Child's Play: Tech's new generation and the end of thinking

>The net result is a growing schism of resentment by those who do the work towards those who get the credit, glory, and reward, versus those who bask in stardom and truly believe they can replace the perceived entitlement of labor wholesale with an instant gratification machine and somehow survive the resulting societal collapse such a device would bring about.

Naturally, unmentioned are those shut out of reasonable opportunities for meaningful productivity, regardless of technical potential (but largely in line with (lack of) social capital). A few years of this maybe encourages an entrepreneurial spirit. Two decades is quite convincing that there's no place for them in the current order.

The upwardly-mobile opportunity hoarders need to understand, much as the wealth hoarders ought to, that the whole thing falls apart without buy-in from the "losers".

Tang ping bai lan.

For what it's worth, most of the pennies I've earned definitely came from my ability to think and communicate well.

I can't help but wonder whether the person who gave you advice "to think critically wasn't for [you]" didn't have YOUR best interests at heart, and/or wasn't a wise person.

I also worked jobs where I was actively discouraged to think critically. Those jobs made me itchy and I moved on. Every time I did it was one step back, three steps forward. My career has been a weird zigzag like that but trended up exponentially over 25 years.

We all have our anecdotes we can share. But ask yourself this: if you get better at making decisions and communicating with other people, who is that most likely to benefit?

the dot-con era

I think there has always been some truth to that, long before AI. Being driven to get up and just do the thing is the most important factor in getting things done. Expertise and competency are force multipliers, but you can pick those up along the way - I think people who prefer to front-load a lot of theory find this distasteful, sometimes even ego-threatening, but it's held true in my observations across my career.

Yes, sometimes people who barrel forward can create a mess, and there are places where careful deliberation and planning really pay off, but in most cases, my observation has been that the "do-ers" produce a lot of good work, letting the structure of the problem space reveal itself as they go along and adapting as needed, without getting hung up on academic purity or aesthetically perfect code; in contrast, some others can fall into pathological over-thinking and over-planning, slowing down the team with nitpicks that don't ultimately matter, demanding to know what your contingencies are for x y z and w without accepting "I'll figure it out when or if any of those actually happen" - meanwhile their own output is much slower, and while it may be more likely to work according to their own plan the first time without bugs, it wasn't worth the extra time compared to the first approach. It's premature optimization but applied to the whole development process instead of just a piece of code.

I think the over-thinkers are more prone to shun AI because they can't be sure that every line of code was done exactly how they would do it, and they see (perhaps an unwarranted) value in everything being structured according to a perfect human-approved plan and within their full understanding; I do plan out the important parts of my architecture to a degree before starting, and that's a large part of my job as a lead/architect, but overall I find the most value in the do-er approach I described, which AI is fantastic at helping iterate on. I don't feel like I'm committing some philosophical sin when it makes some module as a blackbox and it works without me carefully combing through it - the important part is that it works without blowing up resource usage and I can move on to the next thing.

The way the interviewed person described fast iteration with feedback has always been how I learned best - I had a lot of fun and foundational learning playing with the (then-brand-new) HTML5 stuff like making games on canvas elements and using 3D rendering libraries. And this results in a lot of learning by osmosis, and I can confirm that's also the case using AI to iterate on something you're unfamiliar with - shaders in my example very recently. Starting off with a fully working shader that did most of the cool things I wanted it to do, generated by a prompt, was super cool and motivating to me - and then as I iterated on it and incorporated different things into it, with or without the AI, I learned a lot about shaders.

Overall, I don't think the author's appraisal is entirely wrong, but the result isn't necessarily a bad thing - motivation to accomplish things has always been the most important factor, and now other factors are somewhat diminished while the motivation factor is amplified. Intelligence and expertise can't be discounted, but the important of front-loading them can easily be overstated.

Interesting to compare to 2008. At least here, I think we're building something? Whereas then, it was pure, unabashed, siphoning as much as possible out of the financial system from the average American into the pockets of a privileged, self-righteous few, followed by an immediate burning down and parachute out of the whole thing once the cracks started to form.