Aaron Levie：AI 智能体不会终结软件工程
The biggest misread of anyone predicting the end of software engineering was imagining that the world only needed a certain amount of software, and bringing aut
Box CEO Aaron Levie 反驳“软件工程将终结”的预测，认为 AI 智能体让几乎所有事物都变成软件，反而扩大了工程需求。他指出银行、生命科学、制造业的更多工作正呈现软件问题的形态，未来虽不再手工写代码，但几乎所有东西都是代码，懂代码的人处于极佳位置。
查看原帖Some observations about the "total" automation of software engineering: 1. There are more software engineers now than in 2025, and demand is growing. 2. Software engineers have never worked harder than they do now. 3. They largely don't write code anymore, agents write ~100% of the code. 4. The bottom line of the companies that employs these engineers…
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Some observations about the "total" automation of software engineering: 1. There are more software engineers now than in 2025, and demand is growing. 2. Software engineers have never worked harder than they do now. 3. They largely don't write code anymore, agents write ~100% of the code. 4. The bottom line of the companies that employs these engineers and agents (i.e. the terminal purpose of all this code) is typically not budging as a result of AI adoption. This is why you have to think in terms of systems. Automating one aspect of a system creates its own friction and moves the bottlenecks elsewhere.
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The biggest misread of anyone predicting the end of software engineering was imagining that the world only needed a certain amount of software, and bringing automation to the field would reduce the need for labor.
Exactly the opposite is happening where essentially most things are actually turning into software. Because agents can use tools, work with computers, write software on the fly, and process data like humans (but far faster), we can now throw “software” at problems that never could reasonably be digitized before.
What that leads to is the role of engineering taking on greater importance in the economy, because we can now engineer far more systems and processes than were possible before.
If you’re a bank trying to do new forms of trading, engineers are often your first bet. If you are in life sciences, you expect more and more research and lab work to be engineering centric. If you’re in manufacturing, you’re trying to automate more of the supply chain, all that is engineering. More and more work is shaped like software problems.
Yes we’re not going to be coding manually in the future. But almost everything will be code, which means those that understand it are in a fantastic position.