Certainly. In one of my recent projects, I worked on developing an AI-based image classification system using Python and TensorFlow. The project involved training a model to accurately classify images into different categories. To ensure scalability, I structured the code by modularizing it into distinct components: data preprocessing, model architecture, training, and evaluation. Each module was encapsulated in separate Python scripts, allowing for easy maintenance and updates. I used object-oriented principles to define classes for each component, which helped in reusability and scalability. Additionally, I employed version control with Git to manage changes and collaborated with team members to integrate the model into a larger application. This structured approach not only facilitated scalability but also ensured the project could be easily extended with additional features in the future.