What's the role of these tools? Can't a developer just write the code to get those data points?

At a first glance it seems like the hassle of integrating such a product into an existing ML codebase/pipeline is larger than solving the problem by hand.

What I mean is an annotation tool that interacts with the model itself in such a way that it will present to the user exactly those training examples next that will have the greatest impact in helping the model learn. So an annotation tool that provides a user interface for annotating data quickly (with keyboard shortcuts etc.). And looped into inference through the model to be trained, so you always get presented with the very training example that, out of the ones available, the model currently would be most unsure about.