“Vibe coding” is the term for a workflow that’s become common fast: describe what you want, let AI write it, ship it, move on. Here’s how we actually use AI for development at Yugantix, and why the difference matters.
We don’t paste AI-generated code directly into a project and hope it works. It goes into the editor first. We read it, understand what each part does, and only then does it go into the codebase. After running it, we check the files again — what changed, why, and whether it actually makes sense for this specific project.
That extra step takes longer. But after 17 years of writing code before AI existed, here’s what that time teaches you: speed without understanding doesn’t save time. It delays the cost.
What the data actually shows
This isn’t just a personal preference — recent research backs it up. AI-generated code shows nearly double the major bugs compared to human-written code, and meaningfully higher rates of security vulnerabilities. Teams that vibe their way to a working product often hit a wall months later: a fragile codebase that nobody — not even the person who built it — fully understands.
“AI hasn’t replaced the judgment part of development. It’s made the judgment part more important, not less.”
Why this is how we work
This is the whole reason review stays a real step in our process rather than a formality, even on AI-assisted work. The model can generate a plausible-looking solution in seconds. It can’t tell you whether that solution fits how your specific system is actually built, whether it’s introducing a security gap, or whether it’ll make sense to whoever has to maintain it a year from now. That judgment is still entirely human work, and it’s the part we’re actually being hired for.
The takeaway
If you’re using AI to code — your own team, or evaluating a vendor who does — the real question isn’t how fast you can ship. It’s whether you, or they, will understand what got shipped six months from now, when something breaks.
