Claudeis surprisingly capable at handling graphics rendering pipelines, which is exactly how NeoBox ended up supporting a native Metal pipeline via libGeoLith. Most of the app is standard AppKit code I wrote by hand, but the low-level rendering stuff was a complete blind spot for me. Using AI to bridge that gap allowed me to move beyond a simple MAME frontend and actually implement something with better performance on macOS.
For anyone curious about the technical split in this project: Manual Code: The entire native macOS UI and the tedious process of ROM compatibility testing.AI-Assisted: The website and the integration of libGeoLith/Metal. Without an LLM, I would've been stuck in documentation hell trying to figure out the rendering pipeline.
The app currently lets you toggle between the GeoLith core or a self-managed MAME installation. It's basically designed for people who want an OpenEmu-style experience but specifically for SNK classics like Metal Slug or Art of Fighting.
If you're looking for a practical tutorial on how to integrate C++ libraries into a Swift/AppKit project using AI, this is a great real-world example of using an LLM agent to handle the "scary" math and graphics code while the human handles the architecture and UX.
`https://apps.apple.com/us/app/neobox-neo-geo-player/id6769912877`
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Claude's actually been a lifesaver for my Swift projects lately, saves so much boilerplate.
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