Have We Reached The End of Software Engineering?

By Raimund Laqua, P.Eng

The End of Software Engineering?

I've spent over three decades practising engineering in both Canada and the United States, and what I've witnessed represents something I, along with others, have been slow to understand.

The death of software engineering isn't only a result of artificial intelligence, or perhaps ineffective engineering governance—it's also because information technology itself is reaching the end of its natural life-cycle. The technological era that needed it has run its course.

The Decline of Engineering in Canada

Over my career, I kept hearing "We don't do engineering in Canada anymore." For years, I brushed this off as professional griping. Turns out I was wrong.

Working across different sectors and organizations, I learned that while we were still building things, we weren't building them like engineers anymore. This was especially true in Canada. We'd stopped engineering the big infrastructure projects that define industrial nations—refineries, pipelines, nuclear plants, major data centres. Most of our work had shifted to maintaining and operating what earlier generations had actually engineered and built.

So when people said engineering was dying, they had a point—at least when it came to designing new infrastructure and mission-critical systems.

Information Era at Its End

The software world showed this decline even more clearly. What I've come to realize is that information technology itself was hitting the end of its life-cycle as a technological pursuit. You could see it everywhere, but nowhere more obviously than in the rise of Agile methodology.

Agile wasn't just push-back against heavy processes—it was information technology's death rattle as an engineering discipline. When any field abandons systematic design in favour of rapid iteration and "working software over comprehensive documentation," it's telling you that the core engineering problems have been solved.

This is exactly why software engineering struggles to establish itself as a legitimate engineering discipline. We were trying to professionalize a field just as its fundamental engineering challenges were disappearing. The infrastructure was already built and waiting in the cloud. Design patterns were baked into frameworks. Deployment was increasingly automated. Unless you worked at one of the few companies still tackling basic computing problems, genuine engineering work had largely vanished.

Agile just made this official. It acknowledged that you could build most systems through iterative assembly rather than systematic engineering. The methodology wasn't improving our practice; it was adapting to a world where the engineering had already been done by others.

The Dawn of Intelligence Technology

I was one of the people fighting to revive software engineering as a profession. I believed we could bring back engineering discipline to software development. But sitting here now, I think I was fighting the wrong battle.

What I see today isn't the revival of software engineering, but something bigger: the end of the information technology era and the start of the intelligence technology era. AI isn't just another tech advance—it's a fundamental paradigm shift like going from mechanical to electrical engineering, or from electrical to information technology.

Unlike the commoditized world of cloud computing and agile development, AI systems need real engineering thinking. They force us to understand complex systems, manage uncertainty, design for safety, and deal with behaviours that emerge in ways we can't always predict—behaviours that can have serious consequences for society.

The stakes are enormous. AI systems are being deployed in critical areas—healthcare, transportation, finance, criminal justice—often without the engineering oversight we'd require for any other system with similar potential for harm. We're seeing biased algorithms, unreliable predictions, systems that fail in unexpected ways, and growing public distrust of automated decisions.

Digital Engineering: The Next Generation of Software Engineering

This is where digital engineering becomes essential. Digital engineering is the systematic application of engineering principles across evolving digital paradigms—from information technology to intelligence technology and whatever comes next.

As engineers, we need to establish digital engineering as a proper discipline with clear practice standards, professional accountability, and systematic approaches to managing risk. This means developing methods for analysing requirements in uncertain environments, design patterns for safe AI systems, testing frameworks that can handle non-deterministic behaviours, and maintenance practices for systems that keep learning and evolving.

The death of software engineering isn't a failure—it's the natural end of information technology's life-cycle. But this ending marks the beginning of something far more significant: digital engineering as the discipline that adapts engineering rigour to whatever digital paradigm emerges: AI systems, cybersecurity, machine learning, compute and inference engines, and even existing cloud technologies.

We stand at the threshold of the AI era. The question is whether we'll build these systems with proper engineering discipline from the start, or repeat the same mistakes that left software engineering struggling for legitimacy. Digital engineering gives us the framework to get it right this time—if we choose to use it.

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About the Author:

Raimund Laqua, P.Eng, is a professional computer engineer with over 30 years of expertise in high-risk and regulated industries, specializing in lean methodologies and operational compliance. He is the founder of Lean Compliance and co-founder of ProfessionalEngineers.AI, organizations dedicated to advancing engineering excellence.

As a Professional Digital/AI Engineering Advocate, Raimund champions proper licensure across the entire spectrum of digital engineering disciplines. He actively contributes to the profession through his leadership roles, serving as AI Committee Chair for Engineers for the Profession (E4P) and as a member of the Ontario Society of Professional Engineers (OSPE) working group on AI in Engineering, where he helps shape the future of professional engineering practice in the digital domain.