I've always been of the view that for a workflow language, you should use a proper, turing-complete functional language which gives you all the usual flexiblity for transformations on intermediate data, while also supporting things like automatic parallelisation of things like external, compute-intensive tasks.

I recommend checking out https://github.com/peterkelly/rex and also my PhD thesis on the topic https://www.pmkelly.net/publications/thesis.pdf.

The gap in flexiblity between DAG-only and a full language designed for the task is a significant one.

I guess that ship has sailed and also it's maybe nitpicking but I find it a bit unfortunate to call a new programming language "Rex" when there's already "Rexx" for several decades.

redun is quite interesting in this regard

https://insitro.github.io/redun/

Do you implement a DAG within your system to act as a kind of well-defined backbone for analysis and execution, or do you dispense with (explicit) DAGs entirely?