为领域专家造 Agent 僚机。 一人团队^AI https://xitter.cf/t.co/x2AKGInyVh

China
Joined July 2012
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把 Anthropic 的 S-1 链接甩给 Opus,它创作了一座菜园。 角度是它自己挑的。招股书里写着,算力通常要提前 12–18 个月签下,于是算力账单成了棚,先搭好;营收是豆苗,往上生长。 六个季度,豆子从 3.76 亿美元长到 116 亿,涨了 30.7 倍,棚只高了 5.9 倍。2026 年一季度,豆尖越过棚顶;二季度开了花,首次经营盈利 9.74 亿。 它还翻出一个反直觉的数字:同一季度净亏 663 亿,九成是可转债跟着估值上涨做的账面重估。估值越高,账面亏得越多。 读招股书、选角度、抽数核账,agent 按 SOP 完全自治,挑刺我来 😂。 种菜传送门在一楼,园子里还有彩蛋哦 ⬇️
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Replying to @HaileyAILabs
看来要顺便让模型加一点后期
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Once the damselfly was done, I wanted to see if that same skill could handle any subject, especially infographics. So I extended it with rules for turning real data into a world you can explore. The Short Blanket is the first thing it made after that. Honestly, it turned out better than I expected.
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How this came together: It started with a different piece: the life of a damselfly, from egg to egg, as a 75-second hand-colored copperplate film. Every frame drawn in code by Opus. While building it, I kept writing down what worked (and what kept going wrong) and turned it into a reusable skill.
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Replying to @HaileyAILabs
好奇角色这部分这么处理,需要单独建模吗?
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Saw all those frame-by-frame, hand-drawn animations going around my timeline and got curious: what if Opus took a boring data table and turned it into a little stage you can actually walk into? So I handed it a sleep dataset. It built a moonlit dorm: one bed for each stress level, and every blanket is exactly as long as the hours slept. Drag around, zoom in, tap a bed to see the numbers. Stress, not steps, decides how long your night is. Honestly? We're barely scratching the surface of what this model can do. Link in the reply ⬇️
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Replying to @LgyLight
挺好的,除了股价🥺
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Replying to @CuiMao
确认道心碎了
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Replying to @Xian0063
笑死,美人鱼才是真正的小丑鱼
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Fins drawn along the bending body look fine on a shark. A humpback stays curled all the way round its bubble net, and its flippers are a third of its length. same method, the outer one balloons (koi too). So fins are pinned stiff at the root now. porting was mostly re-checking what quietly worked.
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Couldn't stop poking at this. the shark is literally a wiggly spine, and the letters just work out what they're sitting on. So I swapped in koi and gave them a pond with wind and ripples. tap the water and they come eat.
full demo of shark ascii animation
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Replying to @turingou
现在 Claude 还返 Credits,1 个订阅 2 份 额度
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Replying to @Fortunate
给同时兼职打光的 Claude 师傅加鸡腿
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Replying to @aaugeART
声音感受不好沟通,这也算是取巧。
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三个踩出来的坑,留给要上线 3D 页面的人: 手机上打字越打越慢,是帧率掉下来:动画时钟每帧最多推进 1/20 秒,帧率一掉到 20 以下,整段剧情就跟着放慢。 先查到的是纸面贴图:每敲一个字,那张 400 多万像素的贴图都整张重传一次。改成只传落墨的那一小块,快了不少,但还没到位。 剩下的在桌面浏览器上复现不出来,就在页面里挂了块性能面板,直接在手机上看每帧耗时:总耗时远大于主线程,说明卡在显卡。顺着查到右下角那排按钮的毛玻璃,3D 画面每帧都在重绘,按钮底下的模糊也跟着每帧重算。去掉毛玻璃、树影降频,从 8 帧回到 26 帧。
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体验 letterfall.glintiary.com 这回从设计到发布,整条流水线都交给了 Claude Code 1️⃣ 按需求搭出可交互、带声效的实时 3D 场景 2️⃣ 对照历次积累的踩坑记录精修 3️⃣ 排一段首尾相接的剧情,导出循环视频 4️⃣ 给社交平台做封面卡片 (ogimage) 5️⃣ 发布到 Cloudflare,得到一个打开就能玩的链接 6️⃣ 维护仓库里各个案例和文档之间的双向链接,下个同类项目直接接上这次的沉淀 能一路顺下来,靠的是这个 LLM wiki 里沉淀的个人画像、方法和脚本,我只管说清楚想要什么。
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上次说建模学晚了就不用学了,这次拿打字机试了试能做到多沉浸。 在浏览器里真能打字:每个键是一根连着字锤的杠杆,纸上有纤维、逐字压出的凹痕和背面透出的反字。敲击声是代码现合成的,照一台 1940 年 Erika 5 的录音标定(agent 自发)。中文走模拟拼音,选好字再一个个敲上去。 整台机器没有一个模型文件、一段录音,全是 Opus 5.5 写出来的。⬇️
有些技术学得太迟就不用学了,比如说,建模? Opus 在后台一顿敲,海上小火车就这么水灵灵造出来,场景音效都是它自发用代码合成的…… 实现: 基于 Sac 的提示词解构了一份通用 meta prompt,然后用 NB 2.1 生成参考图丢给 Opus 5.5 High。 额外提示如下,给模型的自由度较高: 做一个千与千寻的海上小火车场景 [参考图],3 只海鸥(1 停 2 飞是必备要素),车内暖光。 交互事件不一定是水面,按最佳戏剧效果帮我设计。
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Replying to @recatm @goldengrape
打补丁太消耗精力了,扭头直接换 Claude🤪
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