设计工程新纪元 AI与动效的交融。
Vercel引领AI原型部署革新,动效设计原则揭示产品叙事新逻辑。
Vercel通过Dockerfile和AI Gateway等更新,为设计工程师提供更强大的基础设施。AI原型部署和模型路由的灵活性得到显著提升。同时,动效设计原则的讨论,为产品界面与交互设计带来了新的视角。
给 Fable 放权:让它自行判断工作方式
Fable's judgement
Simon Willison 从 Claude Code 团队获知的实战心法:与其给 Fable 规定繁琐的测试规则,不如直接让它自行判断工作方式。更可通过一句提示词让 Fable 自主调用低功耗子代理处理编码任务,在涨价前显著节省 token,同时提升输出质量。
Vercel MCP 和 CLI 新增 Agent Runs 追踪
Agent Runs now available in the Vercel MCP and CLI
Vercel 在其 MCP 与 CLI 中正式上线 Agent Runs,自动采集部署在平台上的 AI Agent 运行轨迹。设计工程师现可通过自然语言或 vercel agent-runs 系列命令,直接查询项目的推理过程、工具调用详情及 token 消耗,大幅简化 AI 应用的调试与优化流程。
LLM 正在瓦解努力的可辨识度
Legibility of effort
LLM 让高质量内容的生产成本趋近于零,导致我们丧失了通过成果外观判断背后真实人力投入的能力。当“努力”不再可被直观辨识,创意工作的价值衡量、用户信任机制乃至设计师的职业认同,都将面临根本性的重构。
caveman skill:让 Claude 说洞穴语省 75% token
JuliusBrussee/caveman
这是一个 Claude Code skill(也支持 Codex/Cursor 等 30+ 工具),通过让 AI 用极简的“洞穴人语”输出,在保持技术准确性的前提下削减约 75% 的 token。项目提供了安装指南和基准测试,能直接降低 API 成本并提升响应速度。
OpenAI 推出 Claude Code 专用 Codex 插件
openai/codex-plugin-cc
OpenAI 发布了一个 Claude Code 官方插件,允许用户在不离开 Claude Code 的情况下直接调用 Codex 进行代码审查、对抗性审查或后台任务委派。对于已经使用 Claude Code 作为主力环境的设计工程师和开发者来说,这意味着无需切换上下文就能接入 Codex 的推理能力,进一步打通两大 AI 编码工具的工作流。
开源 AI Gap Map 发布
Open Source AI Gap Map
Current AI 发布开源 AI Gap Map v0.1,系统索引 421 个产品(工具、模型、数据集、硬件),覆盖模型组件到基础设施三层栈。全部 1,184 个 YAML 数据文件与脚本已在 GitHub 以 MIT 协议开源,支持用 Datasette Lite 直接探索,方便设计师与开发工程师按需检索开源资源。
Vercel Functions 支持 Dockerfile 容器部署
Bring your Dockerfile to Vercel Functions
Vercel Functions 正式支持通过 Dockerfile 或 Containerfile 部署容器化 HTTP 服务。任何语言编写的现有应用现在都能直接迁移到 Vercel 平台,无需重构为特定运行时,同时继续享受预览部署、自动扩缩容和统一日志等能力。
别再堆工具了,用户要的是无缝集成
Users Don’t Need More Tools: They Need Seamless Integrations
文章批判“AI-first”产品思维,提出“Quiet AI”理念:AI 应像 Claude 嵌入 Office 那样隐形运行,贴合用户既有心智模型,解决高频高痛点,而非用新工具或聊天界面增加认知负担。作者还引出“Folder Instructions”概念,但正文在此处截断。
设计完然后呢?Figma 转代码 AI 乱象全图
You design it. Then what? A clear map of the Figma-to-code AI mess
文章将 Figma 到代码的 AI 流程拆解为多层栈,指出 demo 只在完美单一层级运行,真实项目却需三到四层叠加,这正是设计师屡屡碰壁的根源。作者以 MCP 为起点,解释 AI 助手为何无法直接读取设计文件,帮助读者理清设计工程化的真实瓶颈。
别再汇报 UX 活动,去汇报业务成果
Stop Reporting UX Activity and Report Business Outcomes
NNG 指出 UX 团队输掉预算战的原因不是工作没价值,而是汇报方式错误:沉迷展示可用性测试数据等活动指标,却未翻译成高管关心的收入、成本、风险、留存等业务结果。若不能把设计与业务底线挂钩,UX 将被视为成本中心而遭削减。
Principles in motion:动效设计原则
Principles in motion
Figma官方博客指出,动效设计的本质是在时间维度上进行创作。文章阐释了运动机制如何将单纯的视觉移动转化为具有语义和情感的表达,帮助设计师超越装饰性动画,构建更具意义的数字产品体验。
好 UX 搞崩了就业市场?
