During a focused month, Cuev worked on stabilizing the cuda_ping_pong workflow in the meta-pytorch/monarch repository by addressing dependency management challenges. They synchronized Tokio dependencies, updating from version 1.46.1 to 1.47.1, to ensure consistent runtime behavior across components and prevent compatibility issues in a high-performance benchmarking example. Using TOML for configuration and leveraging automated tooling like autocargo, Cuev validated the dependency changes to maintain a clean, reproducible build environment. This work reduced the risk of runtime mismatches in Tokio-dependent components, contributing to more reliable performance demonstrations and highlighting careful attention to system stability and build hygiene.