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Big Tech joins the race to build the world’s heaviest airplane
I'm at the end of my tour for my new book, the international bestseller Enshittification. My last two stops are CCC in Hamburg, Dec 27-30 and the Tattered Cover in Denver (Jan 22). Hope to see you!
I have a weird fascination with early-stage Bill Gates, after his mother convinced a pal of hers – chairman of IBM's board of directors – to give her son the contract to provide the operating system for the new IBM PC. Gates and his pal Paul Allen tricked another programmer into selling them the rights to DOS, which they sold to IBM, setting Microsoft on the path to be one of the most profitable businesses in human history.
IBM could have made its own OS, of course. They were just afraid to, because they'd just narrowly squeaked out of a 12-year antitrust war with the Department of Justice (evocatively memorialized as "Antitrust's Vietnam"):
The US government traumatized IBM so badly that they turned over their crown jewels to these two prep-school kids, who scammed a pal out of his operating system for $50k and made billions from it. Despite owing his business to IBM (or perhaps because of this fact), Gates routinely mocked IBM as a lumbering dinosaur that was headed for history's scrapheap. He was particularly scornful of IBM's software development methodology, which, to be fair, was pretty terrible: IBM paid programmers by the line of code. Gates called this "the race to build the world's heaviest airplane."
After all, judging software by lines of code is a terrible idea. To the extent that "number of lines of code" has any correlation with software quality, reliability or performance, it has a negative correlation. While it's certainly possible to write software with too few lines of code (e.g. when instructions are stacked on a single line, obfuscating its functionality and making it hard to maintain), it's far more common for programmers to use too many steps to solve a problem. The ideal software is just right: verbose enough to be legible to future maintainers, streamlined enough to omit redundancies.
This is broadly true of many products, and not just airplanes. Office memos should be long enough to be clear, but no longer. Home insulation should be sufficient to maintain the internal temperature, but no more.
Ironically, enterprise tech companies' bread and butter is selling exactly this kind of qualitative measurements for bosses who want an easy, numeric way to decide which of their workers to fire, and leading the pack is Microsoft, whose flagship Office365 lets bosses assess their workers' performance on meaningless metrics like how many words they type, ranking each worker against other workers within the division, with rival divisions and within rival firms. Yes, Microsoft actually boasts to companies about the fact that if you use their products, they will gather sensitive data about how your workers perform individually and as a team, and share than information with your competitors!
But while tech companies employed programmers to develop this kind of bossware to be used on other companies' employees, they were loathe to apply them to their own workers. For one thing, it's just a very stupid way to manage a workforce, as Bill Gates himself would be the first to tell you (candidly, provided he wasn't trying to sell you an enterprise Office 365 license). For another, tech workers wouldn't stand for it. After all, these were the "princes of labor," each adding a million dollars or more to their boss's bottom line, and in such scarce supply that a coder could quit a job after the morning scrum and have a new one by the pre-dinner pickleball break:
Tech workers mistook the fear this dynamic instilled in their bosses for respect. They thought the reason their bosses gave them free massage therapists and kombucha on tap and a gourmet cafeteria was that their bosses liked them. After all, these bosses were all techies. A coder wasn't a worker, they were a temporarily embarrassed founder. That's why Zuck and Sergey tuned into those engineering town hall meetings and tolerated being pelted with impertinent questions about the company's technology and business strategy.
Actually, tech bosses didn't like tech workers. They didn't see them as peers. They saw them workers. Problem workers, at that. Problems to be solved.
And wouldn't you know it, supply caught up with demand and tech companies instituted a program of mass layoffs. When Google laid off 12,000 workers (just before a $80b stock buyback that would have paid their wages for 27 years), they calmed investors by claiming that they weren't doing this because business was bad – they were just correcting some pandemic-era overhiring. But Google didn't just fire junior programmers – they targeted some of their most senior (and thus mouthiest and highest-paid) techies for the chop.
Today, Sergey and Zuck no longer attend engineering meetings ("Not a good use of my time" -M. Zuckerberg). Tech workers are getting laid off at the rate of naughts. And none of these bastards can shut up about how many programmers they plan on replacing with AI:
And wouldn't you know it, the shitty monitoring and ranking technology that programmers made to be used on other workers is finally being used on them:
Naturally, the excuse is monitoring AI usage. Microsoft – along with all the other AI-peddling tech companies – keep claiming that their workers adore using AI to write software, but somehow, also have to monitor workers so they can figure out which ones to fire because they're not using AI enough:
This is the "shitty technology adoption curve" in action. When you have a terrible, destructive technology, you can't just deploy it on privileged people who get taken seriously in policy circles. You start with people at the bottom of the privilege gradient: prisoners, mental patients, asylum-seekers. Then, you work your way up the curve – kids, gig workers, blue collar workers, pink collar workers. Eventually, it comes for all of us:
As Ed Zitron writes, tech hasn't had a big, successful product (on the scale of, say, the browser or the smartphone) in more than a decade. Tech companies have seemingly run out of new trillion-dollar industries to spawn. Tech bosses are pulling out all the stops to make their companies seem as dynamic and profitable as they were in tech's heyday.
