Bijan Haney focused on enhancing the robustness of machine learning model serving in the viamrobotics/viam-cpp-sdk repository by addressing input tensor validation within the MLModelService. Using C++ and gRPC, he refactored the validation logic to distinguish between single-tensor and multi-tensor scenarios, ensuring that input tensors are correctly identified and typed before model invocation. This update introduced clear error handling paths, reducing runtime failures caused by misconfigured inputs and improving the reliability of ML inference pipelines. The work demonstrated a thoughtful approach to error messaging and validation centralization, contributing to a more predictable and developer-friendly machine learning service interface.