Suppose I have the following scenario (real-world project, real ML pipeline scenario)

• I have separate projects for different steps (ETL, train, test, tensorrt conversion...). Every step has it's own git repository, docker image, branch etc
• For quite a long time all the steps were not functioning as parts of an automated pipeline. For example, collaborative experimentation (training and validation steps). We were just focusing on reproducibility/versioning etc
• After some time, we decided to chain up everything to a single DAG to make a CI/CD and automate everything. For each step there is still a base task which I want to clone and modify every time the pipeline is launched
• Each individual step still resides in it's own project, and I want all the pipeline-initiated tasks to still reside in their respective projects