Phase 4: When Things Break · 25 min · Any vibe coding tool

The Predict-Before-Reveal Debugging Habit

Before you paste the error to the AI, write down what you think is wrong. Even if you're wrong, the prediction builds the instinct.

Hiring signal: What changes when you use this: you develop debugging instinct — the ability to guess what's wrong before the AI tells you — which is the skill that lets you catch the AI when it's wrong.

What you will learn

Use the predict-before-reveal habit before asking the AI to debug
Write effective predictions using the 'I think the error is because...' format
Understand why wrong predictions are still valuable
Track how predictions get more accurate over time

Your Mission

Practice the predict-before-reveal habit 5 times and track whether your predictions get more accurate. Output: prediction_log.md.

You need: Any AI coding tool with a project you can build and break.

Time: 30 minutes.

Step 1: Learn the Habit (3 min)

Before pasting any error to the AI, write down your prediction:

"I think the error is because [your guess]."

One sentence. You don't need to be right. You just need to think before you reveal.

Example:

Error: TypeError: Cannot read properties of undefined (reading 'map')
Your prediction: "I think the data I'm trying to .map() over is undefined — maybe the API hasn't returned yet."
AI says: "The items variable is undefined because the API call is async and the component renders before data arrives."
Compare: Your prediction was close! You guessed the data was undefined and timing was involved.

Wrong predictions are valuable too:

Error: SyntaxError: Unexpected token '<'
Your prediction: "Missing closing tag in HTML template."
AI says: "The API is returning HTML instead of JSON — the < is from <!DOCTYPE>."
Compare: Wrong, but now you've learned: Unexpected token '<' often means "receiving HTML when expecting JSON."

Why predictions build skill
Predicting before revealing forces your brain to engage with the problem. Even when your prediction is wrong, the comparison between your guess and the actual cause creates a learning moment. Over time, your predictions get more accurate — and that's the skill that lets you catch the AI when its diagnosis is wrong.

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers Step 2: Build Something (5 min), Step 3: Run 5 Error Cycles (20 min), Cycle 1, Cycle 2, Cycle 3, Cycle 4, Cycle 5, Step 4: Reflect (2 min), Reflection, You're Done — plus a hands-on lab, quiz, and project artifact.

Create a free account to unlock Phase 0 and Phase 1 of every course — no credit card.