Back to Projects
Flagship case studyreview surface

The AI Cook-Up

A concept site designed for community AI development events in Houston. The platform explores event management with LLM-powered team matching. 15 commits, ~4K LOC — built as a prototype for a community event idea.

Event PlatformTeam MatchingNext.jsSupabaseAI Integration
The AI Cook-Up

Build surface

The implementation surface for this system. These are the layers that mattered in practice, not a generic skills wall.
Frontend
Next.js 15, React 18, TypeScript, Tailwind CSS
Backend
Supabase, PostgreSQL, Next.js API Routes
Authentication
Supabase Auth, Auth Helpers
UI/UX
Framer Motion, Radix UI, Custom Components
AI Integration
OpenAI API, LLM-based Team Matching
State Management
Zustand, React Hooks

The Concept

The AI Cook-Up is a concept site exploring how to organize AI hackathon events where participants with diverse skills and experience levels need to form balanced, productive teams. Built as a prototype for a community event idea.

Event Flow

📱

1. Register

Quick QR code registration

💡

2. Ideate

Submit & vote on ideas

🤖

3. Match

AI forms balanced teams

🚀

4. Build

Collaborate on projects

Core Platform Features

01

Event Management

Platform concept for organizing AI development events

  • Schedule and manage AI Cook-Up events
  • Event status tracking (pending, active, completed)
  • Customizable voting periods for idea selection
  • Event-specific team size and configuration settings
  • Participant registration with QR code support
02

Intelligent Team Matching

LLM-powered team formation based on skills and preferences

  • Multi-dimensional matching: skills, AI experience, and interests
  • Player mode preferences: single or team participation
  • Expertise categorization: Design, Engineering, Business, Marketing, Sales
  • AI experience levels: Beginner to Expert classification
  • Dynamic late registration handling with smart team assignment
03

Idea Management & Voting

Democratic project selection through community voting

  • Participant-submitted project ideas with descriptions
  • Real-time voting system with live popularity tracking
  • Must-work-on preferences for passionate project leaders
  • Solo preference options for independent developers
  • Top ideas automatically selected for team formation

For Participants

  • •Quick registration process via QR code
  • •Submit ideas and vote on favorites
  • •Get matched with complementary teammates
  • •Join teams even as a late arrival

For Organizers

  • •Create and manage events easily
  • •Automated team formation at scale
  • •Real-time event monitoring
  • •Export team data for collaboration tools

Intelligent Team Matching System

The heart of The AI Cook-Up is its sophisticated team matching algorithm that ensures balanced, productive teams while respecting participant preferences.

Team Formation Flow

Complete flow from registration through team assignment, including handling of late arrivals

Matching Criteria

Skill Diversity

Each team gets a balanced mix of designers, engineers, business strategists, and marketers

Experience Balance

Teams include members from beginner to expert levels to foster learning and mentorship

Interest Alignment

Participants are matched to ideas they voted for whenever possible

Technical Implementation

01

LLM-Powered Team Logic

Advanced AI algorithms for optimal team composition

  • Structured prompt engineering for team formation constraints
  • JSON-based team assignment output for automated processing
  • Skill balance optimization across all teams
  • Respect for must-work-on and solo preferences
  • Conflict resolution for overlapping constraints
02

Real-time Processing

Efficient system for immediate team assignments

  • Instant team formation after voting period ends
  • Dynamic recommendation engine for late arrivals
  • Live updates to team compositions
  • Automated notification system for team members
  • Seamless integration with collaboration tools
03

Data-Driven Insights

Analytics and optimization for better events

  • Participant skill distribution analysis
  • Popular idea trend tracking across events
  • Team performance metrics and feedback
  • AI experience level progression tracking
  • Event success rate optimization

Platform Statistics

Teams/Event
6-8
Target group count
Members/Team
~5
Target team size
Commits
15
Prototype development
Lines of Code
~4K
Concept implementation

User Experience Focus

Every aspect of The AI Cook-Up is designed for minimal friction and maximum engagement. From the QR code registration to the final team assignments, the platform ensures a smooth, intuitive experience for all participants.

Mobile-First Design

Optimized for smartphones since most users register via QR code

Real-time Updates

Live voting counts and instant team assignments keep engagement high

Vision

Concept Goals

The AI Cook-Up is a concept site exploring how to foster Houston's AI community through organized events with LLM-powered team formation. Built as a prototype to validate the idea.

  • •Cross-disciplinary collaboration through skill-balanced teams
  • •LLM-powered team matching based on skills and preferences
  • •Democratic project selection through community voting
Next inspection step

Inspect the system further

Use the live surface or the source as the next level of proof. The goal here is not to end on a marketing flourish, but to make the next inspection step obvious.

Read the source
Source
https://github.com/hopeatina/theaicookup
Why this matters
Strong systems work should be inspectable from multiple angles: interface, architecture, and implementation.