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!”

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.

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.

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.

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

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)

Good job. It was inevitable, but still someone had to, please excuse me, say the words.

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.

--- 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.