How to Write Prompts That Build Real Products (Vibe Coding Prompt Guide)

The best vibe coding prompts describe outcomes and symptoms in plain language — like a product manager talking to an engineer — instead of prescribing implementation. Say what should happen, not how to make it happen. That single shift is 80% of the game.

I've written thousands of prompts building real products. My students have written millions. The patterns that separate a fast build from a stuck one are surprisingly consistent. Let me hand them over.

The PM-not-programmer principle

Bad prompt: "Add a useEffect that sets isLoading to true when the fetch starts and false when it ends."

Good prompt: "When the user clicks Generate, show a spinner on the button until the image comes back."

Same result. Completely different prompt. The bad version tries to be the engineer. The good version is the product manager. Your job in vibe coding is to know the outcome. The AI's job is to pick the implementation.

When you prescribe implementation, you box the AI into a specific approach, often the wrong one for the codebase it's actually looking at. When you describe outcomes, you give it room to pick the best route.

The spec-first pattern

Before you write your first prompt, write a one-page spec. Not a design doc. Just:

• Who is this for?
• What's the first screen they see?
• What are the 3–5 core actions?
• What's the "success" moment?

Paste that spec as the first prompt. Skip this step and every prompt afterward is a shot in the dark.

I've watched students save days by writing the spec first. It's not procrastination. It's the actual work.

The small-commits pattern

One change per prompt. Even if you can imagine three changes. Even if the three feel related.

Why? When something breaks, you know exactly which change caused it. When you bundle three changes into one prompt and something breaks, you're now debugging three overlapping edits at once. It's a nightmare.

I break this rule maybe once a week and pay for it every time.

Describing bugs by symptom

The single fastest way to fix an AI-generated bug is to describe the symptom precisely. Not your theory of the cause. The symptom.

Bad: "Auth is broken."

Good: "When I click Login with a valid email and correct password, the page reloads and I'm sent back to the sign-in screen. No error message. Console shows: Uncaught TypeError: cannot read properties of undefined (reading 'user') at line 47 of AuthProvider.tsx. Screenshot attached."

The good version fixes itself in 90 seconds. The bad version takes an hour of back-and-forth.

Symptom first. Theory second. Fix third. In that order. Always.

10 real before/after prompts

Real ones from my projects. Vague → specific.

1. "Make it look better." → "Increase the vertical spacing between cards to 24px, and use a slightly darker shade of the background color for card surfaces."

2. "Add auth." → "Add email + password sign-up and sign-in using Supabase. After sign-up, send the user to /onboarding. Show clear error messages for wrong password."

3. "It's slow." → "The dashboard takes ~5 seconds to load. Network tab shows one fetch to /api/reports is 4.2s. Cache the reports call for 60 seconds."

4. "Mobile is broken." → "On iPhone Safari at 375px width, the top nav bar overlaps the hero heading. Add proper responsive breakpoints so the nav stacks below on screens under 640px."

5. "Save the data." → "When the user clicks Save, insert a row into the orders table with these fields: user_id (from auth), items (jsonb), total (numeric), created_at (now)."

6. "Add search." → "Add a search input at the top of the products page. Filter the visible product list by name (case-insensitive contains). Debounce input by 200ms."

7. "Fix the error." → "The console shows: Cannot read properties of null (reading 'map') at ProductGrid.tsx:24. This happens when the products query returns an empty array. Guard for that case and show an empty state."

8. "Make login secure." → "Turn on RLS on the orders table. Add a policy that only lets a user select, insert, or update rows where auth.uid() equals user_id."

9. "Add a chart." → "Add a bar chart showing daily order count for the last 30 days, using Recharts. Empty days should show 0. Tooltip should display date and count on hover."

10. "Improve the copy." → "Rewrite the hero heading to be under 8 words and emphasize speed. Rewrite the sub-heading to be one clear sentence about who this is for. Keep the tone confident but plain."

Prompting in Urdu-English mix

You do not need to write prompts in perfect English. Modern models handle Urdu-English mix well.

Real prompt from a student: "Login button pe click karne ke baad bhi kuch nahi hota. Console mein error hai: session is null. Please fix so that after login the user goes to /dashboard."

This works. It's specific. It has the symptom. It has the desired outcome. Don't let English fluency slow down your building. Your problem-clarity matters more than your grammar.

Common prompt anti-patterns

• The novel. A 400-word prompt with 12 requirements. Break it up. One change per prompt.
• The vague vibe. "Make it feel more premium." Feel is subjective. What specifically?
• The theory. "I think the bug is in the useEffect." Maybe. Just describe the symptom and let the AI investigate.
• The apology. "I'm sorry, I know this is silly but..." Just ask. The AI doesn't care.
• The stacked question. "Fix the bug and also add the feature and also refactor." Split it.

Putting it all together

Every real product I've shipped follows the same rhythm:

1. Write a one-page spec.

2. Paste it. Get a first draft.

3. Test. Break things on purpose.

4. Describe symptoms in one clear prompt at a time.

5. Ship.

Read my 72-hour Pixistan build to see this in action, and my complete vibe coding guide for the wider context.

If you want structured practice on this, come check out /vibe-coding.

FAQs

Do I need to know code to write good prompts?

No. It helps to understand what a database or an API is at a high level. But you do not need to write code yourself. You need to describe problems clearly. That's a language skill, not a syntax skill.

Are prompts different between Lovable, Cursor, and Bolt?

The style is the same. Small structural differences exist (Cursor loves explicit file paths, Lovable loves outcome descriptions), but the core discipline — describe outcomes and symptoms, one change per prompt — works everywhere.

What's the single most useful habit for prompt writing?

Before every prompt, ask yourself: "Am I describing what should happen, or am I telling the AI how to do its job?" If the second, rewrite. Ninety percent of stuck prompts fix themselves at this step.

Written by Usama Ghazi, CEO of Qawex Solutions.

I'm an International Vibe Coder based in Rawalpindi. I run Qawex Solutions, a Pakistan-first AI product studio building HealthTech, edtech, and automation tools. I've taught over 10,000 students how to build with AI, and I ship products with the same tools I teach — Vibelyflow, Osnify, Pixistan, and more. If any of this hits home, come say hi on WhatsApp or book a call.