In 2024 I created the LEAD podcast with my good friend Geert van der Cruijsen. In this podcast we explored the various aspects of building an engineering culture. We made quite some episodes. With guests and without guests. And I thought it would be a great idea to share some of these stories combined with my insights from these episodes on this blog. All credits do not go to me. They go to Geert as well, and to our guests. And of course to Xebia, the company I work for, for making this possible.

One of the things we talked about a lot in the past year is GenAI. Especially how it’s affecting the work of developers and architects. And honestly, one question kept coming back: will developers still have a job in a few years?

Are developers becoming obsolete?

I stumbled on an article that boldly claimed developers are out of business soon. And it triggered me. Is that really true? Because in my daily work, I use GenAI all the time. It’s incredibly helpful, especially in coding tasks and architecture discussions. But replacing us? I wasn’t so sure.

So Geert and I invited someone who knows the field inside out: April from GitHub. She’s been in the cloud and DevOps space for over a decade, and now works on developer experience and productivity using tools like GitHub Copilot.

Her answer was clear: no, developers are not going away. But your work is definitely changing.

Patterns repeat themselves

April reminded us of something important. We’ve heard this story before. When cloud arrived, people feared for their jobs. Same with virtualization, and later with containers. Each time, it wasn’t about being replaced. It was about adapting. AI is no different.

The core of our job as developers, architects, engineers hasn’t changed. We make decisions. We design systems. We think critically about trade-offs. That’s not something AI can do—at least not yet. GenAI gives suggestions, accelerates repetitive tasks, and acts like a supercharged rubber duck. But we’re still the ones in the pilot seat.

A junior that knows everything

The way we described Copilot in the episode really stuck with me. It’s like pair programming with a junior developer who somehow has access to everything ever written. But it’s still junior. It can make silly mistakes, or suggest code that doesn’t compile. So we still need to test, validate, and bring the right context.

And that’s where the real challenge is. If you ask the wrong question, you get a half-right answer. If you forget to give business context or overlook the architecture, Copilot can’t fill in those blanks. It doesn’t know your organizational structure, Conway’s Law, or your compliance constraints. It just knows code patterns.

Learning to work with AI

One important takeaway for me was this: not using AI might be a bigger risk than using it wrong.

If your peers use AI to complete a task in 30 minutes that takes you five hours, it’s only a matter of time before you fall behind. Just like in sports, technology shifts the baseline. It’s not about replacing humans, it’s about augmenting them.

So the real question becomes: how fast can you learn to work with it?

Prompting matters. Context matters. Iteration matters. The best developers I know don’t just ask AI to “write a unit test.” They keep asking, refining, and learning how to get the best result—just like they would with any tool or colleague.

Rolling it out is not just buying licenses

Another thing that stood out in our talk was the gap between management decisions and real developer adoption. Just buying Copilot licenses doesn’t magically make your team more productive. It requires cultural change. Education. Time to play and experiment. Communities where developers can share prompts, tricks, and frustrations.

Just like with DevOps, it’s not about tooling. It’s about process and mindset. And yes, that takes effort.

Where is this all going?

We asked April to look a bit into the future. And what she sees is not a world where AI replaces developers. It’s a world where AI is embedded throughout the development lifecycle. From writing and testing code, to reviewing pull requests, catching secrets, improving security, and even helping with documentation and collaboration.

And eventually, yes, maybe even fixing bugs and implementing simple features directly from issues.

But still under our guidance.

So… will you be replaced?

Here’s my take after this episode. Developers won’t be replaced. But developers who refuse to learn, experiment, and adopt new tools might be. It’s not about job loss. It’s about relevance.

If you want to stay in this field, invest in your own skills. Not just coding, but also in learning how to use GenAI effectively. How to give it better input. How to challenge its output. And maybe most importantly, how to stay curious and open to change.

Because at the end of the day, the thing that keeps you valuable isn’t just your ability to type out code. It’s your ability to think, to design, to collaborate, and to learn.

And AI, at least for now, can’t do any of those without you.

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The original Episode

If you want to listen to the original episode, you can listen to this