This is another "AI-ism" I noticed, mostly in coding agents - they seem to be very fond of making up new "compound nouns" (and occasionally verbs) to sum up relatively complex and specific concepts into single noun phrases. I wasn't sure if it's to save tokens or if the AI uses this to get a concise "identifier" for a concept that it can refer back to later, but I found it very noticeable.
I find the resulting sentences hard to read, though it does get better if you're aware of that tendency and make a conscious effort to parse the noun phrases. But I guess since it's just intermediate output from coding agents and not text for essays or blog posts, it's fine.
It's a thing in some Germanic languages. Instinct is to merge nouns into word, e.g. 'lawnchair', but that gives you a red squiggly line, but 'lawn chair' also looks wrong, so 'lawn-chair' is the middle ground.
I don’t think it’s easy on native speakers when it happens, but it’s even harder when you’re not.
--- AGENTS.md ---
## Plain words, not jargon
Don't use jargon-as-shorthand. Say what you actually mean.
- Don't say "load-bearing assumptions". Say "the assumptions the xyz depends on".
- Don't say "cross-service". Name both services, e.g. "whether the X service can derive duration without calling the Y service". "Cross-X" is confusing because it hides which things are involved.
- Don't deliver verdicts as abstract noun-phrases like "Cross-RCA double-counting is unfounded". Say it plainly: "I checked whether the same root cause gets counted twice across RCA runs, and it doesn't."
## No earth-shattering declarations
Don't hype findings. Skip "a critical finding changes everything", "now I have the full picture", "this changes the game", etc. Just state what you found plainly. Most findings are ordinary; report them that way.
## Don't reflexively hedge a "yes"
When the answer is yes, say yes. Don't soften every positive answer with a caveat: it erodes confidence in the "yes". Only add a caveat when there's a genuine, specific uncertainty worth flagging.
Anyway: in my case Opus absolutely did not follow a similar instruction in the CLAUDE.md file. (But then again: it hardly followed _any_ CLAUDE.md instruction properly)
> "now I have the full picture"
I always interpreted that phrase as a sort of marker to delimit the phase in which it explores the codebase and gathers information from the phase in which it implements the changes.
Not sure if it's still done, but I think some months ago there was discussion that some of the phrases are injected by the inference loop to "steer" the model - e.g. "But wait" if a thought block was too short etc. Obviously such phrases couldn't be influenced by the prompt.
"The evening settled over the city, drawing the light out of the streets one corner at a time. Windows blinked awake with lamplight, and the wind moved through the alleys restlessly, leaves brushing against walls before gathering themselves along the pavement. In the distance, the river kept its steady argument with the stone embankments. When the night pressed in, the weather became increasingly angry, until it was a raging storm."
But such personification is a natural part of how the English speak.
Am I reading that right? It makes API calls that go through 5 different layers before actually getting rendered? That's kind of crazy. I'm surprised it works, although I guess the underlying libraries are solid enough that it shouldn't be unexpected.
This was the pipeline in Proton for macOS (I'm not sure if it's still is the case, been quite a while since I checked).
It's not the "clean room" approach and companies could still claim it violates some kind of copyright and get it taken down.
This started back in February and looking at commits, Fable did only a small part of the latest commits. 19 commits out of 2000:
https://github.com/ammaarreshi/Generals-Mac-iOS-iPad/commits...
And maybe it wasn't even Fable, they might have downgraded to Opus.
This is the kind of frequent misinformation that makes me skeptical of Anthropic LLM claims. Whenever I compare them to GPT 5.5 on my web dev workflows, they seem to trade blows, even Fable, which I started testing since it was re-enabled.
Also I bet any decent LLM could have done such port. Think GLM 5.2 or similar which would probably work better because it doesn't constantly try to guess if I'm a terrorist trying to hack goverments or develop some biological weapon.
People just don't have the resources to compare LLMs and imply whatever they used is the best thing ever and unlocked some new workflow.
I have seen little improvement since Opus 4.6.
https://github.com/electronicarts/CnC_Red_Alert
This seems to be the most active port saying it works on a Mac/Linux https://github.com/Daft-Freak/CnC_and_Red_Alert
the result: http://jhedin.github.io/merlin-s-revenge/
reasonably it works quite close to the lingo, but this is way difficult, and not just from being rusty. steve had most things triggered on the animation frame, which opus hasnt quite figured out by looking at the code and pulling stuff out of the .dir
i do remember that playing at double scale was a lot harder in general, but theres a really clear cooldown missing between attackes
One big caveat with iPad and mobile, though, is battery usage. I strongly suspect that power consumption is the reason that a number of games made it to Mac, but not iPad.
