This is a strange question since augmentation can be objectively measured even as its utility is contextual. With MidJourney I do not feel augmented because while it makes pretty images, it does not make precisely the pretty images I want. I find this useless, but for the odd person who is satisfied only with looking at pretty pictures, it might be enough. Their ability to produce pretty pictures to satisfaction is thus augmented.
With GPT4 and Copilot, I am augmented in a speed instead of capabilities sense. The set of problems I can solve is not meaningfully enhanced, but my ability to close knowledge gaps is. While LLMs are limited in their global ability to help design, architect or structure the approach to a novel problem or its breakdown, they can tell local tricks and implementation approaches I do not know but can verify as correct. And even when wrong, I can often work out how to fix their approach (this is still a speed up since I likely would not have arrived at this solution concept on my own). This is a significant augmentation even if not to the level I'd like.
The reason capabilities are not much enhanced is to get the most out of LLMs, you need to be able to verify solutions due to their unreliability. If a solution contains concepts you do not know, the effort to gain the knowledge required to verify the approach (which the LLM itself can help with) needs to be manageable in reasonable time.