Firing workers and blaming it on AI lets tech bosses transform a story that would freak out investors ("Our business is flagging and we had to fire a bunch of valuable techies") into one that will shake loose fresh billions in capital ("Our AI product is so powerful it let us fire a zillion workers!").
And for tech bosses, mass layoffs offer another, critical advantage: pauperizing those princes of labor, so that they can shed their company gyms and luxury commuter busses, cut wages and benefits, and generally reset the working expectations of the tech workers who sit behind a keyboard to match the expectations of tech workers who assemble iPhones, drive delivery vans, and pack boxes in warehouses.
For tech workers who currently don't have a pee bottle or a suicide net at their job-site, it's long past time to get over this founder-in-waiting bullshit and get organized. Recognize that you're a worker, and that workers' only real source of power isn't ephemeral scarcity, it's durable solidarity:
https://techworkerscoalition.org/
If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
Do game developers list any hard rules for design to avoid glitches or technical issues? For example, if the trigger to activate a save point is 12 units around the point, any wall that the save point the save point has to be 13 units wide to avoid players touching it, or a fight cannot have more than 100 NPCs loaded at once as the engine pathfinding breaks and it cannot be fixed without causing worse issues?
Yes, we absolutely have these kind of established rules. We generally call these metrics and we try to establish them very carefully because they are the assumptions around which design can build levels, environments, combat, and other core gameplay. We often have to establish metrics for most core gameplay actions - how fast a player can run, how high/far a player can jump, how many party members a player can have, and so on. This also includes lots of other smaller details like the size of doors, the allowed angle ranges for stairs/slopes, the width and minimum heights of ladders, the minimum width of corridors, height for cover walls, heights for mantling/hopping over obstacles, maximum height a player can step up without getting stopped by the wall, etc. We use these limits to design our gameplay.
A large part of this is, as you alluded to, staying within our technical limitations. If we can't animate more than X characters on screen at once, then we can't have scenes with more than X characters in them. If we can't run more than Y particles in a frame, then we can't create scenes with more than Y particles running at the same time.
However, there are also user experience and design considerations for this. Imagine that the farthest range the player can jump is 15 feet after a full sprint. Any gap in the game that is 15 feet or less is jumpable. Any gap that is more than 15 feet is jumpable. Now imagine that some level designer sets a 15 foot + 1 inch gap. How frustrating do you think it would be to a player who tries to make that jump and fails because it isn't possible? How can we expect a player to evaluate whether that gap is jumpable if it looks so close to an actually jumpable gap? In order to reduce player frustration, we probably need to set up a metric for minimum un-jumpable gaps so that players can recognize them on sight so they don't have to try and fail at every gap that's pretty close to maximum length.
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Poetic Language is organized into rhythmical units which appear in print as lines.
In Europe, the traditional study of versification, or prosody, was based on the rules of Latin scansion.
Poetic lines would be analysed into combinations of stressed and unstressed syllables known as feet.
Five types were formerly prominent in English verse, as shown above.
Lines would then be classified in terms of the number of stressed syllables they contained, as shown above.
In theory, there is no limit; in practice, most English metrical lines are found to be 5 feet or less; when they exceed 6 feet, there is a strong intuitive tendency to break them into 2 parts.
Combinations of foot-type and line length produced such designations as iambic pentameter – the heartbeat of much English poetry – and analyses in these terms were the staple of traditional metrical studies, which traced the norms of English poetic rhythm and evaluated the way poets deviated from these norms.
As a system of description, it worked quite well in giving an account of the regular lines of traditional poetry.
But it came to be criticized on several counts:
It was often mechanically applied, with students being taught to identify the form of metrical patterns at the expense of their function, or role, in a poem.
It was unable to cope well with lines containing unusual rhythm sequences.
With the bulk of modern poetry no longer using such metrical patterns, but working instead with ‘free’ kinds of verse, the traditional system of description came to be viewed as largely irrelevant.
Today, metrists work in several alternative ways, not restricting themselves to the notion of stress, but bringing in other prosodic systems, such as tempo and intonation, and a general concept of rhythmical weight.