In June 2025, Lycosospider developed a dynamic device selection feature for the bytedance/Dolphin repository, focusing on optimizing cross-platform model execution. Using Python, PyTorch, and deep learning techniques, they engineered a system that automatically selects between CPU and CUDA hardware, ensuring models run efficiently regardless of the underlying environment. The implementation included a robust fallback mechanism to CPU when CUDA is unavailable, preventing runtime crashes and improving deployment reliability. This work addressed compatibility challenges across diverse hardware setups, reduced maintenance overhead, and established a foundation for future hardware-aware optimizations, demonstrating thoughtful engineering depth within a focused, high-impact feature delivery.