Did good UX break the job market?
一键申请、简历自动填充与 AI 生成求职信把应聘摩擦降为零,平均职位收件暴增至 300 份,面试率却从 15% 跌至 2–3%。作者指出 UX 设计师引以为傲的'极致体验',正在制造系统性噪音,让招聘市场陷入低效内卷。
JavaScript 版代码整洁之道指南
ryanmcdermott/clean-code-javascript
将 Robert C. Martin《Clean Code》原则适配到 JavaScript 的开放指南,覆盖变量命名、函数、类、SOLID、测试与并发等章节。对需要交付生产代码的设计工程师而言,这是一份可直接落地的代码质量检查清单,能显著降低设计系统前端实现的技术债务。
Agent Skills:让 AI Agent 获得专业技能的开放标准
agentskills/agentskills
Agent Skills 提出了一种轻量级开放标准,通过 SKILL.md 文件和配套资源文件夹,为 AI Agent 注入可复用的领域知识和工作流。对设计团队而言,这意味着可以将设计规范、审查流程或组件用法封装成标准 skill,让 AI 助手在不同工具间保持一致性和可靠性。
Vercel AI Gateway 上线模型路由规则
Routing rules now available on AI Gateway
Vercel AI Gateway 新增防火墙级路由规则,支持在网关层直接重写或拦截模型请求。当模型宕机、退役或团队需要统一标准时,无需修改应用代码,推送一条规则即可实时切换流量,且保留原有的回退与提供商配置,显著降低 AI 基础设施的维护成本。
Vercel Functions 包体积上限提至 5GB
Vercel Functions can now be up to 5GB in package size
Vercel Functions 将 Node.js 与 Python 部署的包体积上限从 250MB 提升至 5GB,增幅达 20 倍。此前因体积过大而无法部署的 Python AI 库、浏览器自动化依赖及音视频处理工具,现在可直接跑在 Vercel 上,设计工程师做重型 AI 原型和图像处理服务的门槛被大幅降低。
Strix:开源 AI 自动渗透测试工具
usestrix/strix
Strix 是一套自主 AI Agent,能动态运行代码、执行 PoC 验证来自动发现应用漏洞,并支持 GitHub Actions 与 CI/CD 集成。它面向开发者与安全团队,虽在 DevSecOps 场景有实用性,但对设计师日常工作流无直接关联。
caveman skill:让 Claude 说洞穴语省 75% token
JuliusBrussee/caveman
这是一个 Claude Code skill(也支持 Codex/Cursor 等 30+ 工具),通过让 AI 用极简的“洞穴人语”输出,在保持技术准确性的前提下削减约 75% 的 token。项目提供了安装指南和基准测试,能直接降低 API 成本并提升响应速度。
msitarzewski/agency-agents
A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes, and proven deliverables. 🎭 The Agency: AI Specialists Ready to Transform Your Workflow A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes, and proven deliverables. 🚀 What Is This? Born from a Reddit thread and months of iteration, The Agency is a growing collection of meticulously crafted AI agent personalities. Each agent is: 🎯 Specialized: Deep expertise in their domain (not generic prompt templates) 🧠 Personality-Driven: Unique voice, communication style, and approach 📋 Deliverable-Focused: Real code, processes, and measurable outcomes ✅ Production-Ready: Battle-tested workflows and success metrics Think of it as: Assembling your dream team, except they're AI specialists who never sleep, never complain, and always deliver. ⚡ Quick Start Option 1: Use with Claude Code (Recommended) # Install all agents to your Claude Code directory ./scripts/install.sh --tool claude-code # Or manually copy a category if you only want one division cp engineering/*.md ~/.claude/agents/ # Then activate any agent in your Claude Code sessions: # "Hey Claude, activate Frontend Developer mode and help me build a React component" Option 2: Use as Reference Each agent file contains: Identity & personality traits Core mission & workflows Technical deliverables with code examples Success metrics & communication style Browse the agents below and copy/adapt the ones you need! Option 3: Use with Other Tools (GitHub Copilot, Antigravity, Gemini CLI, OpenCode, OpenClaw, Cursor, Aider, Windsurf, Kimi Code) # Step 1 -- generate integration files for all supported tools ./scrip…[truncated]
健身动作数据集 trending:6 语言结构化数据开源
hasaneyldrm/exercises-dataset
