For me this feels irrelevant. These tools are marketed for developers for their day-to-day jobs that involve building products. Devs don't look up information on people or build some complex mathematical things daily. They build things that consist of different parts, which in turn can consist of different contexts and can be a combination of other things as well. It can be a straightforward approach or it can be a legacy codebase that also need to incorporate new features with new stacks. The real test is in the real world scenarios. But every time it's about a narrowly scoped thing, the tests, the marketing. And they try to build an image that the combination of these scoped tasks can somehow bring you the ability to build at large scale. They don't say it, but they implicitly mean it with the way they present all this. Computers can compute, they can detect patterns and do analytics part, they can build assumptions based on the data they have. But they need the data, they need parameters, they need not only an operator, they need the source for the material they base their computations and output on. And somehow all the marketing completely ignores this fact. And this is damaging.