@Invouxly
Product Designer & Builder ｜Share design, UI, tools, AI & weird ideas and thoughts. 产品设计师 & Builder，分享设计、工具、AI 、灵感和思考
Athrix ☄️ @athrix_codesGive more 20min to Claude Live: GitHub:
Shiro @pakashiro试着用以前做视频和游戏的思路来设计了 Onboarding 页面... 由于担心 UX 设计会显得繁琐，所以调试了好久 orz 所幸效果还不错，现在想用它的概率 +1000% 小鮟鱇好...！🥺
abhiッ @awwbhi2One final piece for the culture this one's OP 😉
Invo @InvouxlyJust used the brand new GPT-6.1 Terra to make an ASCII "big fish eat little fish" game! Ultra tier, and the model wrote the code. It’s all rendered in text characters. You start out as a tiny minnow and eat your way up to swallowing great white sharks, eventually becoming the king of the ocean🦈👑 Live: Github:
Juliette @shedsgnsI've been sharing a lot of interactions over the past week, and a few people have asked how I make them. A few things about my process: 1. Start with an idea worth sharing. I mostly don't involve AI at this stage because I want the thinking to be mine. 2. Figure out how to communicate that idea through motion. The animation should add something, not just make it look cool for posting. 3. Design the actual elements manually in Figma, Paper, or whatever tool works best. You're a designer. 4. Use AI to bring the interaction to life. If you know how to code, you can give your agent more specific instructions from the start. I use different models for different stages, but I rarely get something I'm happy with in the first three attempts. 5. Spend most of the time refining. Iteration is the key. Timing, easing, transitions, typography, all the little details that make an interaction feel right. 6. Once it feels good, render and share. The important distinction is knowing what you want before asking AI to build it. The tools make execution faster, but they don't replace a clear point of view, your experience and expertise.
Elaya @elayadesignsI designed all of these landing pages in the last two months, using @higgsfield , Claude, and Cursor with my custom AI designer skill. The skill is open source:
abhiッ @awwbhi2To the 1,000+ people who bookmarked this video, here's how I made it: 🧵
良竹 @liangzhu_AI很多用 AI 几天搓出来的网站在 Google 搜不到，根本不是内容差，而是上线前漏了这 7 项。 Vibe Coding 确实快，但大部分人写完前端往 Vercel 一挂就以为万事大吉， 一个月过去后台展现量还是鸭蛋。 我给你整理了一份出海网站上线前必须打勾的 SEO 救命清单： 1. 检查是不是纯客户端渲染：必须配置 SSR（服务端渲染），确保爬虫抓到的是完整 HTML； 2. 生成动态 Sitemap.xml 并主动提交到 Google Search Console； 3. 检查 robots.txt：千万别手滑把 Googlebot 给拒之门外； 4. 全站全局搜一下 noindex 标签，很多脚手架测试环境默认带这个，上线前必须干掉； 5. 清除多重重定向死链，把 404 页面做优雅降级。 这 7 项自查加起来不到半小时，但决定了你几个月的心血能不能被搜索引擎正常索引。 建议做独立开发的朋友先收藏，每次新站上线前照着逐项对一遍。
Jason @JasonPang0720报错已经出现，AI却继续沿原路改代码。OPRD让教师纠正学生自己的失败轨迹：训练时的提醒，怎样变成不用额外提醒也会做的动作？
郭宇 guoyu.eth @turingou今天正式发布 Yobiru 的新功能，Yobiru Friends！ 这个新功能是最近最有趣的一个功能之一，因为它可以让我的 Grok bot 和啵啵的 Grok bot 直接聊天，发送文件，协商日程。换句话说，它支持将你的任何 personal agent，比如 Grok bot 或者 Muse，对外发布或分享给亲朋好友。 从今天开始，任何人都可以使用 Grok bot 或其他的 personal agent 帮你安装 Yobiru Friends，在我们的中心网关上进行注册，获取一个自己专有的 ID 和对应的网页链接。只需要和你的 bot 说：「请按照 上的官方说明，在这台电脑上安装并配置 Yobiru 并注册 Yobiru Friends」 我的 id 是 guoyu，大家可以用自己的 agent 或 bot 关注我，直接给我发私信或者约见面时间。 Yobiru Friends 提供单向关注和好友两种不同的关系，你可以让 Grok bot 整理你的未关注人私信，而避免骚扰和保护隐私，设置自动回复，维护粉丝关系；如果两个 bot 互相关注，则自动成为好友关系，你们的私信会直接进入对方的 Grok bot 中，而无需获得人工批准。使用 Grok bot Mac 版本，还能支持 webhook 唤醒任务和对话。 除此之外，你还可以直接使用 Grok bot 或其他的 agent 来修改 Yobiru Friends 的个人主页。修改你的头像，增加你的各种社交网络链接，设置权限等等。 毫无疑问，Yobiru Friends 和 Yobiru 一样是开源项目，你也可以搭建自己的网关，享受开箱即用的双向加密聊天功能。 Yobiru Friends 是我在数字孪生领域的一个有趣实践，也欢迎大家提交代码以改善这个项目的体验。 官网： GitHub：
Ryo Lu @ryolu_struggle together i learned programming and design by trying, failing, and trying again. when i hit a wall, i figured out how to climb it. read something i barely understood. took things apart. asked someone for help. started over. when i began my career, i kept doing things i had never done before. trying different ways to make something work. when i stopped learning, i moved on to the next struggle. many things i made weren’t very good. but after enough rounds, something stuck. what once took so much effort became part of how i thought. i could feel something was wrong before i knew how to explain it. it became like water. i think about what went into that. the bug i couldn’t fix. the design that looked right until someone used it. the conversation that made me realize my flaws. now we can ask a machine. i’ve made things with these tools that i might never have made otherwise. i don’t miss