality, participation, and forecasting performance.
  • Pilot with real campus orgs/classes and iterate based on real user behavior.

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