开发者将 1324 个健身动作整理成结构化数据集并开源,附带数据库模式、API 代码与多语言指令(中英意土俄西),但因版权争议未包含演示媒体。对健身类应用开发者是即拿即用的后端脚手架,但对广义设计师而言可复用价值极低。
Career-Ops:用 Claude Code 打造的 AI 求职代理系统
santifer/career-ops
开发者将 Claude Code 扩展为求职指挥中心,通过 Playwright 自动扫描 Greenhouse 等招聘门户,以 10 维度加权评分批量筛选职位,并生成 ATS 优化的定制 PDF 简历。它不是海投工具,而是帮求职者从数百条信息中快速定位高匹配机会的过滤系统。
obra/superpowers
An agentic skills framework & software development methodology that works. Superpowers Superpowers is a complete software development methodology for your coding agents, built on top of a set of composable skills and some initial instructions that make sure your agent uses them. Quickstart Give your agent Superpowers: Claude Code, Codex CLI, Codex App, Factory Droid, Gemini CLI, OpenCode, Cursor, GitHub Copilot CLI. How it works It starts from the moment you fire up your coding agent. As soon as it sees that you're building something, it doesn't just jump into trying to write code. Instead, it steps back and asks you what you're really trying to do. Once it's teased a spec out of the conversation, it shows it to you in chunks short enough to actually read and digest. After you've signed off on the design, your agent puts together an implementation plan that's clear enough for an enthusiastic junior engineer with poor taste, no judgement, no project context, and an aversion to testing to follow. It emphasizes true red/green TDD, YAGNI (You Aren't Gonna Need It), and DRY. Next up, once you say "go", it launches a subagent-driven-development process, having agents work through each engineering task, inspecting and reviewing their work, and continuing forward. It's not uncommon for Claude to be able to work autonomously for a couple hours at a time without deviating from the plan you put together. There's a bunch more to it, but that's the core of the system. And because the skills trigger automatically, you don't need to do anything special. Your coding agent just has Superpowers. Sponsorship If Superpowers has helped you do stuff that makes money and you are so inclined, I'd greatly appreciate it if you'd consider sponsoring my opensource work. Thanks! Jesse Installation Installation differs by harness. If you use more than one, install Superpowers separately for each one. Claude Code Superpowers is available via the official C…[truncated]
ChromeDevTools/chrome-devtools-mcp
Chrome DevTools for coding agents Chrome DevTools for agents Chrome DevTools for agents (chrome-devtools-mcp) lets your coding agent (such as Antigravity, Claude, Cursor or Copilot) control and inspect a live Chrome browser. It acts as a Model-Context-Protocol (MCP) server, giving your AI coding assistant access to the full power of Chrome DevTools for reliable automation, in-depth debugging, and performance analysis. A CLI is also provided for use without MCP. Tool reference | Changelog | Contributing | Troubleshooting | Design Principles Key features Get performance insights: Uses Chrome DevTools to record traces and extract actionable performance insights. Advanced browser debugging: Analyze network requests, take screenshots and check browser