xstas1

That was the first such car. Even though the automatic transmission was invented a long time ago, new cars are still made with manual ones

XML??

Video in the terminal window of course

Can you put some of the text in a comment here?

I had never heard of the Playdate but it looks like a very interesting device... and... I want it? Would you suggest getting one?

How do you set it to search in Japanese language mode?

Kagi is good, but only for English language queries

It's just a fun reference to a song/psa ad called "Dumb Ways To Die"

I ran to the comments with this question

This markdown mirror is a partial solution to a problem that does not exist in "normal" Logseq (what's being rebranded to Logseq OG). The markdown files ARE the data (which syncs beautifully over Dropbox and the like.)

I am a Logseq user and I was under the impression that development had stalled or better, stabilized (frankly, most software does NOT need a constant stream of updates). Based on this post, it looks like they're back - and they've chugged some vibe juice.

Code is not spec. There is an implementation spectrum.

On one end, you have code that can perform only the behaviour explicitly declared in the spec, but has to be thrown away and rewritten for any new or updated spec.

On the other end, you have code that implements or anticipates a wide range of future possible specs including the given one.

The AI can operate on any point on this spectrum, but it's not very good at choosing. The more complex the software, the more such choices need to be made.

When the number of bad choices reaches a certain critical mass, even a skilled engineer becomes powerless to undo all the bad choices, and even a powerful model becomes unable to reduce it back to a coherent spec.

Turning you into a "reverse centaur" to borrow a term from Cory Doctorow

Sounds like a good system. To use the analogy from ths other comment, this would be like running an image through JPEG compression twice.

The issue happens then if you're updating the individual research files on a regular basis. (Or making a long series of commits on a starting code base.) Every edit has a chance of doing a drive-by cleanup on nearby lines. Over a long enough timeline, it'll ablate your logic into something featureless, like if you compress an image too many times.

I do remember early SourceForge. It remember it as very clean, simple and reliable, and popular.

Promotional pricing? Are they saying that after the promotion, it will cost more than 7.5x??

Also coding agents will happily compile android applications (of maximum complexity) via Github Actions where you can just pick them up with Obtainium. No PC needed

you already could! just install Termux, npm install your favourite agent harness (pi for one has explicit Termux support, but its AGENTS.md works just fine with Claude Code for example - https://github.com/badlogic/pi-mono/blob/main/packages/codin...), and say you want an android app. It problem solves for a bit, then spits out an apk out to your Downloads folder.

I just run claude code on my phone, in termux

Hypothesis: it's a sprawling, labyrinthine mess because it was grown at high speed using Claude Code.

Partway through, I recognized the function calling syntax as similar to Nix which I just started learning.

Turns out the implementation of the article is in Haskell, another declarative language.

At work. we use Power Query with it's M language - a declarative language with lazy evaluation.

Is there something about declarative languages that makes them especially suitable for data work?

This maps nicely to Cybermen in Dr Who

I learned about this from The Wire. They called it "the headshot"

Why GPT 5.1?

I find that the default Claude Code harness deals with the ambiguity best right now with the questionnaire system. So you can pose the core of the problem first and then specify only those implementation details that matter.

Have you tried the Explore feed? Mine has Music, Movies & TV, Hype, Live, Gaming, News, Sports, Learning, Fashion & Beauty, Podcasts and Playables. Most of those have some sort of subcategories too. It appears to be regionally determined - I don't see any influence from my data here

They're working on it.

I wonder what will happen if the author of isOdd optimizes their code by using the isEven package