As someone who’s weathered tech cycles, scaled legacy systems, and mentored more than a few generations of engineers, I find myself returning to a recent essay by Jonathan Hoyt: “The Uncertain Future of Coding Careers and Why I’m Still Hopeful”. Hoyt’s piece feels timely—addressing, with candor and humility, the growing sense of anxiety many in our profession feel as AI rapidly transforms the software landscape.

Hoyt’s narrative opens with a conversation familiar to any experienced lead or architect: a junior developer questioning whether they’ve chosen a doomed career. It’s a concern that echoes through countless engineering Slack channels in the wake of high-profile tech layoffs and the visible rise of AI tools like GitHub Copilot. Even for those of us long in the tooth, Hoyt admits, it’s tempting to wonder if we’re on the verge of obsolescence.

But what makes Hoyt’s perspective refreshing—especially for those further along in their careers—is the pivot from fear to agency. He reframes AI, not as an existential threat, but as an amplifier of human ingenuity. For senior engineers and system architects, this means our most valuable skills are not rote implementation or brute-force debugging, but context-building, system design, and the ability to ask the right questions. As Hoyt puts it, the real work becomes guiding the machines, curating and contextualizing knowledge, and ultimately shepherding both code and colleagues into new creative territory.

The essay’s most resonant point for experienced professionals is the call to continuous reinvention. Hoyt writes about treating obsolescence as a kind of internal challenge—constantly working to automate yourself out of your current role, so you’re always prepared to step into the next. For architects, this means doubling down on mentorship, sharing knowledge freely, and contributing to the collective “shared brain” of the industry—be it through open source, internal documentation, or just helping the next engineer up the ladder.

Hoyt’s post doesn’t sugarcoat the uncertainty ahead. The routine entry points into the field are shifting, and not everyone will find the transition easy. Yet, he argues, the need for creative, context-aware technologists will only grow. If AI takes on the repetitive work, our opportunity is to spend more time on invention, strategy, and the high-leverage decisions that shape not just projects, but organizations.

If you’ve spent your career worrying that you might be automated out of relevance, Hoyt’s essay offers both a challenge and a comfort. It’s a reminder that the future of programming isn’t about competing with machines, but learning to be amplified by them—and ensuring we’re always building, learning, and sharing in ways that move the whole field forward.

For anyone in a senior engineering or system architecture role, Jonathan Hoyt’s original piece is essential reading. It doesn’t just address the fears of those just starting out; it offers a vision of hope and practical action for those of us guiding teams—and the next generation—through the shifting sands of technology.