console messages (with source-mapped stack traces). Reliable automation. Uses puppeteer to automate actions in Chrome and automatically wait for action results. Disclaimers chrome-devtools-mcp exposes content of the browser instance to the MCP clients allowing them to inspect, debug, and modify any data in the browser or DevTools. Avoid sharing sensitive or personal information that you don't want to share with MCP clients. chrome-devtools-mcp officially supports Google Chrome and Chrome for Testing only. Other Chromium-based browsers may work, but this is not guaranteed, and you may encounter unexpected behavior. Use at your own discretion. We are committed to providing fixes and support for the latest version of Extended Stable Chrome. Performance tools may send trace URLs to the Google CrUX API to fetch real-user experience data. This helps provide a holistic performance picture by presenting field data alongside lab data. This data is collected by the Chrome User Experience Report (CrUX). To disable this, run with the --no-performance-crux flag. Usage statistics Google collects usage statistics (such as tool invocation success rates, latency, and environment information) to improve …[truncated]
video-use 开源:扔素材进文件夹,Claude Code 出成片
browser-use/video-use
browser-use 团队开源 video-use,让 Claude Code 等 AI Agent 自动完成粗剪、调色、字幕烧录与动画叠加。创作者只需把素材丢进文件夹、自然语言对话即可出片,将视频后期纳入 Agent 工作流,对需要批量产出演示或教程的设计师极具实操价值。
actions/checkout v7:默认阻止 Fork PR 代码检出
actions/checkout
GitHub 官方 CI/CD 动作发布 v7,核心变更是默认拒绝在 pull_request_target 触发时检出 Fork PR 代码,以防范供应链攻击,同时整体迁移至 ESM 并更新依赖。对设计师及 AI 设计工具用户几乎无直接关联,仅对自行维护复杂自动化管道的设计工程师边缘相关。
ECC v2.0 RC:跨 Claude/Cursor 的 Agent 性能优化框架
affaan-m/ECC
这个开源项目为 Claude Code、Cursor、Codex 等主流 AI 编程工具提供了一套完整的性能优化系统,涵盖 skills、记忆优化、安全扫描和 MCP 配置。作为 Anthropic 黑客松获奖项目,它已在生产环境经过 10 个月验证,刚发布 v2.0.0-rc.1 版本并新增 Hermes 操作员工作流。
Vibe-Trading 个人交易代理
HKUDS/Vibe-Trading
香港大学数据科学实验室开源的 AI 交易代理,支持通过自然语言驱动股票分析与自动交易,集成 Shadow Account 回测与 MCP API。对设计师受众而言属于跨领域金融工具,无直接实操价值。
Agent Skills:让 AI Agent 获得专业技能的开放标准
agentskills/agentskills
Agent Skills 提出了一种轻量级开放标准,通过 SKILL.md 文件和配套资源文件夹,为 AI Agent 注入可复用的领域知识和工作流。对设计团队而言,这意味着可以将设计规范、审查流程或组件用法封装成标准 skill,让 AI 助手在不同工具间保持一致性和可靠性。
OpenAI 推出 Claude Code 专用 Codex 插件
openai/codex-plugin-cc
OpenAI 发布了一个 Claude Code 官方插件,允许用户在不离开 Claude Code 的情况下直接调用 Codex 进行代码审查、对抗性审查或后台任务委派。对于已经使用 Claude Code 作为主力环境的设计工程师和开发者来说,这意味着无需切换上下文就能接入 Codex 的推理能力,进一步打通两大 AI 编码工具的工作流。
Langflow 登 GitHub Trending:可视化 AI 工作流引擎
langflow-ai/langflow
Langflow 近日登上 GitHub Trending,它是一个支持可视化拖拽的 AI 智能体与工作流构建平台,内置 API 与 MCP 服务器导出能力,可对接主流 LLM 与向量数据库。对于需要快速搭建 AI 原型或把设计流程自动化的设计师和工程师,值得留意。
PyTorch 登上 GitHub 今日 Trending
pytorch/pytorch
该条目仅为 GitHub Trending 对 PyTorch 主仓库的自动抓取,正文内容是项目的基础 README 摘录,涉及张量计算与动态神经网络等常规介绍,未包含任何新功能、版本更新或设计相关动态。
哈佛 cs249r ML 系统工程教材开源
harvard-edge/cs249r_book
哈佛边缘计算实验室将《Machine Learning Systems》教材及全套实验代码开源,涵盖 TinyTorch、硬件实验与基础设施模拟,定位为 ML 系统工程的综合课程。
JavaScript 版代码整洁之道指南
ryanmcdermott/clean-code-javascript
将 Robert C. Martin《Clean Code》原则适配到 JavaScript 的开放指南,覆盖变量命名、函数、类、SOLID、测试与并发等章节。对需要交付生产代码的设计工程师而言,这是一份可直接落地的代码质量检查清单,能显著降低设计系统前端实现的技术债务。