I think "backward-deployed engineers" might become one of the defining roles of AI-assisted software development. 🤖💻
We were promised that AI would remove the boring parts of coding. Instead, something slightly different seems to be happening.
AI generates the code.
The engineer reviews it. Questions the assumptions. Fixes the architecture. Finds the edge cases. Repairs the tests. Checks the dependencies. And sometimes rewrites a good part of it. 😅
That sounds like a strange inversion of software engineering.
But there is another side to it that I actually enjoy a lot: I'm learning constantly from AI-generated code. 🧠
I've always been the kind of developer who enjoys reading documentation, man pages, command references and API docs. So when Codex generates something I don't know, I don't just accept it. I look it up.
Every command I don't recognize. Every parameter I haven't seen before. Every API or method I'm not familiar with.
And surprisingly often, I learn something. Sometimes it's completely new to me. Sometimes it's a parameter I had forgotten existed because I hadn't used it in years. Sometimes it's simply a different way of using a tool I already know.
Recently, for example, Codex used Format-Hex in PowerShell in a way I hadn't used before.
Of course, my first reaction wasn't "great, let's ship it." It was: "Wait what exactly is this doing?" 😄
So I opened the documentation, checked it, experimented with it, and added another small thing to my toolbox.
That's why I don't see reviewing AI-generated code only as cleanup work. Done properly, it can also become a continuous learning loop.
The important distinction is whether you are reviewing the code or merely accepting it.
If you blindly accept generated code, you outsource understanding. If you inspect it, question it and verify what you don't know, AI can expose you to commands, APIs, patterns and techniques you might otherwise never encounter. 🔍
For prototypes, AI coding is already incredibly powerful. For large, long-lived systems, I'm still much more cautious.
Because code generation is cheap. Understanding a codebase is not.
And every line generated today becomes something somebody has to understand, maintain and debug tomorrow.
Maybe the future engineer is partly an architect, partly a reviewer, partly a "backward-deployed engineer" and partly a student again. 👨💻📚🤖
I'm actually quite happy with that last part.