Graph Neural Networks (GNNs) excel at modeling complex data but do require feature engineering. This article shows how integrating getML's FastProp automates this process, boosting accuracy to 92.5% on the CORA dataset—surpassing the 90.16% benchmark. This approach simplifies implementation, reduces manual effort, and ensures consistent performance across a wide range of neural architectures, making it a valuable tool for data scientists for building consistent and high-performing models with minimal effort.