Vibe coding allows anyone, even without technical skills, to create fully functional apps simply by describing what they want. These examples show how real projects are created through natural language instructions using Emergent. Each one highlights how the system interprets prompts, builds the logic, handles integrations, and shapes complete applications.

The following projects cover 3D sites, Chrome extensions, dashboards, automations, bots, and research tools. They demonstrate how natural language can replace traditional coding, how Emergent fills the skill gaps, and how non developers can build advanced experiences simply through conversation.

Read More About: Best vibe coding tools

Vibe Coding Examples

1. 3D Websites

About the Project

This project shows an interactive 3D website that responds to user movement and on screen actions. It includes animated elements, camera movement, smooth transitions, and a modern layout. The entire experience is built visually, making the site feel dynamic and immersive.

Project Link: Interactive 3D Website 

Initial Prompt

The build begins with a simple prompt describing the 3D scene you want, such as an animated model, a background environment, or scroll based movements. Emergent reads the description, identifies the needed components, and sets up the scene, lighting, and camera flow based on your instructions.

Preview

Emergent then renders a functional preview so you can see the animations, model positions, and interaction responses in real time. This helps you immediately check whether the motions feel natural and whether elements like lighting and depth behave the way you imagined.

Refinement Prompt

You can refine any detail by giving natural instructions like brighten the lighting, slow down the rotation, or add a floating button. Emergent updates the full scene instantly, ensuring the changes appear in the next preview without requiring you to adjust any code manually.

Deployment

Once everything looks right, Emergent packages the 3D website into a deployable build. It prepares all assets, optimizes performance, and makes the site ready for hosting so you can publish it with a single click.

Read About: How to build 3D websites with Spline Animations?

2. Invoice Generator Tool

About the Project

This project lets users chat with an AI to generate invoices from plain language descriptions. It converts client details, items, dates, and totals into a polished invoice. The final output can be downloaded or shared directly.

Project Link: Invoice Generator

Initial Prompt

The process starts when you describe the invoice flow you want, such as capturing client details, listing items, or generating totals. Emergent understands your instructions and creates a conversational interface that can interpret natural sentences and convert them into structured fields.

Preview

You immediately see a working version of the invoice generator where your sample messages turn into invoice data. The preview shows the layout, collected fields, totals, and formatting so you know exactly how the final invoice will appear.

Refinement Prompt

If any adjustment is needed, you simply describe it. You can ask for branding, layout spacing, logo placement, or different color styles. Emergent redraws the invoice instantly and updates the calculations or formatting without breaking any part of the workflow.

Deployment

When the tool is ready, Emergent packages the final invoice generator with a clean UI and a download function. You can export the project as a full web app or embed it inside an existing workflow with no additional setup required.

Read About: How to build a conversational invoice generator?

3. Meeting Research Assistant

About the Project

This tool collects meeting topics, scans the web, and prepares summaries and briefings before your call. It creates a research pack with key insights, context, and talking points. The goal is to help you join any meeting fully prepared.

Project Link: Meeting Research Assistant      

Initial Prompt

You begin by telling Emergent what kind of meeting you want research for, such as a client briefing, competitor call, or industry discussion. The system interprets your goal and prepares a structure for gathering insights, summaries, and context around the topic.

Preview

Emergent generates a first research pack showing summaries, highlights, and key talking points. This preview helps you see what information the system gathered and whether the content matches what you need for your upcoming meeting.

Refinement Prompt

You can refine the research by giving instructions like add financial details, find recent news, or include product comparisons. Emergent updates the research pack with deeper insights and restructures the content on the fly so it is clear and useful.

Deployment

When the research looks complete, Emergent prepares a clean output that can be shared or saved. You can export it as a document or use it inside the tool as your meeting prep, without any manual formatting or extra steps.

Read About: How to build an AI-powered Meeting Research Assistant?

4. Chrome Extension for Personalised Connection Request Generator

About the Project

This extension lets users generate personalized LinkedIn connection messages directly from profiles. It reads key details, suggests tailored messages, and helps users build better networking outreach. The tool runs instantly within the browser.

Project Link: Linkedin Personaliser 

Initial Prompt

The build starts when you describe the behavior you want, such as reading profile details and generating a custom message. Emergent interprets this and creates the extension structure, including scripts and layout, based on your instructions.

Preview

Emergent shows a working prototype where you can load a LinkedIn profile and see the generated message appear. This helps confirm that the extension is reading the right fields and producing meaningful connection suggestions.

Refinement Prompt

You can refine the tone, adjust message style, or add new data points such as work history or headline keywords. Emergent immediately updates the extension logic and adjusts the message generation without needing any code edits.

Deployment

Once ready, Emergent packages the extension into a loadable Chrome folder. You can install it instantly through Chrome’s extension manager and use it within LinkedIn right away, with no setup or debugging required.

Read About: How to build a Chrome Extension for personalised connection request generator for LinkedIn?

Conclusion

These examples show how vibe coding turns natural language into real applications. Understanding how it works helps you think clearly about what to ask, which improves the quality of your builds. The best way to learn is by experimenting with small ideas and watching how the AI translates your instructions into complete, functional tools.