A Solid Guide to Structuring Your AI Project Directory

When you're building AI applications—whether it's a small model prototype or a production-level system—how you organize your files and directories can make or break your workflow. This guide provides a clear blueprint for structuring your AI project directory, covering everything from where to place data, models, configs, and utility scripts to how to handle training pipelines, experiments, and version control. Ideal for AI engineers who want cleaner, more collaborative, and production-ready codebases.