Right now there’s a temporary mismatch between the jobs that used to be sought after in some fields and the new jobs that are becoming in demand in those fields. For instance, if you studied CS, for years the general direction of travel was often to join a tech company and build customer-facing software in some form. A significant portion of the CS pipeline from college to hire was built for this. When you realize that AI is going to make coding abundant, you realize everyone will need technical talent to implement agentic systems. This means the types of roles engineers should be thinking about radically expands. I was talking to a Fortune 500 pharma CEO a week ago that commented on how much more technical talent they need right now. The job may be different from what it was 5 years ago when thinking about tech, but the demand for the skills are still there. And this is what I’m hearing from every CIO and CEO across nearly every industry right now. We definitely need colleges to wake up to this; but we equally need companies think about how they craft pipelines into these jobs.
眼下，在某些领域里，过去热门的岗位与这些领域中正在变得抢手的新岗位之间，存在一种暂时性的错配。比如，如果你学的是 CS，很多年来，大方向往往是加入一家 tech company，去构建某种面向客户的软件。大学到招聘之间，相当大一部分 CS 人才输送链路都是围绕这个目标建立的。当你意识到 AI 会让 coding 变得极其充裕时，你也会意识到：每个组织都将需要 technical talent 来实施 agentic systems（智能体系统）。这意味着，工程师应该考虑的岗位类型会急剧扩展。一周前我和一位 Fortune 500 pharma CEO 聊天时，他提到他们现在需要多得多的 technical talent。这个岗位也许已经不同于 5 年前人们谈论 tech 工作时的样子，但对这些技能的需求依然存在。而且，这也是我现在从几乎每个行业的 CIO 和 CEO 那里反复听到的。我们当然需要 colleges 尽快意识到这一点；但同样也需要 companies 去思考，如何为这些岗位打造人才输送 pipeline。
One of the best things students and colleges can do is not bail on learning and teaching the fundamentals of any given domain. AI will trick you into thinking you don’t need to go deep in a particular area, but that’s wrong. The expert with AI is always going to be far more capable than the novice. Those that can steer AI agents properly, figure out how to evaluate their work, fix their mistakes, and incorporate their work into a workflow will always be the most potent users of these tools. The experienced software developer that’s built and scaled complex systems using agents outrun someone just vibe coding. The designer that uses AI will build far better products and campaigns than anyone else. The banker or analyst that understands financial models will be able to pull off far more with agents. Despite some of the rhetoric in the valley that this is less implement now, that couldn’t be further from the case. Don’t give up on going deep in your craft.
学生和 colleges 最该做的事情之一，就是不要放弃学习和教授任何特定领域的 fundamentals（基本功）。AI 会诱使你以为自己不需要在某个具体方向上钻得很深，但这是错的。掌握专业能力又会使用 AI 的 expert，能力始终会远远强于 novice（新手）。那些能够正确引导 AI agents、知道如何评估它们的工作、修正它们的错误，并把它们的产出纳入工作流的人，永远都会是这些工具最有威力的使用者。一个使用 agents 构建并扩展过复杂系统的资深 software developer，会把那些只会 vibe coding 的人远远甩在后面。会使用 AI 的 designer，会做出比其他人好得多的产品和 campaign。理解 financial models 的 banker 或 analyst，将能够借助 agents 完成多得多的事情。尽管 valley 里有一些论调好像在说，现在没那么需要落实执行了，但事实恰恰完全相反。不要放弃在你的手艺上深耕。