What is the smallest complete user journey?
Name the user, their starting point, the action they take, and the result they receive.
The Vibe Coding Hub
Build with AI. Stay in control.
Vibe coding turns natural-language ideas into working software. The reliable version is a disciplined loop: clear outcomes, relevant context, small changes, visible tests, and continuous refinement.
A repeatable workflow
The five-step Vibe Coding loop
1
Define the outcome
Choose one user, one problem, and one action the first version must complete.
2
Supply context
Share the stack, current files, constraints, visual direction, and definition of done.
3
Build a thin slice
Create the smallest complete flow before adding accounts, dashboards, or polish.
4
Test with evidence
Run the feature, inspect errors, try edge cases, and report the exact observed result.
5
Refine and protect
Improve in small commits. Review security, privacy, accessibility, and performance.
Core principle
Prompting starts the work. Verification finishes it.
A polished-looking result can still be incorrect. Treat the browser, tests, logs, and actual user flow as the source of truth.
Starter prompt
Give the project a strong first brief
Act as my development partner. Goal: [one testable user outcome] Audience: [who needs it] Stack: [languages, framework, hosting] Current state: [existing files or starting point] Requirements: [3–5 essential behaviors] Constraints: [security, browser, accessibility, budget] Done means: [a checklist I can verify] First, propose the smallest working version and identify any assumptions. Then implement it in reviewable steps.
Avoid common failures
Build confidence, not just code
Do not paste secrets
Keep keys and credentials in server-side environment variables. Never place private keys in frontend code or prompts.
Do not accept mystery code
Ask what changed, inspect the diff, and confirm you understand the data flow before publishing.
Do not skip real testing
Check mobile layouts, keyboard use, empty states, invalid inputs, slow networks, and failure messages.
Project playbook
What to ask at every stage
Use these questions to keep an AI-assisted project focused, understandable, and ready to improve.
What changed, and how can I verify it?
Request a focused diff, a short explanation, and exact steps for testing the new behavior.
What evidence narrows the problem?
Share the exact error, reproduction steps, relevant file, input, and expected result.
What could break or expose data?
Review inputs, authentication, secrets, dependencies, accessibility, responsive layouts, and error states.
Useful prompt patterns
Prompts that move work forward
Planning
Turn an idea into a thin slice
“Break this idea into the smallest end-to-end version one person can use. List assumptions and leave later features out.”
Debugging
Diagnose before changing code
“Using this error and reproduction, rank the likely causes. Show the smallest diagnostic check before proposing a fix.”
Review
Inspect what the AI produced
“Review this change for correctness, security, accessibility, edge cases, and unnecessary complexity. Identify evidence for each concern.”