My thinking is that companies are using AI LLMs for selection now. Maybe the goal is to eliminate bias but I suspect the opposite actually happens. The goal used to be compatibility more than capability and if AI now provides the filtering you get hyper compatibility selection. In order to achieve compatibility you need to develop in the dominant language, style, and platform of the employer which may not be stated in the job requirements and occur as near as possible in the center of a bell curve.
What that means practically is that bias is amplified. It used to be that having a blog and large portfolio demonstrated your experience, but that experience may be a weapon used to deselect you.
That imposes a challenge. If you cannot be selected for an interview then everything is irrelevant. Once you are selected for an interview these open proofs of experience are the tie breakers between candidates.
Where I have seen success lately has only occurred in these constraints:
* A given project has technical constraints, like a security clearance, that eliminates selection based upon culture compatibility. When this occurs then be awesome, not average.
In that above scenario I am getting offer letters two thirds of the time I get to the interview. Otherwise my failure rate is about 100% resulting in being dropped from consideration the moment they get your resume. If it felt like a game before job hunting is exclusively a game now.