Have you ever wondered what it’s like to take a simple frontend app and transform it into a full-stack powerhouse? In this blog post, I’ll share the journey of converting the MoodFlip app from a basic frontend application to a full-fledged full-stack solution. Whether you’re into watching the journey unfold on video or prefer a written guide, I’ve got you covered. You can also check out the accompanying video here: Transforming MoodFlip: A Full-Stack Journey with AI.
MoodFlip App: The Starting Point
In the previous iteration of the MoodFlip app, we had successfully integrated some AI capabilities by using GitHub Codespaces and OpenRouter API. However, we soon discovered two significant issues:
- The API key was exposed in the frontend code, a major security concern.
- The app relied on local storage to manage flip history, which limited persistence and flexibility.
Our goal in this journey was to solve these problems and make the MoodFlip app not only secure but also scalable with a proper backend setup. This involved transforming it from a frontend-only application to a full-stack one, implementing database support, and tackling real-world challenges with AI development tools.
Tools of the Trade
To make this transformation possible, we relied on some powerful tools, including:
- GitHub Codespaces for a smooth cloud-based development environment.
- Aider 0.60 along with Claude 3.5 Sonnet to assist with coding tasks and development challenges.
- SvelteKit for adding full-stack capabilities and backend functionality.
- Neon PostgreSQL to replace SQLite and provide proper serverless database support.
This combination of technologies allowed us to take MoodFlip to the next level while also experimenting with AI-supported coding techniques. While AI tools helped automate much of the code generation, there were moments when human intervention was required to correct the course—a real example of human-AI collaboration.
Key Challenges and Solutions
- API Key Security: One of the first things we tackled was the exposure of our API key in the frontend code. We moved it to a secure environment variable on the backend using SvelteKit, ensuring that it no longer appeared in the client-side code.
- Frontend to Full Stack Migration: Migrating the app to a full-stack architecture involved setting up SvelteKit and adding backend functionality. AI tools like Aider were helpful, but they also made mistakes, particularly with understanding the existing project setup. At times, Aider suggested incorrect steps—such as recreating a new SvelteKit project instead of integrating with the existing one—which led us to cancel and adjust these instructions manually. Learning when to step in and how to guide AI tools was a key part of the journey.
- Database Migration: Initially, MoodFlip used SQLite for local storage, which is not ideal for serverless environments. We migrated to Neon PostgreSQL, which provided a more scalable and serverless-friendly backend solution. The migration wasn’t without hiccups, especially when configuring it to work within the Netlify deployment context. But with troubleshooting and reconfiguring environment variables, we made it work.
- Deployment on Netlify: With the backend in place, our deployment strategy also had to change. Initially, our configuration was incompatible with Netlify’s serverless environment, particularly because of its lack of persistent file-based storage. We configured the project to work with Netlify by using the appropriate SvelteKit adapter for Netlify, and after some tweaks to the environment variables, we were able to successfully deploy the full-stack version of MoodFlip.
Lessons Learned
- AI as a Development Partner: AI tools like Aider are fantastic development partners but not infallible. When the AI generated incorrect code or misinterpreted the context, stepping in to provide the right prompt or cancel and redo actions was essential.
- Serverless Considerations: Moving from local storage to a cloud database like Neon meant that we had to think about persistence, scalability, and how to manage data securely across serverless environments. It was a great learning experience to understand the practicalities of serverless functions and the role of environment variables in a secure deployment.
- Hands-On Debugging: The deployment process, especially working with Netlify, required a lot of hands-on debugging and iterative adjustments—an area where the combination of human experience and AI-assisted coding really shone.
Watch the Journey
For those interested in seeing the nitty-gritty details and real-time problem-solving, you can watch the full journey here: Transforming MoodFlip: A Full-Stack Journey with AI. The video includes step-by-step guidance, some troubleshooting moments, and how we collaborated with AI tools to make it all work.
What’s Next?
Moving forward, we’ll be working on adding user authentication and making the application more robust, including comprehensive testing. If you want to continue the journey with us and learn more about using AI tools for development, stay tuned for future videos and posts.
Feel free to like, subscribe, and follow along for more AI-driven development adventures. Let’s keep coding, keep learning, and make the impossible possible!