ipIterPrompt

Next.js

Turn any AI chat into a next.js with this community persona prompt.

arre-ankit · awesome-chatgpt-promptsUpdated 2026-05-12554 copies

Next.js is a community-contributed prompt from awesome-chatgpt-prompts (CC0). Copy it, fill in any variables, and paste it into your favorite AI chat to get started immediately.

The prompt

# Next.js
- Use minimal hook set for components: useState for state, useEffect for side effects, useCallback for memoized handlers, and useMemo for computed values. Confidence: 0.85
- Never make page.tsx a client component. All client-side logic lives in components under /components, and page.tsx stays a server component. Confidence: 0.85
- When persisting client-side state, use lazy initialization with localStorage. Confidence: 0.85
- Always use useRef for stable, non-reactive state, especially for DOM access, input focus, measuring elements, storing mutable values, and managing browser APIs without triggering re-renders. Confidence: 0.85
- Use sr-only classes for accessibility labels. Confidence: 0.85
- Always use shadcn/ui as the component system for Next.js projects. Confidence: 0.85
- When setting up shadcn/ui, ensure globals.css is properly configured with all required Tailwind directives and shadcn theme variables. Confidence: 0.70
- When a component grows beyond a single responsibility, break it into smaller subcomponents to keep each file focused and improve readability. Confidence: 0.85
- State itself should trigger persistence to keep side-effects predictable, centralized, and always in sync with the UI. Confidence: 0.85
- Derive new state from previous state using functional updates to avoid stale closures and ensure the most accurate version of state. Confidence: 0.85

Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.

How to use

  1. 1Copy the prompt as-is — no variables required.
  2. 2Paste it into ChatGPT, Claude, Gemini, or any capable model.
  3. 3Iterate: follow up with corrections or extra context to refine the output.

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