Build a Chat Application with Next.js
A messaging interface with conversations, message bubbles, and input. Using Next.js's Next.js 14+ with App Router, SSR, and shadcn/ui, LoomCode AI generates a production-ready chat application with clean code structure, proper state management, and a polished user interface — all from a single text description in seconds. No prior coding experience required.
Build This App NowHow to Build a Chat Application with Next.js
Select Next.js
Open LoomCode AI and choose the Next.js template from the template picker.
Describe your app
Type a description of your chat application and click submit.
Preview & deploy
Watch the AI generate code and preview your working app live. Deploy with one click.
Why Build a Chat Application with Next.js
Next.js handles the real-time, interactive nature of a chat application well. Message lists, feed updates, and user interactions all benefit from the efficient DOM reconciliation and reactive state updates.
What the AI Generates for This Chat Application
- Responsive chat application layout that adapts to desktop, tablet, and mobile
- Component-based architecture with reusable UI elements
- Client-side state management for instant user interactions
- Styled with Tailwind CSS utility classes for a polished look
- User interaction patterns: likes, comments, and real-time updates
- Feed layout with cards, avatars, and timestamp formatting
Example Prompt
Copy this prompt and paste it into LoomCode AI:
What You Get
LoomCode AI generates a chat application with a feed layout, user interaction elements, and content cards. Each card includes avatar, text, timestamps, and interactive buttons for engagement. The output is properly structured Next.js code using Next.js 14, TypeScript, Tailwind CSS, shadcn/ui with typed components, responsive styling, and clean state management. The app runs immediately in a live sandbox — interact with it, test every feature, then iterate with follow-up prompts or deploy to a shareable URL.
Tips for Better Results
- Describe the content card format: "avatar, username, post text, like button with count, timestamp" so the AI generates proper social layouts
- Ask for interaction states: "like/unlike toggle, comment expand/collapse, share button" for a complete interactive experience
- Include "responsive feed layout" and "infinite scroll or load more" if you want a feed-style interface
- Consider asking for responsive design explicitly if mobile support matters for your chat application
Tech Stack
FAQ
Can AI build a Chat Application with Next.js?
Yes. LoomCode AI generates a complete chat application with Next.js 14, TypeScript, Tailwind CSS, shadcn/ui from a text description. The AI understands user interactions, feeds, messaging, and real-time updates and produces working code that runs immediately in a live sandbox. Next.js's component architecture handles user interactions, feeds, messaging, and real-time updates with reusable UI pieces and efficient state management. You can iterate with follow-up prompts to refine features or deploy with one click.
How long does it take to build a Chat Application with AI?
A working chat application typically generates in 30-60 seconds. The initial version includes user interactions, feeds, messaging, and real-time updates with a polished UI. From there, you can add features incrementally — each follow-up prompt takes another 15-30 seconds. Most users go from idea to a deployable chat application in under 10 minutes, compared to hours or days of manual development.
Can I customize the generated Chat Application?
Yes, in two ways. First, use natural language follow-up prompts: "add dark mode", "change the layout to tabs", or "add a search filter" — the AI modifies the existing code. Second, copy the full source code and edit it directly. The output is standard Next.js code using Next.js 14 and TypeScript that works in any React/Vue/Next.js project.
Which AI model works best for a Chat Application?
For a chat application, GPT-4o is fast for interactive UI-heavy apps. Claude 3.5 Sonnet produces the cleanest component architecture for complex interactions. DeepSeek V3 is a cost-effective alternative for simpler versions. You can switch models anytime.
Is the generated chat application production-ready?
For prototypes and MVPs, the generated chat application is typically ready to use immediately. The code includes proper TypeScript types, component structure, and responsive design. For production deployment at scale, you may want to add automated tests, error boundaries, and monitoring.
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