In our recent articles at Inclusion Cloud, we’ve been exploring how AI is reshaping everything from how we hire developers to how we design and ship digital products. One topic that has sparked a lot of attention is vibe coding — a trend that goes beyond the developer world and is now being used by non-developers and junior devs alike to generate code using AI.
And let’s be clear: the idea of using AI to accelerate software creation isn’t inherently bad. In fact, in The AI-Augmented Developer, we talked about how certified, experienced developers can use AI tools to boost productivity while still maintaining high standards for quality, testing, and architectural soundness. That’s a very different mindset from relying entirely on AI outputs without real understanding.
The problem starts when this quick-code approach is adopted without deeper architectural thinking. Writing code isn’t the same as developing software, and that gap becomes painfully obvious as projects grow.
From Vibe Coding to Vibe Architecture: Where Do We Draw the Line?
The issue isn’t just speed. It’s what gets left behind in the process. Vibe coding is great at helping you write functions, generate components, or patch together APIs, but it doesn’t think in systems. It doesn’t weigh trade-offs. It doesn’t align with business logic or long-term scalability.
What we’re seeing now is a new risk: when developers (or teams) start to apply this same mindset to architecture.
We’ll call it vibe architecture.
That’s when architectural decisions are made on the fly, based on convenience or the latest AI output, rather than real design thinking. The result? Systems that may work today, but quickly become brittle, hard to scale, or impossible to maintain tomorrow.
If you’ve read our piece on AI-generated code and technical debt, you’ll see this is a natural progression. Quick code without context leads to messes that experienced teams have to clean up later.
What is software architecture?
At its core, software architecture is the high-level design of a software system. It answers questions like:
- How do the different parts of the system interact?
- What patterns and principles will guide our decisions?
- How will we ensure scalability, security, and maintainability?
But it’s more than just structure—it’s judgment. Architecture isn’t just about drawing pretty diagrams or pleasing a stakeholder with a slick presentation. It’s about shaping a system through deliberate thinking, asking the right questions, and evolving your design as new constraints emerge.
And that process isn’t reserved only for people with the title “architect.” In many teams, senior engineers contribute heavily to architectural decisions. In fact, the more experience an engineer has, the more time they spend thinking about the bigger picture, rather than the next function or feature.
Designing a system from scratch can feel overwhelming. It’s a mix of method and instinct, and sometimes feels more like art than engineering. You’re not just assembling parts, you’re weaving together reliability, security, usability, scalability, and constraints you haven’t even seen yet.
What’s Changing with Vibe Coding?
Vibe coding is enabling people with limited coding experience to generate more code in less time. That’s a win for speed, and sometimes for cost. But it also creates a false sense of completeness.
There’s a common fear among developers that AI might replace them. But that fear tends to focus only on the part where AI generates code. In reality, writing code is just one part of software creation, and arguably not even the hardest.
The deeper challenge is making that code part of a system that works at scale, evolves safely, and doesn’t crumble under real-world use.
Code that “works” in the short term might have:
- Poor separation of concerns
- Overlapping responsibilities
- Hidden coupling between modules
- Zero visibility into performance, observability, or security
In other words: it runs, but no one knows how or why. And that’s a dangerous place to be.
We’ve seen this firsthand in projects where systems were built quickly using AI tools, only for teams to realize later that they had to re-architect everything to scale or integrate properly. And that’s a budget and timeline killer.
Can AI replace software architects?
A recent experiment tried to answer that question by putting four different LLMs to the test on a software architecture challenge.
The outcome? Predictable. The LLMs produced similar, high-level results with very little discussion of trade-offs. Scalability and observability were mentioned, but deeper characteristics like maintainability or domain-driven design? Not so much.
So the real question isn’t “Can I use AI to code a solution?” It’s “Can AI actually generate a meaningful blueprint for an entire system?” And right now, the answer is: not really.
AI can be helpful for brainstorming, but it can’t reflect, iterate, or challenge itself in the way humans do. It doesn’t really know how to weigh options or ask “What am I missing?”—a question that experienced architects ask constantly.
Architecture lives in that space between discovery and refinement. It’s shaped by experience, trade-offs, and the ability to see beyond what’s visible in a single prompt. That’s still very much a human skill.
How We Help at Inclusion Cloud
At Inclusion Cloud, we help companies build and scale digital products with senior, certified, and computer science-trained professionals. That means real developers with architectural thinking, not just prompt engineers.
Whether you’re building a new platform or cleaning up a system built on AI-generated quick wins, we help you:
- Design scalable, maintainable architectures
- Integrate AI tools responsibly into your workflows
- Build teams that combine speed with strategy
We’re not anti-AI. We’re pro-quality. And we believe the future of software lies in knowing where AI helps, and where human thinking still leads.
Need help building architecture that lasts? Contact us and let’s talk about how we can support your team.
If you liked this piece, check out more of our thoughts on: