Sprint Board Page
Settings Page
Team Chat Page
Overview/Dashboard
Documents Page
Video Meetings Page
Analytics Page
Sbmissona Evaluation Page
Github Repositrory Integration Page
AI Assiatance Page
Team Members Page
Task Page
Login/SignUp Page
Landing Home Page

Coders

Inspiration

During hackathons and team projects, we realized that the biggest problem is often not development itself, but coordination. Teams constantly switch between multiple platforms for tasks, communication, meetings, documentation, and GitHub tracking. This creates confusion, missed deadlines, and uneven workload distribution.

We wanted to build a single intelligent workspace that could help student teams execute projects more efficiently from idea to final submission.

What it does

Coders is an AI-powered execution workspace built specifically for student teams and hackathons.

It combines:

Task management
Sprint boards
Team chat
GitHub integration
Meetings
AI insights
Analytics
Submission management

into one centralized platform.

The AI assistant helps teams by suggesting task distribution, analyzing sprint risks, tracking GitHub activity, identifying bottlenecks, and improving collaboration in real time.

How we built it

We built Coders using:

MeDo for full-stack no-code development
Supabase for backend and database
GitHub integration for repository tracking
AI-powered workflows for analytics and task intelligence

Our focus was on building a clean, modern, and productivity-focused user experience optimized for fast-moving student teams.

Challenges we faced

One of the biggest challenges was designing a workflow where every feature connects naturally with the others. We wanted tasks, GitHub activity, analytics, AI suggestions, and notifications to work together as a unified execution system instead of isolated tools.

Another challenge was creating meaningful AI insights that actually help teams rather than generating generic recommendations.

We also worked on balancing simplicity with functionality so the platform feels powerful without becoming overwhelming.

What we learned

Through this project, we learned:

Workspace architecture and workflow design
Real-time collaboration concepts
Team productivity systems
AI-driven coordination logic
Full-stack platform integration using MeDo and Supabase

Most importantly, we learned that productivity tools become far more effective when they focus on execution and coordination instead of just task tracking.