A six-week online cohort for 9-12 grade students with programming basics to design, build, and deploy a real web app using the workflows professional engineers now use with AI.
面向 9-12 年级、有一定编程基础的学生。6 周线上小班，学习如何用 AI 辅助的软件工程流程，设计、开发并上线一个真实 Web App。
Most coding classes still optimize for typing code by hand. That is no longer the highest-leverage skill. Students need to learn how to break systems down, direct AI tools, validate answers, debug failures, and make tradeoffs.
大多数编程课还停留在刷语法、跟着 PPT 写代码。未来更稀缺的能力，是系统拆解、架构设计、提示词工作流、交叉验证、debug 和上线交付。
Students still touch code, but the center of gravity moves from memorizing syntax to building a working system.
学生当然会接触代码，但重点不是背语法，而是把想法拆成能运行、能上线的系统。
Karl brings the software development habits used inside real engineering teams, not a packaged worksheet curriculum.
课程带入真实工程团队的方法，而不是把学生带着做几张模板练习。
The goal is architect thinking: define the system, ask better questions, cross-check outputs, and ship.
目标是培养未来 architect / PM 式思维：定义系统、提出好问题、交叉验证、最终交付。
Each student scopes a realistic non-AI web app around their interests.
每个学生围绕自己的兴趣，确定一个可完成的非 AI Web App 项目。
The project is deployed with Vercel so it can be shared in a portfolio, resume, or application context.
项目通过 Vercel 上线，能作为作品集、简历或申请材料里的真实链接。
Students learn the basics of version control and how real engineers collaborate around code.
学生会接触版本管理，理解真实工程师如何围绕代码协作。
Students leave with a concise explanation of what they built, why it matters, and how it works.
学生最终能说清楚自己做了什么、为什么做、系统如何工作。
Software development lifecycle, front-end/back-end concepts, what AI is, what AI programming is, and how developer roles change.
软件开发流程、前后端概念、什么是 AI、什么是 AI 编程，以及 AI 时代开发者的定位变化。
Turn interests into requirements, user flows, page inventory, feature cuts, and a realistic build plan.
把兴趣转成需求、用户流程、页面清单、功能裁剪和可执行开发计划。
A practical, simple introduction to structure, layout, styling, interactions, state, and events.
用最少但够用的概念理解页面结构、样式、交互、状态和事件。
Use multiple AI workflows to review plans, find bugs, validate assumptions, and reason through browser/devtools failures.
利用多个 AI 工作流互相审查、发现 bug、验证假设，并学习浏览器和 devtools 排错思维。
GitHub basics, collaboration habits, version control, deployment, and how to work with others without losing control of a project.
GitHub 基础、协作开发习惯、版本管理、部署，以及如何和别人一起开发而不把项目搞乱。
Engineering review, README, demo script, application-ready project narrative, launch checklist, then student demos.
项目整理、README、demo script、申请材料可用的项目叙述、上线 checklist，最后学生展示。
These are examples, not templates. Students can propose their own theme; the course helps cut it down to a buildable first version.
这些只是启发，不是模板。学生可以自选主题，课程会帮助把想法裁剪成第一版可完成的项目。
Rounds, teams, scores, speaker notes, and standings.
管理轮次、队伍、比分、speaker notes 和排名。
Compare schools, deadlines, majors, essays, and priorities.
比较学校、截止日期、专业、文书和优先级。
Track workouts, habits, goals, and progress over time.
追踪训练、习惯、目标和长期进步。
Members, events, roles, attendance, and project tasks.
管理成员、活动、角色、出勤和任务。
Budget scenarios, savings goals, and simple charts.
预算场景、储蓄目标和简单图表。
Log hours, organizations, reflections, and milestones.
记录时长、机构、反思和里程碑。
The six-week course experience for students who can keep their project moving between sessions.
适合能按每周 milestone 自主推进项目的学生。
For students who want async support when their project gets stuck between classes.
适合希望课外也能通过 Discord 获得项目答疑的学生。
1:1 project mentorship for students who want a polished portfolio package after or alongside 101.
面向想把项目做成完整申请作品集 package 的学生。
Tuition is disclosed inside the application flow before submission. Private Studio is scoped by consultation.
价格会在申请流程内、提交前明确展示。Private Studio 按项目目标单独评估。
Karl Qu is a Senior AI Engineer at Google, previously a Software Engineer at Azure OpenAI and Uber. His academic background spans mathematics, computer science, and AI through City University of Hong Kong, UC Davis, and Stanford.
Karl Qu 现任 Google Senior AI Engineer，曾在 Azure OpenAI 和 Uber 担任 Software Engineer。 学术背景横跨数学、计算机和 AI，来自 City University of Hong Kong、UC Davis 和 Stanford。
The course translates real engineering judgment into a format high school students can use: clear system thinking, practical tooling, and the ability to ship.
这门课把真实工程判断翻译成高中生能掌握的方法：系统拆解、工具使用、调试验证和最终交付。
Independent program. Not affiliated with or endorsed by Google, Stanford, Microsoft, Uber, UC Davis, or City University of Hong Kong.
本项目为 Karl Qu 个人独立课程，与 Google、Stanford、Microsoft、Uber、UC Davis 或 City University of Hong Kong 无官方隶属或背书关系。
Not for the first cohort. Students should have some programming exposure and should already be comfortable using AI tools like ChatGPT, Claude, or Gemini.
第一期不主打零基础。学生最好学过 Python、Java、JavaScript、AP CS、robotics，或做过一些个人项目，并且日常使用过 ChatGPT、Claude、Gemini 这类工具。
Because API keys, billing, privacy, and safety distract from the first skill students need: learning how to use AI to build software. AI API integration can come later.
因为 API key、账单、隐私和安全问题会抢走第一期最重要的学习重点：如何用 AI 辅助软件开发。AI API 集成可以放到后续进阶课。
Yes, if taught correctly. The skill is not blind copying. Students learn to define systems, ask precise questions, inspect code, validate outputs, debug errors, and explain tradeoffs.
关键在教学方式。不是让学生盲目复制 AI 输出，而是训练他们定义系统、提出精确问题、读懂代码、验证结果、排查错误、解释取舍。
AP CS is useful, but it is exam- and syntax-oriented. This course is product- and workflow-oriented: students build, debug, deploy, and present a real project.
AP CS 有价值，但主要面向考试和语法。这门课面向真实软件开发流程：拆需求、做项目、debug、上线、展示。
No. The two-hour format is designed so the hard concept and debugging work happens in class. Students will have weekly milestones, but parents should not need to become technical tutors.
不需要。2 小时课程设计就是为了把关键概念和排错尽量在课堂内解决。学生会有每周推进任务，但家长不需要变成技术辅导老师。
Tuition for Core and Mentored Cohort is shown inside the application flow before submission. Private Studio is scoped by consultation.
Core 和 Mentored Cohort 的价格会在申请流程里、提交前展示。Private Studio 按学生目标和项目复杂度单独沟通。
Limited seats. Students are selected by programming background, project fit, schedule match, and motivation.
名额有限。我们会根据学生编程基础、项目匹配度、时间安排和学习动机筛选。