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Yep. Except: 1. This was about important internal tools. The team was stuck in some architecture nightmare of their own doing (writing it in rails but headless, with graphql api, and a SPA react app, constantly needing frontend engineers for changes). I call this kind of thing 'cosplaying an enterprise production app'. All that complexity was in the way and using straight rails was perfect in that case. 2. I make calls like this all the time. Usually someone on the team asks me to. They see what needs to happen but don’t want to be the bad guy. I’m happy to just make the call if I agree with the premise. Saves enormous amounts of meetings and change management etc. Sometimes this is jokingly referred to as Founder-mode-as-a-service here. 3. For ten years I’ve also run an internal podcast called Context, where I revisit decisions like these and explain the reasoning so everyone can learn from them. This is helpful to give people all the variables that were considered and why this was the choice made given the information available at the time. I want to teach how to make such decisions effectively without needing me. Sunk cost fallacy is a problem. 4. Any notions that Shopify is succcessful despite of me doing this, instead of because of it, will have a hard time making their argument come together I think 😄 the part of 'two weeks later tobi learns about...' is nonsese and the pivot of that project up there happens one of the more successful examples of interventions. But getting the company to work effectively with great architecture and low technical debt baggage into the right direction is literally the job, so guilty as charged I suppose. But there are always cope stories floating around like this because they are more fun, than saying 'somehow we needed tobi to stop doing silly architecture astronautics'. I can totally see that.

81.5K 🌟 Anti-Slop 前端设计品味 Skills Taste Skill - @LexnLin # 13 个 Skill 分两类：代码输出实现、图像生成 1. 代码输出实现类 · taste-skill（默认，v2 实验版）：通用技能，约 1200 行 · taste-skill-v1：旧版保留，供依赖精确行为的用户钉住 · gpt-taste：针对 GPT/Codex 的更严格变体 · image-to-code："先生成参考图 → 分析 → 再写代码"流水线 · redesign：存量项目，先审计再改造 · soft / minimalist / brutalist：三种既定视觉方向（高端柔和 / Notion 式极简 / 工业粗野） · output：强制完整输出，禁止占位符截断 · stitch：输出 Google Stitch 兼容的 DESIGN.md 2. 图像生成 imagegen-frontend-web、imagegen-frontend-mobile、brandkit，用于配合图像模型生成设计参考稿，再交给 Coding Agents 实现 # taste-skill (v2) 的方法论 §0 简报推断：先"读空气"——页面类型、氛围词、参考链接、受众、隐性约束，输出一行 Design Read；歧义时只准问一个问题。核心论点是：LLM 设计差的根源是跳过理解直接套默认审美。 §1 三旋钮配置：DESIGN_VARIANCE（布局实验度）、MOTION_INTENSITY（动效深度）、VISUAL_DENSITY（信息密度），各 1-10，并附"信号 → 数值"推断矩阵和场景预设表。 §2 设计系统映射：简报指向 Fluent / Material / Carbon / Polaris / GOV. UK 等时，必须用官方包而非手写仿造；对玻璃拟态、Bento 等"无官方包的美学"则要求诚实标注为实现近似（如明确声明不存在官方 liquid-glass.css）。 §4 设计工程指令：大量从实测失败中提炼的硬规则——Serif 纪律（禁默认 Fraunces/Instrument Serif）、"LILA 规则"（禁默认 AI 紫）、高端消费品"米色+黄铜"色板禁令及替代色板轮换、Hero 纪律（标题 ≤2 行、副文 ≤20 词）、Eyebrow 标签每 3 个 section 最多 1 个、颜色/圆角/主题三把"一致性锁"等。 §5 动效规范：给出 GSAP Sticky-Stack、横向滚动劫持、Motion 渐显的规范代码骨架，并硬性禁止 window.addEventListener('scroll') 等反模式。 §9 AI 破绽目录 + 破折号全面禁令：编目了数十种"看起来很 AI"的签名式模式（编号 eyebrow、装饰性状态点、div 假截图、"Quietly in use at" 文案等），其中 em-dash 被列为"头号破绽"全面禁用。 §11 改版协议：区分绿地/保留式改版/颠覆式改版，先审计后动手，明确列出"不得静默更改"清单（URL、导航标签、表单字段、品牌标识、法律文案），并指出 SEO 迁移是改版头号风险。 §14 出厂前检查：约 60 项机械化清单，任何一项不过即视为未完成。

