AI Won’t Take Your Job. But Someone Who Uses It Better Might
It’s a tough time to be a software developer. You have catastrophists wailing that AI will take your job. Deniers dismiss it as little more than autocomplete. Proponents hail it as the solution to all of your problems, and if you aren’t using it, you’re going to fall behind.
If you’re confused and uncertain, you’re not alone.
This post is about finding the middle ground. Where you don’t have to sacrifice your agency to the altar of AI, where you won’t be replaced by it, where you can do what you do best.
Not Just a Tool
You may be tempted to think of generative AI as just another productivity tool. Something to handle the boilerplate, the tedious parts of the job you can do in your sleep. It certainly can, but not if you approach it as a simple tool. Tools take explicit input and will give you the same output every time. There’s no guarantee of that with generative AI, even using a detailed prompt.
Instead think of it as a collaborator. A junior developer with lots of book learning but little experience of real-world systems. They understand the theory of clean code and architecture, they understand what design patterns are, but they don’t know how to apply them to real world problems, to legacy codebases with quirks and odd workarounds.
And like many inexperienced developers, instead of admitting when they don’t know something, they’ll give you an answer that sounds so plausible you’ll doubt yourself. Treat it like you would a junior developer. Verify the solution, question the approach, and give feedback until you arrive at the solution that fits.
Instead of being replaced by AI, you’re being promoted. You need to operate as a senior guiding a junior. Give them the context, give them the constraints, and review their work. Move beyond your role as a developer and embrace the challenges of an engineer.
Promote Yourself
Another common refrain is that software engineers will become little more than prompt engineers, but this undermines what prompt engineering actually is. It is defining your problem in terms detailed enough to get a predictable output.
Sound familiar?
Using the junior developer example - you wouldn’t give a junior developer a one line brief and expect a perfect implementation first time. You would break the problem down into actionable tasks, you would give them acceptance criteria, you would describe any context and constraints that affect the task. And if their first try wasn’t quite right, you’d guide them in the right direction.
By delegating some of the “how”, you can focus on the real problem, the “what”. And this is where your skills and experience can’t be replaced by AI. Software engineering is about understanding the problem well enough that you solve the right one.
Own It
For any developer that seeks to progress, the path to proficiency with AI is the same path you’re already on. Defining problems clearly, architecting solutions, guiding junior developers - these skills will enable you to get the best outcomes out of generative AI.
But the most important thing you bring to the table is accountability.
Generative AI doesn’t care about code. You do. You care about the experience for the end users, you care about the technical debt, you want to be proud of the work you produce.
So just like you wouldn’t immediately approve a code review without understanding what the code does and why, don’t accept everything generative AI produces without applying that same rigour and judgement.
Trust Yourself
It’s easy to be intimidated by AI. You might be focusing on one language or tech stack; it has instant access to a wealth of information on all of them. New vibe coded apps pop up daily. How can you compete?
The answer is that you don’t need to. How you add value is with the experience and judgement you have built over years of wading through legacy code, handling specialised client requirements, and recognising problems before they’re an issue.
Trust yourself. Focus on the stuff that really matters.
Still figuring out where you stand with AI? Join the discussion. Someone else in the same place might need to know they're not alone.