中文版

亲爱的朋友们：

当前，市场对精通AI的开发人才需求极为旺盛，但供给却远远不足。与此同时，我们看到一个矛盾的现象：由于大多数高校的课程设置未能跟上时代，依旧没有将AI工具融入教学，导致近期计算机科学（CS）专业的毕业生失业率反而有所上升。

当我在面试AI工程师时，我所寻找的是能够做到以下几点的人才：

• 能利用AI辅助，高效地构建软件系统；
• 能熟练运用提示工程（Prompting）、检索增强生成（RAG）、评估（Evals）、智能体工作流（Agentic Workflows）等AI基础模块来开发应用；
• 并且具备快速原型设计和迭代的能力。

掌握这些技能的工程师，其工作效率与那些仍停留在2022年（生成式AI诞生前）传统编码方式的开发者相比，简直是天壤之别。我每周都会和许多大型企业交流，他们渴望招聘数百名甚至更多的这类人才。许多初创公司也空有绝佳的创意，却苦于没有足够的工程师去实现。我预见，随着AI在各行各业的普及，这种人才短缺只会愈演愈烈。

这就解释了我们为何会同时听到“CS毕业生找不到工作”和“市场急需的AI工程师薪资飙升”这两种看似矛盾的声音。

编程技术的演进历来如此。当它从打孔卡升级到键盘和终端时，雇主们也曾一度继续沿用打孔卡程序员。但最终，所有开发者都必须拥抱新的编码方式。如今，AI工程正掀起同样巨大的变革浪潮。

这就像一则漫画描绘的：2022年的技术面试还在问“你能写出FizzBuzz吗？”，而到了2025年，问题已经变成了“你能搭建一个电子商务平台吗？”

社会上有一种说法，认为“AI原生代”的应届生能够超越经验丰富的开发者。这不无道理。我自己就曾多次在招聘全栈工程师时，选择了一位精通AI的应届生，而放弃了一位仍在用传统方式工作的资深开发者。

但我要强调的是，我所认识的最顶尖的开发者，并非应届生（对他们并无冒犯之意！）。他们是那些始终紧跟AI变革浪潮、经验丰富的资深专家。当今生产力最高的程序员，是那些既深刻理解计算机原理、懂得如何架构软件、并能在复杂局面下做出权衡，又同时熟悉前沿AI工具的人。

诚然，一些2022年的旧技能正在被淘汰。比如，过去我们必须死记硬背的大量编码语法，如今已不那么重要。但即便有30%的CS知识过时了，剩下的70%——如果能与现代AI知识相结合——才是铸就顶级开发者的核心。（就像打孔卡被淘汰后，对编程的底层理解对于使用键盘写代码依然至关重要。）

你不可能光靠“感觉”就写出伟大的代码。计算机基础依然是基石。对于那些在此基础上又掌握了AI的人来说，职业机会将不可限量！

持续创造，
吴恩达

English Version

Dear friends,

There is significant unmet demand for developers who understand AI. At the same time, because most universities have not yet adapted their curricula to the new reality of programming jobs being much more productive with AI tools, there is also an uptick in unemployment of recent CS graduates.

When I interview AI engineers — people skilled at building AI applications — I look for people who can:

• Use AI assistance to rapidly engineer software systems
• Use AI building blocks like prompting, RAG, evals, agentic workflows, and machine learning to build applications
• Prototype and iterate rapidly

Someone with these skills can get a massively greater amount done than someone who writes code the way we did in 2022, before the advent of Generative AI. I talk to large businesses every week that would love to hire hundreds or more people with these skills, as well as startups that have great ideas but not enough engineers to build them. As more businesses adopt AI, I expect this talent shortage only to grow! At the same time, recent CS graduates face an increased unemployment rate (e.g., see this study using data from 2023), though the underemployment rate — of graduates doing work that doesn’t require a degree — is still lower than for most other majors. This is why we hear simultaneously anecdotes of unemployed CS graduates and also of rising salaries for in-demand AI engineers.

When programming evolved from punchcards to keyboard and terminal, employers continued to hire punchcard programmers for a while. But eventually, all developers had to switch to the new way of coding. AI engineering is similarly creating a huge wave of change.

Comic showing tech interviews: 2022 asks “Can you code FizzBuzz?” vs 2025 asks “Can you build an e-commerce platform?”

There is a stereotype of “AI Native” fresh college graduates who outperform experienced developers. There is some truth to this. Multiple times, I have hired, for full-stack software engineering, a new grad who really knows AI over an experienced developer who still works 2022-style. But the best developers I know aren’t recent graduates (no offense to the fresh grads!). They are experienced developers who have been on top of changes in AI. The most productive programmers today are individuals who deeply understand computers, how to architect software, and how to make complex tradeoffs — and who additionally are familiar with cutting-edge AI tools.

Sure, some skills from 2022 are becoming obsolete. For example, a lot of coding syntax that we had to memorize back then is no longer important, since we no longer need to code by hand as much. But even if, say, 30% of CS knowledge is obsolete, the remaining 70% — complemented with modern AI knowledge — is what makes really productive developers. (Even after punch cards became obsolete, a fundamental understanding of programming was very helpful for typing code into a keyboard.)

Without understanding how computers work, you can’t just “vibe code” your way to greatness. Fundamentals are still important, and for those who additionally understand AI, job opportunities are numerous!

Keep building,
Andrew