Master Fast AI-Assisted Prototyping With This Simple Hack

A client walked in last week with what he called a “ready-to-go” MVP. He’d spent the weekend using Cursor to build a complex test-tracking tool. “It just needs a few tweaks,” he told me, pointing at a screen that looked surprisingly polished. But when I tried to add a simple ICE score calculation, the whole thing disintegrated. There was no database schema, no consistent state management—just a pile of React components held together by the AI’s best guesses. Total nightmare.

I’ll be honest: my first thought was to just patch it. I figured I could wrap a few functions in a useEffect hook and call it a day. Trust me on this—that was a mistake. Within ten minutes, I was chasing race conditions because the AI-assisted prototyping had skipped the most important part of the process: the conceptual model. We’re in the era of “vibe coding,” and while it’s seductive, it’s also incredibly dangerous for enterprise UX.

The Trap of Building Without a Blueprint

In the world of Triple Diamond design, we often talk about Solution Discovery. This is the phase where you validate your core hypothesis before engineering starts. The problem is that many teams are now using AI to jump straight from a “vibe” to a live prototype. It’s like hiring a builder to start laying bricks while you’re still describing the house one sentence at a time. You might get a wall that looks great, but it won’t hold any weight.

This is especially true for enterprise applications. Unlike a simple B2C landing page, enterprise tools deal with complex data models and non-linear workflows. When you use pure vibe coding, you’re letting the LLM guess the relationships between your data. Here’s what a typical “vibe-coded” relationship looks like versus an intentional one:

// The "Vibe Coded" Mess: Loose associations and fragile logic
const bbioon_save_test = (testData) => {
  // AI guesses the relationship on the fly
  const ideaName = testData.productIdea; 
  localStorage.setItem(`test_${ideaName}`, JSON.serialize(testData));
  // Good luck syncing this later!
};

// The Intentional Way: Explicit conceptual model
class bbioonProductIdea {
  constructor(id, name) {
    this.id = id;
    this.tests = []; // Explicitly linked
  }
}

Avoiding the Lopsided Horse Problem

We’ve all seen the meme: a beautifully rendered horse’s head that turns into a stick figure at the back. That’s exactly what happens when designers over-invest in high-fidelity mockups without defining the underlying structure. AI-assisted prototyping should be used to enforce clarity, not hide ambiguity. If your prototype can’t handle a simple data sync, your final product won’t either.

The allure of vibe coding, a term popularized by Andrej Karpathy, is that it’s fast. And yeah, it is. But for complex systems, speed without a blueprint is just technical debt with a better UI. You end up with a “black box” that developers have to reverse-engineer later. It’s a classic case of saving time today to lose weeks tomorrow.

If you want to do this right, you need simple accessible UX research to define your intent before you even touch a coding assistant. You have to be the architect, not just the guy giving the prompts.

How to Prototype With Intent

  • Define the Schema First: Don’t ask the AI for a “test tracker.” Ask it for a system where “Tests” have a one-to-many relationship with “Product Ideas.”
  • Iterate on Logic, Not Pixels: Get the data flow working in a plain text environment before you worry about the CSS.
  • Document the Prompt Chain: Your prompts are your new specifications. Keep them structured so the engineering team knows exactly what you were thinking.

Look, I’ve spent 14 years in the trenches of WordPress and WooCommerce development. This stuff gets complicated fast. If you’re tired of debugging a prototype that’s built on nothing but vibes and just want your enterprise system to work, drop me a line. I’ve probably seen your exact mess before—and I know how to fix it.

In Part 2 of this series, I’ll show you the exact workflow I use to turn design intent into robust code without losing the “magic” of AI speed. Until then, stop vibing and start planning.

author avatar
Ahmad Wael
I'm a WordPress and WooCommerce developer with 15+ years of experience building custom e-commerce solutions and plugins. I specialize in PHP development, following WordPress coding standards to deliver clean, maintainable code. Currently, I'm exploring AI and e-commerce by building multi-agent systems and SaaS products that integrate technologies like Google Gemini API with WordPress platforms, approaching every project with a commitment to performance, security, and exceptional user experience.

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