This perspective on human performance is super interesting!

Many of our stories about "genius," "superstars," and high performers are grounded in assuming that the patterns of early learning will extrapolate to the rest of life - e.g., child prodigies, gifted students, and those with early steep curves on the achievement trajectory. But what happens when you expand the window of observation?

This review challenges some of our long-standing myths about high performance. They suggest:

"The pattern of predictors that distinguishes among the highest levels of adult performance is different from the pattern of predictors of early performance. Higher early performance in a domain is associated with larger amounts of discipline-specific practice, smaller amounts of multidisciplinary practice, and faster early discipline-specific performance progress."

https://www.science.org/doi/10.1126/science.adt7790

I suspect there are downsides to early hyper-specialization that may not show up in human problem-solving until later; and this is the kind of pattern that really rocks the boat on many of our assumptions about what the best predictors for sustainable high performance really are.
More pointedly, should we be closing the door on the possibility of peak performance by the age of 8-9 across so many domains? Probably not!

Justice for multidisciplinary practice!

"By contrast, across high levels of adult performance, world-class performance in a domain is associated with smaller amounts of discipline-specific practice, larger amounts of early multidisciplinary practice, and more gradual early discipline-specific performance progress."

Parallels to my own developer science work:

- I have emphasizes that short-term payoffs can distract software teams from recognizing the long-term damage of cycles like learning debt, or engaging in contest cultures. Broadening the window of observation is crucial for seeing not just the "line go up" immediate response, but the "line crash down" that happens when your psychological environment is damaging

- human peak performance is probably a lot more diverse than we think, particularly for complex knowledge work. Generalizing from small and narrow measures mostly tested in early childhood/early learning (like cognitive tests) introduces a host of assumptions, and obscures our view of gradual, life-level learning!

- aptitude is not achievement! It's important to know that we can see lower levels of achievement associated with certain strategies at a certain point in time, but those same strategies will yield HIGHER achievement over time! There are many complex effects here, like protective effects from certain strategies that only come to light under challenge, or thresholds after which the longer-term strategies pay off more.

This is all part of the beautiful, incredibly complex science of achievement!

This kind of pattern also challenges long-standing myths about coder talent and what we think predicts what.

Should you always prioritize demonstration of early hyper-specialization when you're hiring programmers? If we overweight that at scale (which cultural beliefs about genius and ability are good at making us do!), we may be cutting ourselves off from the multidisciplinary problem-solving that our organizations will need to face complex challenges.

@grimalkina

Hey, I may name overweight, but that has nothing to do with me being hyper or being a bad programmer.

- bad early morning social media reading skills