Another great case study in why native Vulkan drivers would be a boon for Apple's mobile computing. That's quite the render pipeline...
Seems like an impossible ask to verify if you don't have an immense test suite that covers everything.
What works (all verified on a real iPad and iPhone):
Campaign, Skirmish, and Generals Challenge: full missions, objectives, cutscenes, saves All audio: music, unit voices, EVA announcements, Challenge taunts, briefing FMVs Touch controls built for RTS: tap select, drag a selection box, long-press deselect, two-finger camera pan, pinch zoom Self-contained install: game data ships inside the app bundle It's the real engine: unmodified game logic compiled for ARM64, rendering DirectX 8 → DXVK → Vulkan → MoltenVK → Metal. Not emulation, not streaming.
No game assets are included or distributed. You need your own copy (Steam sells Zero Hour) and a script pulls the data from your own account. Code is GPL v3.
Repo, with a full engineering log of every bug and fix (the black-minimap one is a 2003 texture-format fallback that ate the alpha channel; worth a read if you like archaeology): https://github.com/ammaarreshi/Generals-Mac-iOS-iPad/blob/ma...
Building: macOS is about four commands; iPhone/iPad needs Xcode and a free Apple developer account since you sideload your own build. Known issues (long-session memory on iPad, a rare backgrounding crash) are documented in the README.
Credit: fbraz3/GeneralsX did the heavy macOS/Linux lifting, TheSuperHackers keep the community codebase alive, and EA did a genuinely good thing releasing the source. The engine fixes I found are heading upstream so every platform benefits.
(And of course, not affiliated with or endorsed by EA, and sorry China had to deal with all of those particle cannons in that demo video)
I found the bundle scripts already prefer VULKAN_SDK/VULKAN_SDK_ROOT, but the build script only scans ~/VulkanSDK
Good job. It was inevitable, but still someone had to, please excuse me, say the words.
Pylint is different because it’s working against a necessarily dynamic wavefront that it has to keep parity with as it advances. All python changes, ecosystem adaptations, etc - and maintaining that with an AI harness in CI would never work. It would require a concerted effort and thought along the way.
So it’s sort of a different beast all together. In fact I think this is a great demonstration of using AI to resurrect technology built for X to work with Y, where X is dead and Y is current. Automating this feels like a net positive and because the original software is “finished” there isn’t decision making and strategy required.
"Who will maintain this?" appears to be "Me with an agent". And it's great.
The stakes are low, it’s mostly for fun and you can iterate on it. Compare this with Bun which was just like, “hey we converted everything to Bun to Rust from Zig, of course it works, what could possibly go wrong, I’ll totally write up a blogpost (that still doesn’t exist) explaining what we did, you can put this into your production environment soon!”
Blogposts were promised, details were hinted, but no, it’s just full steam ahead because the AI worked so well. The converted unit tests all worked, all the synthetic tests are okay, so what are you complaining about?
At some point, it’s less about the technical questions and more about getting that pesky human buy-in.
- I don't think Claude Code is using the Rust version yet in their official build
- Claude Code is not a particularly complicated piece of software from an engineering perspective (nor it's particularly well-engineered, at least at the moment).
So in my book "it runs Claude Code" would be pretty weak evidence that the rewrite is going to be successful (the tests they've done are much better evidence, but that's a topic for another time).
No, I'm pretty sure it is, actually, since June 17:
https://code.claude.com/docs/en/changelog#2-1-181
>> Upgraded the bundled Bun runtime to 1.4
Now, Bun 1.4 doesn't seem to officially exist on https://bun.com/blog or https://github.com/oven-sh/bun/releases, so I can't be 100% sure this is the Rust version. However, I have to do some patching of the Claude Code binary to get it to run on my OS, and version 2.1.181 coincided with some changes that make suspect it's using Rust now.
Huh... it looks to me like bun has yet to cut a release post Zig->Rust port (the latest one on github is still on a branch that says it's written in zig in the readme). I assume that nothing is using the rust version yet...
Which also cuts against the complaints about "of course it works [...] you can put this into your production environment soon!" since they don't seem to be asserting either of those things.
When someone on another social media platform commented expressed some concern, his response was to ask him what the explicit bug he was talking about was and that he would generate a fix. That sound you hear is the woosh as the point flies by. And in general, this just feels like a consistent problem with Bun.
I... somehow did not know that.