We’ve been building software for 26 years. We’ve seen plenty of trends come and go. Some stick because they work. Others are just noise.
AI-powered development tools? Definitely not noise. They’re real, powerful, and we use them every day. But here’s the thing: AI is making us faster at solving problems, not replacing the need to actually solve them.
The Real Benefits (We’re Seeing Them)
Our developers use AI tools like GitHub Copilot and Claude for the repetitive stuff that used to eat hours. Boilerplate code? Seconds. Documentation that took half a day? Done in 20 minutes. Standard functions we’ve written a hundred times? Instant.
Recent studies show 15-30% productivity improvements. Google’s CEO noted over 25% of their new code is AI-generated. We’re seeing similar gains—but those gains come from developers using AI as a tool, not as a replacement for engineering judgment.
For our clients on retained development, this means we iterate faster, test more thoroughly, and spend less time on grunt work. More value per hour.
The Vibe Coding Trap
Now let’s talk about “vibe coding.”
It’s the idea that you can describe what you want in plain English, let AI generate code, and ship it. No need to understand it. No careful review. Just vibes.
This is a disaster waiting to happen.
Recent studies found AI-generated code often includes security vulnerabilities, outdated dependencies, and technical debt that costs more to fix than proper development would have cost initially. One developer spent a month reviewing a “vibe-coded” pull request. Another had an AI agent delete their production database because it decided the database “needed cleanup.”
Even Andrej Karpathy—the guy who invented “vibe coding”—recently admitted he hand-coded his latest project because AI “didn’t work well enough.” The guy who coined the term doesn’t trust it for real work.
Why Experience Still Matters
Here’s what people miss: coding is only about 24% of what we do.
The rest is understanding business processes, designing architecture, debugging complex interactions, anticipating edge cases, ensuring security, planning for scale, and translating real-world needs into working software.
AI can’t do that. Not even close.
What it can do is make experienced developers faster at implementation. It’s a smart assistant for tedious parts—but you still need the engineer who knows what to ask for, how to review output, and whether it solves the actual problem.
This is where 26 years of experience matters. We’ve built background investigation systems under Nuclear Regulatory Commission scrutiny. We’ve automated title industry workflows processing thousands of transactions. We understand business processes deeply—that doesn’t come from AI prompts. It comes from solving real problems for real clients.
How We Actually Use AI
AI tools are part of our workflow, but they’re amplifiers, not replacements:
Rapid prototyping: Quickly mock up different approaches to show clients. Three UI concepts in the time one used to take.
Code review: AI spots patterns we might miss, flags security issues, suggests optimizations. But humans make the final call.
Documentation: AI generates initial drafts we review and refine. Saves hours per week.
Testing: Helps generate comprehensive test cases, especially edge cases.
Refactoring: Suggests modern patterns when updating legacy code, identifies potential breaking changes.
The key word? Help. AI helps us. It doesn’t replace engineering, code review, testing, or architectural thinking.
What This Means for You
If you’re considering a software project, ask these questions:
“Are you using AI to go faster, or instead of proper engineering?” One accelerates timelines while maintaining quality. The other creates problems you’ll pay to fix.
“Do your developers actually review and understand AI-generated code?” If the answer isn’t “yes, thoroughly,” you’re building on a shaky foundation.
“Can you explain architectural decisions, not just show output?” Anyone can prompt AI to generate code. Engineers explain why that code is the right solution for your specific problem.
We’re excited about AI because it lets us do more of what we love: solving complex problems and building robust systems that work reliably. It doesn’t replace understanding your business, our architectural experience, or our commitment to maintainable, secure code.
The Bottom Line
AI is a tool. A powerful one. It’s making us faster, and that benefits clients directly through our retained development model. But software development is still engineering, not magic. Experience still matters.
We’re better at what we do now than we’ve ever been—partly because we’re using AI the right way. As tools, not crutches. As accelerators, not replacements.
Want to work with a team that combines decades of experience with cutting-edge tools? Let’s talk.
