A lot of the conversation around AI and coding focuses on whether models will replace software engineers.
What seems to be happening in practice is slightly different.
AI is getting very good at generating code, but the hardest engineering problems were never about typing code in the first place. They’re about:
-system architecture and abstractions
-understanding complex systems
-reasoning about failure modes
-operating systems at scale
-deciding what should actually be automated
If anything, AI tools push engineers to start automating more of their own routine work, which frees time to focus on the harder system-level problems.
In that sense, the role of engineers shifts from “writing code” to designing and governing systems that increasingly include AI components.
Curious how others here see the role evolving as AI coding tools improve.
And so the low-code/no-code cycle spins another revolution.
It's been going since COBOL. Writing programs in COBOL was supposed to eliminate the need for programmers, as businesspeople could understand the code because it was written in English-like syntax. But, it turns out, looking like English isn't enough to make the computer work.
Later on were the form builders. Now anyone could put widgets on the screen. Making them do anything was still hard.
In the AI age, anyone can put widgets on the screen and they can do things, but making them do the right things well is still hard.
A lot of the conversation around AI and coding focuses on whether models will replace software engineers.
What seems to be happening in practice is slightly different.
AI is getting very good at generating code, but the hardest engineering problems were never about typing code in the first place. They’re about:
-system architecture and abstractions -understanding complex systems -reasoning about failure modes -operating systems at scale -deciding what should actually be automated
If anything, AI tools push engineers to start automating more of their own routine work, which frees time to focus on the harder system-level problems.
In that sense, the role of engineers shifts from “writing code” to designing and governing systems that increasingly include AI components.
Curious how others here see the role evolving as AI coding tools improve.
And so the low-code/no-code cycle spins another revolution.
It's been going since COBOL. Writing programs in COBOL was supposed to eliminate the need for programmers, as businesspeople could understand the code because it was written in English-like syntax. But, it turns out, looking like English isn't enough to make the computer work.
Later on were the form builders. Now anyone could put widgets on the screen. Making them do anything was still hard.
In the AI age, anyone can put widgets on the screen and they can do things, but making them do the right things well is still hard.