英文原文
As AI agents accelerate coding, what is the future of software engineering? Some trends are clear, such as the Product Management Bottleneck, referring to the idea that we are more constrained by deciding what to build rather than the actual building. But many implications, like AI's impact on the job market, how software teams will be organized, and more, are still being sorted out.
The theme of our AI Developer Conference on April 28-29 in San Francisco is The Future of Software Engineering. I look forward to speaking about this topic there, hearing from other speakers on this theme, and chatting with attendees about it. We're shaping the future, and I hope you will join me there!
It is currently trendy in some technology and policy circles to forecast massive job losses due to AI. Even if they have not yet materialized, these losses certainly must be just over the horizons! I have a contrarian view that the AI jobpocalypse — the notion that AI will lead to massive unemployment, perhaps even rioting in the streets — won't be nearly as bad as dire forecasts by pundits, especially pundits who are trying to paint a picture of how powerful their AI technology is.
Among professions, AI is accelerating software engineering most, given the rise of coding agents. According to a new report by Citadel Research, software engineering job postings are rising rapidly. So if software engineering is a harbinger of the impact AI will have on other professions, this expansion of software engineering jobs is encouraging.
Yes, fresh college graduates are having a hard time finding jobs. And yes, there have been layoffs that CEOs have attributed to AI, even if a large fraction of this was "AI washing," where businesses choose to attribute layoffs to AI, even though AI has not changed their internal operations much yet. And yes, there is a subset of job roles, such as call center operator, that are more heavily impacted. Many people are feeling significant job insecurity, and I feel for everyone struggling with employment, whether or not the cause is AI-related. And many other factors, such as over-hiring during the pandemic and high interest rates, have contributed to the slowdown in the labor market, and the notion that AI is leading to unemployment is oversimplified.
In software engineering, I see a lot of exciting work ahead to adapt our workflows. It is already clear that:
1. As AI makes coding easier, a lot more people will be doing it. 2. Writing code by hand and even reading (generated) code is not that important, because we can ask an LLM about the code and operate at a higher level than the raw syntax (although how high we can or should go is rapidly changing). 3. There will be a lot more custom applications, because now it's economical to write software for smaller and smaller audiences. 4. Deciding what to build, more than the actual building, is becoming a bottleneck. 5. The cost of paying down technical debt is decreasing (since AI can refactor for you).
At the same time, there are also a lot of open questions for our profession, such as:
- In the future, what will be the key skills of a senior software engineer? And for junior levels, what should be the new Computer Science curriculum?
- If everyone can build features, what skills, strategies, or resources create competitive advantage for individuals and for businesses?
- What are the new building blocks (libraries, SDKs, etc.) of software? How do we organize coding agents to create software?
- What should a software team look like? For example, how many engineers, product managers, designers, and so on. What tooling do we need to manage their workflow?
- How do AI agents change the workflow of machine learning engineers and data scientists? For example, how can we use agents to accelerate exploring data, identifying hypotheses, and testing them?
I'm excited to explore these and other questions about the future of software engineering at AI Dev. I expect this to be an exciting event. Please join us!
[Original text: The Batch newsletter.]
中文翻译
随着 AI 智能体加速编程，软件工程的未来将走向何方？一些趋势已经清晰可见，例如"产品管理瓶颈"（Product Management Bottleneck），即决定做什么比实际构建更受约束。但许多影响——比如 AI 对就业市场的影响、软件团队将如何组织等——仍在被逐步厘清中。
我们 4 月 28 日至 29 日在旧金山举办的 AI 开发者大会（AI Developer Conference）的主题正是"软件工程的未来"。我期待在那里就此话题发表演讲，听取其他演讲者的观点，并与参会者交流。我们正在塑造未来，希望你能加入！
目前，在一些科技和政策圈子里，预测 AI 将导致大规模失业蔚然成风。即使这些失业尚未发生，他们也坚信这只是"山雨欲来"。我的看法恰恰相反——AI 就业末日论（AI jobpocalypse），即 AI 将导致大规模失业、甚至街头抗议的观点，远没有评论家们（尤其是那些试图描绘自家 AI 技术有多强大的评论家们）所描绘的那么悲观。
在各职业中，受 AI 影响最大、加速最明显的是软件工程。 Citadel Research 的一份最新报告显示，软件工程职位需求正在快速增长。因此，如果软件工程是 AI 对其他职业影响的先行指标，那么软件工程岗位的扩张是令人鼓舞的信号。
当然，应届毕业生找工作确实很难。确实，有些 CEO 将裁员归因于 AI，即便这种"AI 洗白"（AI washing）在很大程度上并不属实——AI 实际上尚未真正改变这些公司内部的运营方式。确实，某些岗位（如客服）受到的冲击更大。许多人对就业感到不安全，我理解所有为就业而挣扎的人，无论原因是否与 AI 相关。疫情期间的过度招聘、高利率等许多其他因素也共同导致了劳动力市场的放缓，将失业归咎于 AI 过于简单化了。
在软件工程领域，我看到了许多令人兴奋的工作在等待着我们去适应工作流程。以下几点已经很清楚：
1. AI 让编程变得更容易，会有更多人参与到编程中来。 2. 手写代码乃至阅读（AI 生成的）代码已不那么重要，因为我们可以通过 LLM 来了解代码，在比原始语法更高的层次上操作（当然，我们能或应该达到多高层次正在快速变化中）。 3. 将涌现出更多定制化应用，因为现在为越来越小的用户群体编写软件在成本上变得可行。 4. 决定做什么，比实际构建，越来越成为瓶颈。 5. 偿还技术债务的成本正在下降（因为 AI 可以帮助重构）。
与此同时，我们的职业也有很多悬而未决的问题，例如：
- 未来，高级软件工程师的核心技能是什么？对于初级工程师，计算机科学课程应该有什么新变化？
- 如果每个人都能构建功能，什么技能、策略或资源能为个人和企业创造竞争优势？
- 软件的新构建块（库、SDK 等）是什么？我们如何组织编程智能体来创建软件？
- 软件团队应该是什么形态？例如，需要多少工程师、产品经理、设计师等？我们需要什么工具来管理他们的工作流程？
- AI 智能体如何改变机器学习工程师和数据科学家的工作流程？例如，我们如何利用智能体加速数据探索、识别假设并验证它们？
我期待在 AI Dev 大会上探讨这些以及关于软件工程未来的其他问题。这将是一场令人兴奋的活动，欢迎加入！
[原文：The Batch 新闻通讯]