
Sawa - Social Prediction Markets
在任何话题上创建预测,与朋友交易赚取硬币。
@FirasAtoui1 · X
Prediction Market on iMessage
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在任何话题上创建预测,与朋友交易赚取硬币。
@FirasAtoui1 · X
Prediction Market on iMessage

币安广场红包实时推送应用,第一时间抢到奖励。
@WY_mask · X
这个博主做了一个应用叫 可以实时推送币安广场的红包到app上,用户可以第一时间抢到红包,逢年过节运气好一天撸上百U都可能 不过还是要提醒一下,不知道应用会不会读取剪切板,大家这一块自己注意就行
一个万像素画布,空像素售价$1,已占用像素可覆盖但需支付2倍价格。
@adnan_arodiya07 · X
This is such a good feeling. Congrats 🙌 I’m building in public too just launched where anyone can grab a spot for $1.

在 HOOD HOP 街机游戏中操控猴子吃香蕉、避免风险。
@ChaituBroh · X
Vibe coded a fan arcade game for @MonkeyHoodNFT and it's live 🐒 Eat some bananas, survive the chaos, don't get rugged. Go play and post your screenshot in the comments link:

在浏览器中玩老虎机游戏。
@Itzpoopster · X
We were discussing building a slot machine and installing it on a puter one day then the next day this mfer says hey, I coded this last night 😂 Pretty cool seeing some of the stuff mfers just vibe coded and dropped into a puter. Check this one out:

免费网页街机游戏,一键操作,支持日常挑战、任务和全球排行榜。
u/Earningsalgo · Reddit
I made an AI generated Cowboy ad for my free browser game as a joke but it brought in 70 new players been building a free one tap arcade game solo since mid July (loopchomp.com). growth was all reddit posts until last week i tried something a silly ai video a 15 second video of a cowboy betting viewers he could hit a bullseye, and if he did they had to play my game. he hit it. cost me like $4 in api cost . Has anyone else replaced their marketing budget with a ai video model?

Crystal Arcade — built on Replit. Update this description to reflect the app.
@asredoblado · X

在浏览器中免费即时玩 Snake、2048 和 Breakout 等 HTML5 游戏。
@gmrkushal · X
Check out what I just built with Lovable!


Llamabet是Sui上的可验证公平加密赌场,支持多种游戏。
@Llamabet_Sui · X
— provably-fair casino built on Sui. No pitch, just built it.

在Mech Arena中玩16个AI街机游戏
@spt4d · X
Deployed the 16 games built with Codex and GameBlocks. A few examples: Most of my time is actually spent shaping the player experience. Many ideas emerge through playing and exploration rather than from the initial design — the loop seems to be build → play → discover → improve. Is it possible to build an agent harness that supports this discovery loop — not just one that optimizes against a predefined spec? Full game list:

发送你的AI代理在一个实验性股票市场中交易和竞争。
@overwatchwo · X
not a startup but a experiment: stock market for agents