Yeah, that's a very good metric to look for. In the software space, one of the coolest things and a clear signal that "AI coding" is here was watching Aider's graph of "amount of code aider wrote itself in each PR" and seeing that number go up.
On the robot side, there are many things that have to go right. Hardware needs to become good enough, reliable enough and cheap enough to scale. Then you have the software stack on top that needs to scale in training, fine-tuning, control and generalisation. None of these are "easy" even in a lab setting. Doing it at scale, in production will be huge. And then there's data collection, where whoever does it better will probably win. Collecting data in peoples houses is problematic, but on the factory floor should be ok.
ATM my bet is on Tesla being the best positioned to best deliver (eventually). They have plenty of experience on all fronts, and more importantly they have ample places to test them. Their factories are as automated as possible, so it's safe to say that every human being still doing manual labor is critical in their role. As soon as they can replace some of them with humanoids, and see the "task success" number go up, they can scale it up all over their floors. And we know they can scale.
I used to think that generalist humanoid robots are still 10y out, due to hardware and generalist software stacks, but it seems like things are heating up. It's gonna be an interesting next decade.