When AI writes code

This year, my work completely changed. I remember when building software meant long nights of typing and solving problems line by line. Today, it feels like most of that work is done for me. I’ve noticed that roughly half of my code comes from AI suggestions. In practice, I spend far more time reviewing AI-generated code and designing system architecture than writing every line myself. It’s a strange new chapter in my life, raising big questions: what does it mean to be a developer when AI writes most of the code? How has our craft changed, and what remains uniquely human in this process?

AI-powered tools now handle many routine tasks like implementing the business logic. They can generate a basic component in seconds, but as one analysis notes, they are terrible at creativity, collaboration, and big-picture thinking. In other words, an AI can implement a method for you, but it won’t invent the core idea or vision behind a feature. In practice, this shifts the developer’s role. Industry experts put it like this: future developers will be orchestrators, strategists, and collaborators, valued for solving problems and designing systems rather than for typing speed. I feel this shift every day, as I find myself coordinating projects, guiding the overall design, and reviewing AI suggestions instead of writing code by hand.

All this means that human creativity and judgment come to the fore. Software development is, at its core, an art. AI can output code snippets, but it lacks the insight and context that humans provide - it truly can’t replace human insight, creativity, or collaboration. In practice I still have to ensure everything fits the larger goals and catch what the AI misses. For example, one study found roughly 40% of AI-generated code contained security vulnerabilities, so we must review and test all its output carefully. The final say about correctness and quality is still on us.

Of course, this shift also brings new challenges. The convenience of generating code can encourage bad habits: one report found a jump in duplicate code blocks as teams churned out fresh code instead of refactoring old ones. That creates technical debt I have to manage later. There’s also a funny risk of the “not my code” mindset: some developers might feel less responsible for a bug if an AI wrote the line.

But that attitude is dangerous; even if an AI wrote the code, someone still has to own and fix it. In practice, this means we have to keep our standards high and hold ourselves accountable for every line of code, no matter where it comes from.

And yet, I remain cautiously optimistic. By offloading the basic tasks, we can spend our energy on creativity and solving the hard problems that really matter. The core of being a developer - understanding real problems and crafting solutions - stays the same, and I believe this shift can ultimately make our work more meaningful, as we guide the vision while machines handle the grunt work.

Ultimately, AI may write a lot of code, but it doesn’t decide what we build or why. That responsibility still lies with us. I might spend my days reviewing AI-generated code and planning architecture, but it still feels very much like my own work. The craft has changed, but it hasn’t been replaced. In fact, this new era might let us focus on the most meaningful parts of our jobs. We just have different tools at our disposal - and a bit more responsibility to use them wisely.