I’ve heard senior architects dismiss AI-assisted development as “vibe coding for non-developers.”

I get it. I really do. You’ve spent twenty years learning the craft. You understand why certain patterns exist, when to break the rules, how to architect systems that actually scale. You’ve debugged production outages at 2 AM and refactored legacy code that made you question your career choices. You’ve earned your expertise the hard way.

And now some product manager is showing you code that Claude wrote in thirty seconds, asking if you can “just clean it up a little.”

The dismissal is understandable. But it’s also a career-limiting mistake.

The Quality Objection

Let’s address the obvious concern head-on: yes, AI can write sloppy code.

It can generate inefficient algorithms. It can miss edge cases. It can produce solutions that work but don’t scale. It can hallucinate APIs that don’t exist and confidently reference deprecated libraries. I’ve seen all of it.

But here’s what I keep coming back to: so can junior developers. So can offshore teams. So can that contractor you brought in for the Q4 crunch. We’ve always had quality variance in software development. That’s why code reviews exist. That’s why we have architects in the first place.

The difference isn’t that AI-generated code is uniquely flawed. The difference is speed. An AI tool can produce flawed code in thirty seconds that would have taken a junior developer three days. Your job as an architect was never to write perfect code. It was to ensure the system works, scales, and can be maintained. That job still exists. The inputs just got faster.

Who’s Guiding the AI?

Here’s the question that matters: who’s guiding the AI?

When a junior developer uses Copilot to scaffold a service, who decides whether that service should exist in the first place? Who determines the boundaries between microservices? Who thinks about failure modes, data consistency, and the downstream impacts on the rest of the system?

You do. Or at least, you should.

The architects who embrace AI aren’t delegating their expertise. They’re amplifying it. They’re using AI to handle the mechanical parts of implementation while they focus on the decisions that actually require twenty years of experience: system design, integration patterns, performance optimization, security architecture.

I didn’t just watch this play out. I lived it.

As the architect at Telos, I used Claude Code for everything: detailed documentation on Databricks pipelines, Terraform configurations, Azure infrastructure. I generated state diagrams for complex logic when we needed to build a legacy FTP process with ATPCO. When deployment issues cropped up in our pipelines, I’d use Claude Code to diagnose the problem faster than a traditional debug session, then guide my DevOps engineer to make the fix.

My 34 years of developer experience didn’t become obsolete. It got amplified. Like I was on steroids.

Here’s the thing that skeptics miss: I saw hallucinations as they were being generated. Because I knew the domain, I could catch when Claude was confidently wrong about an Azure configuration or suggesting a Databricks pattern that wouldn’t scale. A junior developer might have shipped that code. I knew better.

Over the past year, I’ve honed my prompting skills and sought out tools like spec-kit to make my toolbox the best I’ve ever owned. Not because the old skills stopped mattering. Because the new skills made the old ones more powerful.

That’s not a demotion. That’s an upgrade.

The Orchestration Shift

Think about how the role of “developer” has evolved over your career.

Twenty years ago, a senior developer needed to understand memory management, manual deployment processes, and probably some assembly language for performance-critical sections. Ten years ago, those same developers were learning to work with cloud services, containerization, and infrastructure-as-code. The “developer” job kept the same title while the actual work transformed underneath it.

The same thing is happening now. The architects who thrive in five years won’t be the ones who write the most elegant code by hand. They’ll be the ones who orchestrate AI agents to build systems that no individual could create alone.

Right or wrong, that’s where this is heading.

The skills that will matter: prompt engineering that actually works, understanding how to decompose complex problems into AI-manageable chunks, evaluating AI output for correctness and security, designing systems where AI-generated components can be safely integrated and tested. These aren’t lesser skills. They’re different skills. And the architects who develop them first will have a significant advantage.

The Real Risk

I’ve talked to senior developers who plan to ride out their careers doing things the traditional way. “I’ve got ten years until retirement. This will blow over by then.”

IMHO, that’s a dangerous bet.

The Agile transformation took five or six years to reshape the industry. Architects who dismissed it as “a fad for startups” in 2010 were struggling to find roles by 2015. The ones who adapted early became the Scrum Masters, the SAFe consultants, the transformation leads who commanded premium rates precisely because they’d embraced the shift before everyone else.

This transformation is moving faster. The tools are improving monthly. What felt like a toy eighteen months ago is now generating production code at companies you’d recognize. The “vibe coding” dismissal might feel satisfying today, but it’s aging poorly.

Your Experience Is the Moat

Here’s what I want every skeptical architect to understand: your domain knowledge doesn’t become worthless in an AI-first world. It becomes the differentiator.

AI doesn’t know your client’s business. It doesn’t understand why that legacy integration exists or what happens when the payment processor goes down. It doesn’t have context on the political dynamics between teams or the historical reasons for technical decisions that look questionable on paper.

You do. And that context is exactly what AI needs to generate useful output instead of generic solutions.

More importantly: your experience is what lets you catch the mistakes. When Claude hallucinates an API that doesn’t exist or suggests a pattern that won’t scale under load, a junior developer might not notice. You will. Your decades of pattern recognition become the quality filter that makes AI-assisted development actually work.

The architects who pair their domain expertise with AI orchestration skills will be exponentially more valuable. They’ll deliver in weeks what used to take months. They’ll prototype solutions in hours instead of days. They’ll become the translators between business intent and technical implementation, using AI as the bridge.

That’s not a diminished role. That’s a superpower.

The Bottom Line

The bottom line is this: the question isn’t whether AI writes good code. It’s whether you’ll be the one teaching it how.

The architects and senior developers who lean into this shift will define the next generation of delivery. They’ll be the ones building the AI-accelerated practices, establishing the guardrails, training the next wave of engineers to work alongside intelligent tools.

The ones who dismiss it as “vibe coding” will be competing for a shrinking pool of traditional roles. And that pool is draining faster than most people realize.

I’ve been in this industry for 34 years. I’ve seen technologies come and go, hype cycles inflate and deflate, trends that promised revolution and delivered incrementalism. This one is different. Not because the technology is more sophisticated (though it is). Because the adoption curve is steeper and the productivity gains are immediate and measurable.

Your twenty years of experience matter. But only if you’re willing to apply them in new ways.

The architects who figure this out will lead the next era of software development. The ones who don’t will be telling stories about the good old days.

Which one are you going to be?

John Doucette is the founder of The Disruption Brief, where he writes about the AI transformation reshaping IT professional services. With 34 years in the industry — from developer to CTO — he’s focused on helping PS firms navigate disruption before it’s too late. Connect with him on LinkedIn.