You are tasked with developing machine learning (ML) models using Google's AI Platform to perform image segmentation on CT scans. Your workflow involves frequently updating your model architectures based on the latest research and rerunning training to benchmark performance on a consistent dataset. Given the need to minimize computation costs and reduce manual intervention while maintaining robust version control for your code, what approach should you take?