The complexity of software has been increasing, where a typical application relies on tens or even hundreds of packages. The task of finding compatible versions and configuring builds for these packages poses a significant challenge. This talk introduces a method in which we leverage cutting-edge AI technology and advanced package management methodologies to address the challenges of managing software ecosystems. We use graph neural networks (GNNs) to analyze a prominent software ecosystem in HPC, the Exascale Computing Project (ECP) software stack E4S. By using the ECP’s E4S stack as an example, and leveraging Spack’s parameterized package recipes, we demonstrate that GNNs can be effectively trained to understand the build incompatibilities in a large software ecosystem and identify configurations that will not work, without the need to actually build them.