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A fun one I recently encountered: I was asked to estimate the number of story points a ticket would take, using "1 story point equals 1 day of work, so if e.g. you need 7 days of work, that would be 7 story points".

Not sure what the benefit of the jargon is here.


"Story" framing allow you select between fiction, non-fiction, drama, horror, comedy, fantasy, etc.

"Enshittification" caught on, but also sounds like it just means "turned to shit" (rather than: companies run at a loss to capture the market with a good product, then once they do, turn the product to shit to extract as much money as possible, since customers can no longer leave).

Surprise surprise, people are using it to mean the former.


Enshittification doesn't seem to capture the malice involved in this process. Manipulation for profit. Pretending to be virtuous to gain trust. An abuser grooming their victim by slowly ratcheting up the abuse and control.

It's more like emprisonification.


Hmm, not sure I agree it ever only meant "running at a loss to capture the market" - even after having gone back and re-read Doctorow's early postings. It's certainly a common way for the situation to start (getting a large mass of users to abuse is a difficult task), but it's never specified as the only way. I could be very wrong of course, but if so I must have missed some very explicit language in the early coinage.

The original post https://pluralistic.net/2022/11/28/enshittification/ about it makes no mentions of running at a loss, just what happens when a two-sided platform gains a bunch of users.

Later in "The ‘Enshittification’ of TikTok" https://www.wired.com/story/tiktok-platforms-cory-doctorow/ Doctorow does explicitly mention Amazon operated as a loss leader to gain it's initial users but when they get around to the subject of the article (TikTok) it's explicitly noted it was the recommendation system which grew the early audience in that case:

> Which brings me to TikTok. TikTok is many different things, including “a free Adobe Premiere for teenagers that live on their phones.” But what made it such a success early on was the power of its recommendation system. From the start, TikTok was really, really good at recommending things to its users. Eerily good.

> By making good-faith recommendations of things it thought its users would like, TikTok built a mass audience, larger than many thought possible, given the death grip of its competitors, like YouTube and Instagram. Now that TikTok has the audience, it is consolidating its gains and seeking to lure away the media companies and creators who are still stubbornly attached to YouTube and Insta.

And, in the very same piece, Doctorow had opened up with this generic definition of enshittification which aligns with the original:

> Here is how platforms die: first, they are good to their users; then they abuse their users to make things better for their business customers; finally, they abuse those business customers to claw back all the value for themselves. Then, they die. I call this enshittification, and it is a seemingly inevitable consequence arising from the combination of the ease of changing how a platform allocates value, combined with the nature of a "two-sided market", where a platform sits between buyers and sellers, hold each hostage to the other, raking off an ever-larger share of the value that passes between them.


No that's fair, I was wondering whether to look up a fully accurate definition (ironically), but figured it didn't really matter for the point that people use it to mean what it sounds like, instead of what it was defined like. And I just didn't feel like making the effort

I think that that's the Deep Web.

IIRC, the goal was for Fluent to have a convertor or something to be able to work with MessageFormat 2.0, but I don't quite remember where I heard that. My approach has just been to stick to Fluent for now.

Yeah it's actually MessageFormat 2 [1] that's very informed by Fluent's design I believe; I think that comparison is to "normal" MessageFormat.

[1] https://messageformat.unicode.org/


Correct. MF2.0 addresses all the challenges we identified during design of Fluent.

Yes, Fluent informed much of the design of MessageFormat. See this FOSDEM talk: https://archive.fosdem.org/2023/schedule/event/mozilla_intme...

This post shows a lot of the challenges with localisation, that many seemingly simple tools don't have an answer to: https://hacks.mozilla.org/2019/04/fluent-1-0-a-localization-...

(Fluent informed much of the design of MessageFormat 2.)


Indeed, if only it were as simple as “{n} rows”.

I18n / l10n is full of things like this, important details that couldn’t be more boring or fiddly to implement.


Which is why Windows UI is littered with language like "number of rows: {n}".

Makes it easier to parse by automatic tools too

> Indeed, if only it were as simple as “{n} rows”.

How long till we just have a LLM do it on the fly?


There's plenty of difference within English accents as well. I'll generally classify any of them as English, I think.

That said, when I use the term British accent, I do usually mean English, I think. Sorry. Also sorry for all the times I used England when I meant UK, or UK when I meant Great Britain, or vice versa.



As a software engineer who's had to interact with Discord only a handful of times, I had no idea when other people could hear me or where I had to click to find people I was looking for.

I've only rarely used it for voice, so I think I'm not in the right demographic. But I find its text/chat UI janky as hell.

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