Social Media

AfghanX

FlutterFlow Social Media Application

Preview coming soon

Overview

AfghanX combines social networking, a job board, and a marketplace in a single FlutterFlow application. Users engage through reels, posts, and communities, while also being able to discover jobs, buy and sell products, and chat in real time.

The Challenge

Bringing four distinct product surfaces — social feed, communities, jobs, and marketplace — into one app meant the Firebase data architecture had to stay clean and query-efficient even as collections for posts, listings, chats, and profiles grew independently.

My Role

I managed application development in FlutterFlow along with the Firebase database architecture, designing the Firestore data model that the feed, marketplace, jobs, and chat modules all read from.

Technical Approach

Designed a Firestore schema that keeps posts, reels, marketplace listings, and job posts in separate, independently scalable collections linked by user references.
Built the social core — posts, reels, likes, comments, and communities — with FlutterFlow's custom logic layered on top for feed ranking and engagement actions.
Implemented real-time chat using Firestore listeners so conversations update instantly without manual refresh.
Added a marketplace module for listing, browsing, and messaging about products, and a job board where users can post and apply to openings.
Optimized Firestore reads with targeted queries and pagination to keep the feed and marketplace performant as content volume increases.

Technical Challenges & Solutions

A single flat data model would have made feed queries slow as reels, posts, jobs, and listings all grew in the same space.

Solution — Split content types into dedicated Firestore collections with denormalized user fields, avoiding expensive joins on every feed load.

Real-time chat and social interactions both compete for Firestore read/write budget at scale.

Solution — Scoped chat listeners to active conversations only and used pagination on feeds so the app doesn't subscribe to more data than the current screen needs.

Technical Architecture

Built in FlutterFlow on a Firestore schema that keeps posts, reels, marketplace listings, and job posts in independently scalable collections linked by denormalized user references, avoiding expensive joins on feed loads. Real-time chat listeners are scoped to active conversations only, and feeds and marketplace queries are paginated to control Firestore read volume at scale.

Outcome

Delivered a production FlutterFlow application spanning social, marketplace, and job-board functionality on a Firebase backend architected to support real-time interaction across all four modules.