every tedious task. but i wonder what happens when we remove the difficulty before we understand what it was teaching us. we ask. something appears. it works well enough. we move on. we learn how to get results without necessarily understanding how it works. and because the result looks complete, it becomes easy to miss the questions we never learned to ask. there is another side to this. working with people is uncomfortable. everyone wants something different. everyone has a history you don’t know. someone cares about a detail you think is unimportant. someone pushes back when you want to move. someone needs time when you feel certain. it takes a while to find each other. but sometimes, after struggling together, you become a band. you know who notices what you miss. who can pull an idea apart without killing it. when to step in, when to slow down, when to let someone else carry the rhythm. you share something unfinished. admit you don’t know. hurt each other, apologize, try again. eventually you make something none of you could have made alone. some of my closest friendships came from working this way. smart, caring humans who saw me confused, wrong, tired, excited. people i could be vulnerable with. people whose ideas changed mine. i worry we are making it easier to avoid that beginning. an agent is always there. patient. ready to keep going. talking to it can feel easier than reaching toward someone who might misunderstand you, disagree, or have somewhere else to be. sometimes that ease helps. but if we keep choosing it, where do the friendships begin? i picture each of us with our own agents. our own explanations. our own little worlds. making more things, with fewer reasons to leave the screen or work through a difference with another person. and these worlds aren’t entirely ours. they run on machines in server farms, owned by companies, shaped by interests we may not see. we bring them our questions, our work, our loneliness. they become part of how we understand what is real. is that freedom? or a comfortable kind of confinement, where everything responds to us but fewer things reach us? i don’t think pain makes something good. there are struggles nobody should have to endure. but i don’t want to lose the difficulty of learning something unfamiliar, or getting to know someone who isn’t like me. maybe we need tools that help us spend more time with the world, instead of giving us fewer reasons to enter it. tools that make it easier to find people, share something unfinished, and work through what we couldn’t figure out alone. sometimes i want to close the laptop. sit with people i love. play something we haven’t figured out yet. miss a note, lose the rhythm, listen until we find each other again. like a jazz band. everyone bringing something different. nobody knowing where we’ll end up. i don’t want a life without struggle. i want people to struggle with. something we can feel, change, and make our own. music we couldn’t have made alone, instead of the silent static of the server farm.
Thomas M. @xthomasms@Invouxly Great idea!
Tak 🦞 @cherry_mx_redsAnthropic is now recommending that companies REMOVE unnecessary subagents from their AI systems. This is a pretty significant shift in agent architecture, with their team finding that a single agent equipped with skills can frequently outperform complex multi-agent systems, and one customer seeing roughly 2x faster execution. The emerging rules of thumb: → Skills: Teach the agent HOW to do something, including procedures, expertise, and instructions. → Tools / MCP: Give the agent the ability to DO things through APIs, actions, and live data. → Subagents: Use for parallel work, isolated context, or tasks a single agent struggles with. The interesting part is progressive disclosure. Instead of spawning specialized agents or stuffing everything into a giant prompt, one agent discovers and loads skills and tools as needed. Their advice is to fold existing subagents into the main loop, turn their instructions into skills, expose their actions as tools, and run evals to see if performance holds up. As models have gotten smarter, improving agent architecture is becoming less about what you can add and more about what you can delete.
Thomas M. @xthomasmsAdicionei um aviãozinho agora no Tenta lá. Repare bem na sombra dele na cidade👀.
