Llm labelling is so incredibly useful, as is transforming labelled data to other valid but different forms (like where you might train on sentences but also randomly replace days of the week with others).

You can also do stuff like setup active learning but have the labeller be an llm as well to make things more efficient.

Definitely worth it for PoC level things if not full ones.

Edit - also reviewing, so it can run training, test, review failure cases and investigate itself. You can leave them to plough through a few iterations where the early part is the classic time you’d have a few obviously bad sets of results.