I’ve been deep in the process of building my AI-driven hair styling application, “Today’s Hair Glimpse.” Like many developers, I’ve been enjoying the convenience of vibe coding—letting AI handle much of the implementation while I focus on the overall direction. But recently, I hit a wall that became a valuable reminder.

The Problem: Constraints and Clipping

The hair segmentation logic was failing in two ways.

First, the hair mask detected only the upper portion of the hair, causing the hairEndY coordinates to stop far too early.

Second, the rendering pipeline was constrained by a destination-out compositing operation. The AI had effectively cut a hole in the layer corresponding to the original hair, forcing the newly rendered hair strands to remain inside that masked region. Naturally, the strands couldn’t extend beyond the original hair boundary.

The “Fix” That Wasn’t

The AI proposed two solutions.

Interpolation: Filling the missing -1 values in hairEndY by borrowing values from neighboring columns—a reasonable way to compensate for missing measurements.
Refactoring the compositing pipeline: Moving the hair rendering to the main canvas so the strands could extend freely beyond the original mask.

Both ideas sounded perfectly reasonable, and I implemented them.

But the rendering still didn’t look right.

As I reviewed the AI’s explanation again, I realized the underlying architecture itself was fundamentally flawed. The hair segmentation layer was being placed above the original photo.

The Turning Point

I asked the AI:

“Doesn’t placing the segmentation layer on top of the original image block the photo?”

The AI paused, re-evaluated the architecture, and replied:

“You are absolutely right. I will refactor the code to correct this.”

At that moment, everything clicked.

The Lesson: Never Let Your Guard Down

That experience reminded me of one important lesson: never become too comfortable with vibe coding.

It’s easy to trust AI when it speaks confidently and offers technically plausible solutions. But AI can become so focused on solving local problems that it overlooks fundamental architectural flaws.

Vibe coding is an incredibly powerful way to build software, but it is not a replacement for critical thinking. As developers, we still need to verify the logic, challenge assumptions, and recognize architectural issues that AI may miss.

AI is an incredible pair programmer—but it is still my responsibility to validate the architecture, question the assumptions, and make the final decisions.