This simply isn't true. Given that the whole promise of AI is accessibility, there isn't an obstacle being raised by other people adopting it faster. You can always pick up the latest trick quickly, and if you struggle at all, an LLM can explain. There is no evidence of people falling behind.
The idea that you need specialised knowledge to compete with the tool that is designed to let you do things without specialised knowledge is trivially nonsensical.
Admittedly part of the hype around AI is that you won't have to need to know what you're doing in order to use it. But there's a massive downside if you believe that and it turns out to be wrong.
As with any powerful but potentially-hazardous tool that is not perfectly reliable, I personally prefer to know what I'm doing and how the tool works. That's why I still have 10 fingers, 2 eyes, and a job.
I agree for every other tool, but AI's unique proposition--not part of the hype, the whole thing--is that it can do the thinking for you. If AI becomes what everyone claims, then you can't fall behind: you can always ask it to catch you up.
Everyone knows how to use AI; it's designed to be accessible. The people who think it's a special unique skill are the ones behind every vibe-coded disaster.
Don't people get better results by putting LLMs inside the right kind of loops and using the right kind of prompts? If I go to Claude and prompt "make me a website" it certainly doesn't produce as good of a result as other people with more sophisticated processes get.
I haven’t seen loops work for anything beyond simple tasks. And for complex tasks the loop itself is so complex half the time it would just fail and need you to intervene. Why would you go through all that effort of engineering a loop when a descriptive prompt followed by inspection is more than enough. It’s like idle hands looking for something to do.
And Claude or gpt can make websites just fine. So can the open weight models.