I think maybe there's some nuance here to how to think about tooling. A data science team without any sort of data warehouse is probably going to be ineffective.

Maybe one way to think about it: some tools try to model and streamline the things you're already doing, and some tools expand the set of things you're able to do. I think the first type is the one to be more skeptical of. Face-to-face conversations, whiteboards, and Excel sheets are all extremely flexible and powerful. It's possible for tools to improve on these, but it's a high bar.