In the last post, we talked about why “vibe coding” — throwing a vague description at an AI and hoping for the best — usually doesn’t work. The AI doesn’t understand your vision. It can only work with what you give it.

So what does work?

The answer is surprisingly simple, and it has nothing to do with AI. It’s a skill that engineers and project managers have used for decades: breaking big problems into small pieces.

You Already Know How to Do This

Imagine you’ve just been hired to build a new app for a client. They walk into the meeting and say, “We want something modern and innovative that really disrupts the space.”

You don’t walk out of that meeting and start coding. You ask questions. What does it actually do? Who uses it? What’s the most important feature? What does success look like?

You break their big vision down into specific, concrete steps. You make a list. You draw diagrams. You figure out what needs to happen first, second, and third.

That process — turning a fuzzy idea into a clear plan — is exactly what you need to do before you type a single word into an AI chat window.

The AI is like a highly skilled contractor. It can build almost anything, incredibly fast. But it can’t read blueprints that don’t exist yet. That part is your job.

What “Breaking It Down” Actually Looks Like

Let’s say you want to build a simple to-do list app.

Don’t ask the AI: “Build me a to-do list app.”

Instead, think about what that app actually needs:

• A way to add a new task
• A way to mark a task as done
• A way to delete a task
• A list that shows all tasks

Now you have four separate pieces. Each one is small enough for the AI to handle cleanly. Ask for them one at a time, test each one, and build up from there.

This approach might feel slower at first — but it actually saves time. You catch problems early, before they pile up. And you always know exactly where you are in the process.

Why This Changes Everything

When you give the AI a clear, specific task, it performs dramatically better. It’s not guessing anymore — it’s executing. And when something doesn’t work, it’s easy to figure out why, because you were only asking it to do one thing.

Think of it like this: you get much better results asking a contractor to “install a door in this specific opening using these measurements” than asking them to “make the house feel more open.”

Same idea. Specific instructions get specific results.

Next Up: Let’s Actually Build Something

In the final post in this series, we’ll put this into practice. I’ll show you a simple, repeatable framework for turning your plan into working code — step by step, piece by piece — using AI as your build partner rather than your mind reader.