Sure, I think the article is basically correct, as things stand right now ... but the problem is that that wipes out software development as a career: software becomes just a tool that domain experts can spin up to make their jobs easier.
> Fifty-four tightly clustered, slanted oil wells — the last of the Salt Lake Oil Field — sit snuggly between Macy’s, Bloomingdale’s and San Vicente Boulevard. In fact, the Beverly Center’s odd, curved footprint is designed to accommodate the drilling site, which is hidden by a wall along the street. The wells are almost completely invisible, dwarfed by the mammoth mall and the sprawling Cedars-Sinai Medical Center across the street — the hospital where I was born and where I later dropped my friend off to meet his wife for an ultrasound appointment.
This is all very right, but I'd like to add this: As your capacity to deal with abstraction (which is a function of intelligence and executive function and, to some extent, knowledge) grows, you become more and more constrained by the extent to which you can manipulate symbols. AI-based solutions for that are potentially really powerful, and that's the mechanism through which, as TFA says, "intelligent, educated people with working reward circuitry stand to gain more from AI."
And I'd also add that AI strongly disaggregates the returns to different levels of the capability to deal with abstraction -- higher levels get more, lower levels get less -- rather than uniformly boosting returns across the board (unfortunately). Of course, this has been the trend of information technology since at least the '80s, but now the slice at the top is really small and the returns very high.
Yeah, I think that's a good one, as would be e.g. Guards! Guards!
No idea why the recommendation in that link is Sourcery -- it's not bad, but it has that early Discworld flavor that's really just an extended riff on late '80s / early '90s fantasy and probably wouldn't land with a modern audience.
> Barnum’s first rule: pick the work you’re built for, then aim to be the best at it.
Edsger Dijkstra, in one of his letters, giving advice (IIRC) to a PhD student: "Do only what only you can do."
Kind of funny to see one of the greatest computer scientists and one of the greatest public entertainers giving the same advice, but I guess that speaks strongly in its favor.
I've come to learn that "do only what only you can do" is not great advice at all. It's leagues better to be the 10,000th-best SWE at Meta than the world's best basketweaver. Often doing something super unique is an excuse for shying away from mainstream competition.
Focusing on the best of anything is usually misleading.
The deep end of anything almost always has some positives attached to it. The best basketball players make a ton of money. That doesn’t make it a good career option.
For more obscure activities it takes an unreal amount of effort and sacrifice to get near the deep end of the pool. I grew up knowing a lot of people who were the best of the best at their sports and poured their life into it, but none of them ended up making it professionally or getting into the Olympics despite a lot of trying.
For a hobby or sport it’s more enjoyable if you’re not trying to turn it into something more. Leave it as a relaxing thing you do on the side.
1. The 2nd-best basketweaver will die in obscurity.
2. The MacArthur Grant, while obviously greatly commendable as an achievement, is monetarily worth less than what the 10,000th Meta engineer makes in one or two years.
I once had a talk with one of (the?) world's best bonsai gardener in Edogawa, Tokyo. Trees cut by him are worth millions and he has pictures of himself with FANG leaders. This guy wakes up every morning at 5 and works until it's dark outside even though he clearly does not need to work for money, but because he loves it.
I think some people just aren't wired to love doing something over and over, especially something so monotonous. Basket weaving or bonsai gardening is much more monotonous than solving difficult crimes or difficult science problems or difficult tech problems. There are people who absolutely love solving difficult problems but get tired of it after a few years and switch to another field. For those people doing weaving or gardening would get boring very quickly. I think it may come to whether people like the idea of things or the things themselves. If I was a basket weaver, I'd quickly realize there aren't that many groundbreaking weaving ideas I'll have in my lifetime, that most baskets are very similar in how they're made. I'll say to myself "I could make these 50 amazing baskets but they'll all fall under these 5 types of baskets with these 10 skills required to make them. So why do it if I can imagine doing it and if I know I'll be able to do it?". I may even envision a mega basket that incorporates every trick in the trade, like a skyscraper compared to a hut. I'll know that I'm capable of making it. That will satisfy my love for the idea of baskets but if I don't love the thing itself, why do it at all? The idea is 90% of the mega basket. The execution could be automated in a few years, why bother doing it for 5000 hours?
I think you underestimate just how competitive obscure fields and crafts can be. The world's second-best basketweaver is likely to be painfully aware of their superior rival, and push themselves hard to catch up and surpass them.
What you're really arguing is that SWEs are superior to basketweavers. But I wouldn't be so sure. That basket might well be around and admired long after the software's obsolete and gone.
I have to strongly disagree with this one. People should strive to do hard things, solve uniquely hard problems. SWE is not hard or particularly unique.
What? I would much rather be the world's best basketweaver than the 10,000th best SWE at Meta. Are you sure you aren't projecting your biases on what you think is more fulfilling?
I could never do anything, I could talk fancy and bullshit and could come up with all kinds of great ideas as an ideas guy.
Nothing useful.
So I became a developer and data engineer, and I became really good at it even though, like the protagonist in Gattica (with whom I share other similarities), I had to work twice as hard and spend all my off hours obsessed with it because my nature worked against me.
While others with this natural prediliction could spend all their time in type 1 thinking I had to live in type 2.
But it was a success, and I found myself becoming an executive at long last on the strength of my technical abilities, and it turns out executives don't actually need to do much of anything and really, outside of maybe some complex CFO roles, executive roles are by far the easiest roles at existing profitable companies. I suspect csuite positions are actually the roles most secretly replaced by Ai already.
> I could talk fancy and bullshit ... I became a developer and data engineer, and I became really good at it
That's a formidable combination.
> I found myself becoming an executive at long last on the strength of my technical abilities, and it turns out executives don't actually need to do much of anything and really ...
You probably think that because talking fancy and bullshitting come naturally to you.
This is also the kind of advice that only sounds good on paper. In reality there is no clear marker of what you can and cannot do well unless you empirically experiment with everything which would take several lifetimes.
Modern gurus like Cal Newport advise the opposite, and for good reason.
Newport's book on this topic is terribly underwhelming, and I say that as someone who has really enjoyed his other books, blog posts, and YouTube videos. Most of the anecdotes he gives to support his "Career Capital over Passion" have an ambiguous directionality of the causal arrow. For example, the fact that the happiest admin assistants have been at the job the longest does not mean that getting good at being an AA makes you happy with the work. There is an equally plausible explanation that enjoying the work of an AA makes one likely to stay in the job longer. Most of his examples in the book are like this.
The place where I think Newport flounders in this area is that, in order to get "So Good They Can't Ignore You", you actually have to be able to put in the time and effort to get good. And the vast majority of people do not possess the self-control and willpower to force themselves to do something they dislike to the level that is necessary to achieve said mastery.
What a good book! I was expecting some "follow your dreams and lean into the hustle" pablum, but no. He talks pretty frankly about how the pursuit of extreme wealth, (100s of millions) which he'd succeeded at, isn't worth it even then because a single-digit amount of millions is quite enough to enjoy life, but adds that he expects readers will ignore that part and attempt to get filthy rich anyway.
Also, he later became a poet (a very good one, too, if I remember right) and early on in his life tried to be a pop singer. Feels a bit like that whole multi-decade career as founder and owner of a massive publishing empire was an odd detour for him.
Very fascinating person, and the book's definitely worth reading.
That was the biggest surprise to me -- they are really, appreciably worse! Why?
One thing that comes to mind is that AI labs are increasingly specializing models for coding and, to a lesser degree, white-collar work in general (writing summaries, reports, etc.), and maybe that comes at the cost of other, unrelated capabilities.
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