How Do We Stay Relevant as Software Engineers in the Age of AI?

If you work as a programmer or software engineer today, there is a question worth asking yourself:

“How do I make sure my skills are still valuable three years from now?”

I have always known that professions can disappear, evolve, or become something entirely different. But I rarely thought about what happens to the people who have spent their lives working in them.

Do they hold on for as long as possible, convincing themselves that their experience makes them irreplaceable? Do they try to adapt without knowing where to begin? Or do they take a step back and explore a different path?

Recently, I have started to see myself in that position.

That has led me to a difficult but necessary conclusion: I need to be honest about what is changing, question my assumptions, and explore alternatives early.

Three Years May Be a Generous Timeline

The public launch of ChatGPT marked a turning point in how many of us understood the potential of AI. What has followed shows how much can change in a relatively short period.

That makes the three-year question feel almost optimistic. Perhaps we should also be asking what our work will look like in a year, or even six months.

I do not claim to know how this will unfold. My perspective may turn out to be wrong. But I see three possible paths worth investing in today.

1. Build Something People Will Continue to Need

One path is to use your technical skills to create a product or service that solves a real problem and gives people a reason to pay for it.

That could mean using technology to support a physical product, deliver a practical service, or address a need that AI alone cannot fulfil.

AI can help you build the supporting tools faster. But the lasting value needs to come from the problem you solve and the quality of what you deliver.

Before investing your time, ask yourself:

  • Does this solve a real problem?
  • Will people pay for it?
  • Could AI easily replace the service itself?

The opportunity is to use AI to build something whose value extends beyond the software behind it.

2. Become the Engineer Who Can Bring Everything Together

When I say software engineering will be affected, I do not mean companies will stop hiring engineers altogether.

I believe companies will still need people who take responsibility for the final result: understanding the requirements, making technical decisions, and ensuring that a product works reliably.

But teams may become smaller. Work that once required 50 people might eventually be handled by five or ten. Those numbers are illustrative, but the possibility matters: fewer roles could mean greater competition and higher expectations.

The engineer who stands out will be able to connect the pieces. They will understand the business problem, choose suitable tools, design a sound architecture, and turn it into a working product quickly.

Preparing for that requires a balance between two things:

Strong engineering fundamentals and practical fluency with AI tools.

You need to understand the software you build, even when AI helps write it. You should be able to explain its design, identify its weaknesses, maintain it, and change it when requirements evolve.

That means investing in both your technical foundations and your ability to deliver with the tools becoming available.

3. Explore a Path into AI Engineering

I expect major technology companies to continue investing in AI models and the systems around them. That could create opportunities for engineers who can develop, evaluate, and improve those systems.

However, those opportunities may not be numerous enough to absorb everyone whose work is affected elsewhere.

Still, if this field interests you, it is worth starting now. A structured learning path in machine learning and AI engineering could help you build the knowledge and practical experience needed to pursue those roles.

The important thing is to approach it as a serious investment in your skills, with a clear understanding of the work you want to do.

Start Preparing Before You Have To

I cannot predict exactly what software engineering will look like in three years. But I do not want to rely on the assumption that my current experience will always be enough.

For me, the response is to keep learning, build things that solve meaningful problems, and stay willing to change direction.

The question I keep coming back to is:

“What am I doing today to make sure I can still contribute tomorrow?”