This is a submission for the Amazon Q Developer "Quack The Code" Challenge: Exploring the Possibilities
🧠 What I Built
I built AI Medicine Analyzer — a web app that simplifies how people understand their medications by letting them ask natural-language questions and get instant AI-powered answers.
This project represents an unexpected and innovative use of Amazon Q Developer. While Amazon Q is typically used for improving productivity during development, I used it to rapidly ideate, build, and enhance an AI-powered health tech tool. It’s a practical healthcare utility powered by modern web tech and LLMs, demonstrating that Amazon Q can be a catalyst for meaningful, real-world innovation — even in domains like digital medicine and patient education.
🎥 Demo
You can search any medicine name (e.g., "Paracetamol"), and the app will fetch structured data and allow follow-up questions like:
- “What are the side effects?”
- “Is it safe for pregnant women?”
- “Can it be taken with Ibuprofen?”
Here are the screenshots of the chat interface:
💻 Code Repository
The app is built with:
- React + Vite
- Framer Motion
- Tailwind CSS
- Google’s Generative AI API
- Amazon Q Developer (CLI & VS Code Extension)
⚙️ How I Used Amazon Q Developer
I used the Amazon Q Developer VS Code extension extensively throughout development. Here's how it helped at every stage:
🚀 Rapid Component Generation
Amazon Q helped scaffold my React app components quickly — from form UIs to API wrappers. This saved a lot of boilerplate time and let me focus on core functionality.
💡 Tip: When generating boilerplate or reusable code, be specific with your prompt. For example:
"Create a React component with a Tailwind-styled search bar and result list."
🧠 Real-time Debugging and Optimization
I leveraged Q to inspect confusing bugs, async issues, and even logic errors in the quiz module. It understood my code context inside VS Code and guided me to the fix instantly.
💡 Tip: Use inline Q chat on specific functions or files — it's smarter than just copy-pasting errors.
✨ Code Refactoring & Enhancements
Amazon Q suggested optimized implementations for custom hooks, modularized my data-fetching logic, and offered more performant code patterns — helping me clean up spaghetti code.
💡 Tip: Ask Q to refactor messy code blocks. Example:
"Refactor this useEffect with better async pattern and error handling."
📘 Learning Use Case
Amazon Q felt like pairing with a senior developer. I asked it UX-related questions too — like improving the quiz result interface — and it gave both logic suggestions and UI advice.
💡 Tip: Don’t limit Q to “just code” — use it to ask architectural, UX, or even API strategy questions.
🛠️ CLI + IDE Combo Power
I also tried the Amazon Q CLI in terminal for exploring available commands and streamlining workflows. It was handy when working outside the IDE or reviewing repo history.
🎯 What's Next & Final Thoughts
Working on this project with Amazon Q Developer has been a super productive and genuinely fun experience. It felt like having an AI pair programmer who understands not only your code but also your intent.
I'm excited to take AI Medicine Analyzer to the next level by expanding it into:
- Prescription image analysis
- X-ray and radiology image understanding
- Plant disease identification using image input
- And even more domain-specific AI models
This challenge was more than just a submission — it sparked a product vision I genuinely want to build out further.
👥 Team
This was a solo submission by me, @sumitkcs.
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