AI-Powered Development Experiment

Just Spent: Cross-Platform Expense Tracker

An experimental project demonstrating AI-assisted development methodology and architectural validation.

This was an intentional experiment to explore AI-assisted development methodology for producing production-quality applications. My role was as system architect, technical specification author, and quality validator.

Just Spent is a voice-driven expense tracker developed using AI tools under my architectural direction. I designed the system architecture, created detailed technical specifications, established TDD validation workflows, and verified generated code against production quality standards through testing and code review.

What this demonstrates: My ability to architect multi-platform systems, write precise specifications, apply systematic validation, and guide AI-assisted implementation toward maintainable results.

Code
8,000+
Lines of Code
AI-assisted implementation
Tests
700+
Automated Tests
Unit and UI coverage
Apps
2
Platforms
iOS and Android
Docs
15+
Technical Specs
Architecture and test guides

Technical Highlights

Voice

Voice-First Architecture

Designed around natural expense entry, platform voice integrations, and fast logging flows for mobile users.

TDD

Test-Driven Validation

Used tests as the control system for AI-assisted implementation, regression checks, and behavior consistency.

CI

Automation Workflow

Created repeatable implementation, review, and verification loops so generated code could be evaluated reliably.

Quality

Production-Oriented Structure

Focused on offline behavior, multi-currency design, platform-native storage, and maintainable app architecture.

Technology Stack

iOS

Swift SwiftUI Core Data SiriKit XCTest

Android

Kotlin Jetpack Compose Room Assistant JUnit

Open Documentation & Implementation Guide

The repository is structured as a studyable system with architecture notes, testing guidance, and platform-specific implementation specs.

Explore the complete system architecture, browse the source code, and see how AI collaboration can support production-minded app development.