Fair enough. But there needs to be evidence that this stuff actually works. I'm reminded of the fact that Richard Feynman didn't have a high enough IQ to get into Mensa.
https://www.gwern.net/docs/www/www1.udel.edu/63a495ef6b79bb4...
Why g Matters: The Complexity of Everyday Life
Personnel selection research provides much evidence that intelligence (g) is an important predictor of performance in training and on the job, especially in higher level work. This article provides evidence that g has pervasive utility in work settings because it is essen- tially the ability to deal with cognitive complexity, in particular, with complex information processing. The more complex a work task, the greater the advantages that higher g confers in performing it well. Everyday tasks, like job duties, also differ in their level of complexity. The importance of intelligence therefore differs systematically across differ- ent arenas of social life as well as economic endeavor. Data from the National Adult Literacy Survey are used to show how higher levels of cognitive ability systematically improve individuals’ odds of dealing successfully with the ordinary demands of modem life (such as banking, using maps and transportation schedules, reading and understanding forms, interpreting news articles). These and other data are summarized to illustrate how the advantages of higher g, even when they are small, cumulate to affect the overall life chances of individuals at different ranges of the IQ bell curve. The article concludes by suggesting ways to reduce the risks for low-IQ individuals of being left behind by an increasingly complex postindustrial economy.
> For several decades, the question of whether measures of specific cognitive ability contributed anything meaningful to the prediction of performance on the job or performance in training once measures of general mental ability were taken into account appeared to be settled, and a consensus developed that there was little value in using specific ability measures in contexts where more general measures were available. It now appears that this consensus was premature, and that measures of specific abilities can make important contributions even if general measures are taken into account.
[1] http://bactra.org/weblog/523.html
[2] https://humanvarieties.org/2013/04/03/is-psychometric-g-a-my...
And then it goes on to conclude that "If the goal is to do a good job in prediction... it makes sense to use the most general measures available" and "If predictive efficiency is the goal, it will be hard to consistently beat g."
It's an opinion piece arguing that, because the concept of g provides no mechanistic insight into how people solve problems, studies that seek to explain how problems get solved (as opposed to whether problems will get solved) should try to explain that process in terms of factors at the second-highest level of abstraction, rather than the highest level.
It is not in short supply.
But if you're looking for a brief overview, you could read https://www.amazon.com/dp/1444791877/