This is literally my new workflow now: Realtime Research → Grok Bot Planning & Orchestration→ Grok Bot Day-to-day Coding/Debug → Grok Build + Grok 4.6 Write & Run Tests → Grok Build + Grok 4.6 Complex Coding/Debug → GPT-5.6 Sol Frontend → Fable 5 Bookmark this.

Big news: Qwen3.8-Max by @Alibaba_Qwen just landed at #4# on the Frontend Code Arena leaderboard with a score of 1,668! With 1,668 points, Qwen3.8-Max is trailing only Claude Opus 5 (Max) with 1,705 pts and Kimi K3 (Max) with 1,676 pts, on par with Claude Opus 5 (High) with 1669 pts. It also ranks high across all domains: #2# in Consumer Product #3# in Brand & Marketing, Reference-based design, Gaming, and Content Creation Tools #4# in Data & Analytics #5# Simulations Dig into the thread for more details and to see how it also performs on real-world tasks in the Text Arena. Congrats to @Alibaba_Qwen on this huge release!

DeepSeek-V4-Flash-High by @deepseek_ai is #7# overall in the Frontend Code Arena with 1,586 pts! It’s #3# among open. In categories it’s #4# in Consumer Product, #6# in Reference-based Design, Data & Analytics, Gaming, and #7# in Brand & Marketing. This is an impressive improvement from DeepSeek-V4-Flash-High-Preview, a +154 pt jump. Even more impressive is the jump from DeepSeek-V4-Pro-Preview, a +121 point improvement.

$0.50 model just beat the most expensive AI on the market same prompt, one shot each: "build a $10k-looking landing page. single html file, dark theme, neon green accents, animated hero, pricing cards" claude fable 5 - anthropic's flagship, $10/$50 per M tokens: → 600 lines → clean page: hero, features, pricing, footer → solid. minimal. safe kimi k3 on openrouter - this request cost me $0.50: → 1200 lines → live animated chart with a ticking price feed → bento grid, testimonials, FAQ accordion → monthly/yearly pricing toggle, mobile menu, animated counters one of these looks like a template. the other looks like a funded startup full run in the video - kimi first, then fable. judge it yourself the frontier premium is real. but for one-shot frontend it just stopped making sense like + bookmark, prompt in the first comment

BREAKING: Kimi K3 by @Kimi_Moonshot is officially 1st on Frontend Web App Arena by DesignArena With an Elo of 1326, this open-weight model leads the way, ahead of Fable 5, Sonnet 5, and Opus 4.8 by @AnthropicAI Huge congrats to the @Kimi_Moonshot team for this achievement!

This is literally my new workflow now: Realtime Research → Grok 4.5 Planning & Orchestration→ Fable 5 Day-to-day Coding/Debug → Grok 4.5 Write & Run Tests → Grok 4.5 Complex Coding/Debug → GPT-5.6 Sol Frontend → Fable 5 Bookmark this

kimi已经登顶全球代码榜 这是中国大模型次登顶全球代码榜 在全球AI评测平台Arena AI的 Frontend Code Arena( 前端编程）榜单中，Kimi K3获得1679分，超 过Claude Fable 5的1631分和GPT-5.6 Sol的1618分， 并且成功上了抖音热搜第三 而且kimi 也是cz亲自夸奖过的ai 目前横盘一天了，看有没有庄家看上 0x9596247c39838e39fd528288969ec9c342f04444