Auggie246 developed a startup preloading feature for the Blaizzy/mlx-vlm repository, focusing on accelerating server readiness and simplifying machine learning model management. By introducing command-line flags for model and adapter preloading, Auggie246 enabled the server to optionally load assets at startup, reducing initial load times and improving deployment predictability. The implementation leveraged Python and FastAPI, with careful attention to error handling to ensure robust operation in diverse environments. Documentation was updated to reflect these changes, supporting maintainability and ease of use. This work demonstrated depth in backend and API development, addressing operational efficiency for machine learning workloads in production settings.