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📰 AI-Powered News App — Project Story

💡 Inspiration

I’ve built a news app before, but it always felt incomplete. Users could read headlines, yet they still had to spend several minutes per article to understand what was going on. I wanted to take that idea a step further by integrating AI — not as a gimmick, but as a practical way to save time and reduce information overload.
The goal was simple: help users understand the news faster than traditional reading.

🛠️ How I Built It

I built an Android app that pulls real-time U.S. headlines from a live news API and displays them in a clean, swipeable interface. When a user taps on an article, the app sends the article content to an AI model, which returns a concise, neutral summary.

From a technical perspective, the project is structured using Clean Architecture:

• Presentation layer: Jetpack Compose UI + ViewModel (MVVM)
• Domain layer: Use cases that encapsulate business logic
• Data layer: Repositories, API services, and mappers
• Dependency Injection: Hilt for managing dependencies
• Networking: Retrofit for API calls

This architecture keeps the app modular, testable, and easy to extend with future features like sports, transit updates, or a personal assistant.

📚 What I Learned

• How to integrate AI APIs into a real-world mobile application
• How Clean Architecture helps isolate changes and reduce complexity
• Managing asynchronous data flows with coroutines and state
• Debugging dependency injection issues in a multi-layered setup
• Designing UI that emphasizes speed of understanding over content density

Conceptually, I also learned that AI is most valuable when it removes friction, not when it replaces core functionality.

⚠️ Challenges I Faced

• Dependency Injection errors: Hilt setup across modules required careful binding and visibility management
• API response modeling: Mapping nested JSON structures cleanly
• State management: Handling loading, error, and summary states without UI glitches
• Time pressure: Balancing clean architecture with hackathon-style iteration speed

One recurring challenge was deciding what not to over-engineer. Staying focused on the core user value — fast summaries — helped guide those decisions.

🚀 Outcome

The final result is an AI-powered news app that lets users scan key points in seconds instead of reading full articles, demonstrating how AI can meaningfully enhance an existing product rather than just being added for novelty.

This project represents both a technical step forward and a product-thinking evolution from my previous work.

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Built With

• jetpack
• kotlin