Creating the Music Discovery Map was not just about building an app—it was a journey of trial, error, and discovery. From experimenting with cutting-edge AI tools like Cursor to troubleshooting when things didn’t go as planned, the process offered valuable lessons about the intersection of technology and creativity.
In this blog post, I’ll take you behind the scenes of the development process, sharing how AI assisted (and occasionally stumbled), and how human intuition and iteration brought the Music Discovery Map to life.
What is the Music Discovery Map?
The Music Discovery Map is an interactive web application that invites users to explore the diverse world of music. With its intuitive design, users can:
Dive into global music genres by selecting regions on an interactive map.
Discover popular artists and songs unique to different areas of the world.
Gain insights into the cultural richness of music across continents.
The goal was to create a visually engaging and informative app that connects users to the global music landscape, making discovery fun and seamless.
Leveraging AI Tools in Development
Building the Music Discovery Map meant tackling a wide range of challenges, from designing the map interface to integrating music data. To streamline this process, I used Cursor, an AI-powered code editor that brought powerful tools to the table:
AI-Powered Autocomplete: Cursor’s predictive coding suggestions allowed me to quickly build the app’s core features without worrying about syntax errors or boilerplate code.
Multi-Line Code Edits: The tool could generate and edit blocks of code, saving time when working on repetitive elements like interactive regions on the map.
Natural Language Commands: Cursor let me describe what I wanted in plain English—like “add a responsive map element”—and it generated a starting point for my code.
Using these features, I was able to prototype the app quickly, focusing on the creative aspects while AI handled much of the heavy lifting. However, AI tools aren’t perfect, and this project was no exception.
The Refinement Process: When AI Needs Help
One thing I learned early in this project is that while AI tools like Cursor are powerful, they don’t always get everything right the first time. Here are some of the challenges I faced:
Ambiguity in Instructions: When I asked Cursor to create a dynamic, clickable map, the initial code didn’t fully align with my vision. For example, the map regions weren’t properly linked to the backend data, requiring manual adjustments.
Over-Simplified Solutions: Cursor occasionally generated basic solutions that worked in ideal scenarios but didn’t handle real-world complexities, like regions without music data.
Debugging AI-Generated Code: Some outputs contained minor errors or inefficiencies that weren’t immediately obvious but surfaced during testing.
These challenges emphasized that AI tools are great collaborators, but they still require human oversight and refinement. I often found myself iterating on the AI-generated code, using my understanding of the app’s needs to bridge the gap between Cursor’s output and the final product.
Iterative Development: Bringing the Map to Life
The development process followed an iterative approach, combining AI efficiency with human creativity:
Prototyping with Cursor: Cursor helped me quickly build a working prototype, generating code for the interactive map and integrating external music data sources.
Testing and Debugging: I rigorously tested every feature, ensuring the map was responsive and intuitive on both desktop and mobile devices.
Refining Code Outputs: When AI-generated code fell short, I stepped in to tweak and optimize it. This included improving performance, adding error handling, and ensuring a smooth user experience.
User Feedback Loop: Early testers provided invaluable insights, pointing out areas for improvement, like making genre labels clearer and optimizing loading times.
Each iteration brought the app closer to its final form, blending AI-powered efficiency with human problem-solving.
Lessons Learned
Building the Music Discovery Map taught me several key lessons about working with AI in app development:
AI Amplifies Productivity: Tools like Cursor drastically reduced the time needed for repetitive coding tasks, allowing me to focus on higher-level design and functionality.
Human Insight is Irreplaceable: While AI can generate code, it lacks the contextual understanding and creativity needed to create a truly polished product.
Iteration is Essential: Success doesn’t come on the first try. Refining AI outputs through testing and feedback is crucial to building something functional and impactful.
AI as a Collaborative Partner: Think of AI as a co-pilot—valuable for steering the project forward, but you’re still the one in control.
Conclusion
Developing the Music Discovery Map was a rewarding journey that demonstrated the transformative potential of AI tools like Cursor. The app showcases how creativity and technology can come together to build something that connects people across cultures through music.
This project also highlighted that while AI can accelerate development, it’s the iterative process and human creativity that ultimately bring a vision to life.
If you’re a developer curious about using AI tools in your projects, my advice is to embrace them as powerful collaborators. Be prepared to refine their outputs and trust your instincts as you navigate the challenges of turning an idea into reality.
Have you used AI tools in your development journey? I’d love to hear your thoughts and experiences in the comments below!