A useful vibe coding prompt connects a request to observable behaviour. State the situation, expected result and what should be preserved. When correcting an application, explain what actually happens: this gives AI a clearer target than “improve everything”.
The first prompt sets the scope
Describe the user, task, inputs and expected output. Specify the limits of the first version too. If you want neither accounts nor storage, say so clearly, then have the resulting behaviour checked.
For example: “Prepare a lead-time calculator using three durations in days. Show the total and breakdown. Reject negative values. Use fictional demonstration data.” You can compare the answer with a manual calculation.
For a bug, explain how to reproduce it
Write the actions in order: “I fill in the four fields, view the summary and click Back. The second field is empty. I want to recover all my answers.”
Add the expected result and scope of the fix: “Correct answer preservation, then check that the summary and printing still work.” A screenshot can help, but may not show the actions that caused the problem.
For design, name the difficulty
“More modern” could produce a new colour scheme when the real problem is a hidden button. Describe the use: “On a phone, the main action appears after a long list. Make it visible when the sheet is complete.”
Ask for validated behaviour to be preserved. A visual improvement should also retain keyboard navigation, error messages and information order. Check the result in the situation that originally caused difficulty.
Ask for a plan before a large change
Before adding a connection, permissions or a new journey, start with: “List the affected elements, regression risks and checks to perform. Identify missing decisions before making changes.”
You now have a discussion point. Examine the AI’s assumptions: has it invented a role, formula or storage system? A well-written answer does not prove that its choices match your organisation.
Keep a record of decisions
A small log is enough: request, change made, test performed and result. As exchanges accumulate, summarise validated rules in the project. Avoid leaving an essential instruction only in an old conversation.
Before a significant change, save a working version. You can compare results and go back if needed. Your aim is to explain what changed, why and what evidence shows that it works.
Frequently asked questions
Is there a universal prompt?
A template helps avoid omissions, but the rules and criteria must come from your project. A generic formula cannot replace knowledge of the task.
Should you fix several problems at once?
Group problems that share a cause. For unrelated issues, work in stages so that you understand the effect of each change.
Explore further
Do you have a business task to explore with AI? Discuss your needs with eloRezo.
Content and sources checked on 30 October 2026.