The Elevator and the Stairs: A Software Engineering Perspective
Generative AI is changing the pace of software development. Teams are shipping faster, junior developers are producing production-grade code, and AI copilots are embedded into nearly every workflow. The future has arrived and is advancing at unprecedented speed. However, without proper engineering foundations, this velocity can lead to instability.
At RBA, we believe that AI doesn’t replace experience. It amplifies it. And in a world where GenAI is writing more code than ever before, experienced engineers are the steady hand that turns that code into scalable, sustainable systems.
Let’s break down why senior engineers remain critical, especially now.
Generative AI is the Elevator. Experienced Engineers Are the Stairs.
Think of GenAI as an elevator: fast, convenient, and capable of accelerating progress in ways that were unthinkable just a few years ago.
But just like any building that includes an elevator, it still needs stairs. The stairs are what you depend on when the elevator breaks down. They’re reliable. They’re grounded. And they’re often the only way forward in an emergency.
In modern software development, experienced engineers are the stairs.
Why Experience Still Powers the Infrastructure of Good Software
AI Needs a Foundation to Build On
Even the most advanced GenAI coding tools depend on solid system design principles. Security architecture, performance optimization, and integration reliability. These aren’t things AI tools can fully own. When AI generates buggy or bloated code, it’s experienced engineers who debug, refactor, and course-correct.
AI Can Get You There Faster—But Engineers Know Where “There” Is
We’re seeing more “vibe coding”. Developers using GenAI to generate code without understanding the problem they’re solving. It’s like stepping into an elevator and pushing a random button. It moves. It’s working. But where are you actually going?
Experienced engineers bring the architectural vision. They ensure that what’s being built solves the right problem, integrates with existing systems, and scales with the future in mind.
Experience Fills the Gaps AI Can’t See
AI models have limitations, including knowledge cutoffs, hallucinations, and difficulty with novel integrations. When tools hit those walls, experienced engineers step in. They’re trained to handle complex systems, critical bugs, and high-pressure environments—without relying on autocomplete.
You Can’t Retrofit Innovation Without Understanding Legacy
Legacy applications weren’t built for GenAI. Enhancing or modernizing these systems is like installing an elevator in a historic building. It requires deep knowledge of what can be safely updated and what must remain intact.
Senior engineers understand:
- Legacy dependencies and how to work around them
- Institutional knowledge buried in decades-old code
- How to layer modern AI functionality without compromising system integrity
Future-Proof Systems Start with Smart Architecture
Today’s GenAI tools are impressive, but tomorrow’s will be even more powerful. Experienced engineers design with that future in mind. They utilize patterns, interfaces, and abstractions that support new models as they emerge, without requiring the need to rebuild everything.
It’s not about hardcoding for today’s tool. It’s about architecting for what’s next.
Better Prompts Come from Deeper Experience
The quality of AI-generated code is only as good as the prompts it’s given. Engineers who’ve built, broken, and fixed complex systems know:
- What edge cases to test
- Where vulnerabilities hide
- How to craft prompts that generate usable, maintainable, and performant code
This experience doesn’t just make AI tools more useful. It transforms them from novelty into a strategic advantage.
The Real Opportunity: Elevators and Stairs Working Together
GenAI is an accelerator, but experienced engineers are the guide rails. You don’t have to choose between them. In fact, the smartest teams build with both.
Let GenAI automate the repetitive. Let your senior engineers focus on design, direction, and stability. Let them lead when things break or change, because they always will.
The future of software isn’t AI or human. It’s AI enhanced by human expertise.
TL;DR: Generative AI is powerful, but experienced engineers make it production-ready.
You need both. The elevator for speed. The stairs for safety. And the right strategy to combine them.
Ready to move fast, without falling behind?
At RBA, we bring the strategy, engineering depth, and AI expertise to help you scale with confidence. Whether you’re modernizing legacy systems or integrating GenAI into your development workflow, we’ll help you move with speed and build with stability.
About the Author
Mike Siers
Senior Data Engineer
Mike is a Senior Data Engineer at RBA, with years of experience building data-driven solutions using a variety of languages, frameworks, and cloud platforms. He has worked on all stages of product development, from custom hardware for data collection to data analysis and the application of machine learning models. He is a lifelong learner who has degrees in Computer Science and Mathematics and enjoys living in and exploring the northern woods of Minnesota on foot and by paddle.