1. Define the Idea
First, figure out your problem which you want to solve. For example, if you want to create an “AI Resume Builder” which makes ATS friendly resumes by only giving user details.
2. Write a Natural Language Prompt
Then make a prompt according to the requirements, like the UI, Architecture, Pages, etc. A clear prompt will help the AI to make better results.
Then, provide the prompt to the AI coding tool.
3. Generate the Code
After giving the prompt, the AI coding tool will read it, make a plan, and sometimes may ask you before executing the process. For example, In Google AI Studio (Max Mode) asks before confirming the whole plan.
Then, it will generate the whole code and some tools also provide you the live preview of the code.
4. Test the Application
If live preview is available, test the application through AI-assisted software testing, whether it is as you want or not.
5. Refine Through Follow-Up Prompts
Then, make the changes by giving the follow up prompt if required. If everything is fine and up to mark, you can skip this step and jump to the next step.
6. Review and Deploy
After reviewing all the functionality, you can deploy the application to the live version so you can access from anywhere. For example, In Google AI studio you can link your project directly through GitHub and then further deploy using Vercel or Netlify for free.
The process discussed above for vibe coding any application may differ from platform to platform. Once you get started you can check how it is.
Now, let’s discuss what different types of vibe coding tools are available right now, to start your development.
Vibe Coding Example: Build a Personal Expense Tracker Using Google AI Studio
Let's understand how vibe coding works through a practical example. Through Google AI Studio, we will be building a budgeting tool to track an individual's financial transactions without having to manually write any HTML, CSS, or JavaScript code.
This app is supposed to help users keep track of their earnings and outlay, get monthly expense reports, and check the remaining balance at any time.
Step 1: Open Google AI Studio
Begin by going to Google AI Studio and signing in with your Google Credentials.
Click on Build and create an app. You will now be greeted by a prompt box where you will tell the AI the kind of app you want to build.
Step 2: Write a Prompt to Describe Your Application
Now, tell the AI the kind of app you want the features, design, and the functionalities as you like them to be in your expense tracker.
For example, you may input the below prompt:
Build a personal expense tracker web application.
Include these features:
1. A dashboard showing total income, total expenses, and remaining balance.
2. Separate categories for income and expenses.
3. A form to add, edit, and delete transactions.
4. Monthly expense summaries.
5. Charts showing spending across different categories.
6. A transaction history with date and category filters.
Use a clean and simple interface with a responsive layout.
Use local storage to save transaction data so users can access their records after refreshing the browser.
Make sure all buttons, forms, filters, and calculations work properly.
After entering the prompt, the first thing you will get to do is generating the actual app by clicking the Build button.
Step 3: Generate the Application and Check the Preview
You will notice that Google AI Studio will interpret and generate the source code of your project from that prompt. Once your files are properly created with all the elements in place, the system will open a preview of your final product that you can try interactively while watching the changes.
The live feature allows you to check if the expense tracker suits your design and functionality expectations and also test how users will interact with the app (dashboard, transaction form, expense categories, monthly summaries).
Apart from that, you might want to go into the Code View (tab) to have a look at the code that has already been generated.
Step 4: Refine the Application Using Follow-Up Prompts
Some of the features you have in our mind could very well have missed it from the first draft. Through the chat window, you can issue subsequent instructions that will be translated to changes in the app.
Let us suppose you are not satisfied with the look of the dashboard or want to add a new section; simply mention what you want to fix.
Enter a follow-up prompt like this:
Improve the dashboard design.
Make the following changes:
1. Add a separate card for total income, expenses, and available balance.
2. Use a pie chart to show expenses by category.
3. Add a monthly spending trend chart.
4. Include a date range filter for transaction history.
5. Make the layout mobile-friendly.
Keep the existing transaction data and functionality intact.
Google AI Studio will modify the application based on your instructions.
Keep giving instructions till the application becomes what you expect.
Step 5: Test the Application
After you approve the generated design, test the application to see if its features work as promised.
For example:
Make an income transaction and check if the total income is updated.
Enter an expense and verify the remaining balance change.
Update or delete a single transaction and confirm that the total remains correct.
Change the displayed month and see if only the relevant transactions are displayed.
Close your browser and reload the page to ensure you can access the transactions that were entered.
Step 6: Export or Deploy Your Application
Once you have tested the app, you may either export it for your next development cycle or make it accessible on the internet.
Google AI Studio allows you to sync with GitHub so that you can save changes to your project in a repository (a kind of storage for computer code), get the code for free from GitHub and edit and re-compile it wherever you are. Furthermore, you have the possibility to download the code with all your changes in the form of a compressed ZIP file.
For deployment, you can use the Cloud Run option in Google AI Studio to publish the application and get a live URL. Deployment requirements and pricing depend on your Google Cloud account and eligibility.
You can now access and share your expense tracker through its deployed URL.
Note: This example uses sample financial records and browser-based storage. Do not enter real banking credentials or sensitive financial information into an experimental application.
Popular Vibe Coding Tools
Here are some commonly used vibe coding platforms and tools available, which perform based on their capabilities.
Tool | Category | Key Capabilities | Suitable For |
Replit Agent | AI app builder | Generates applications from prompts, writes code, helps debug errors, and supports deployment. | Building full-stack applications and prototypes |
Lovable | AI app builder | Generates user interfaces, application logic, and backend features through natural language prompts. | Websites, dashboards, internal tools, and MVPs |
Bolt.new | Browser-based development platform | Generates web applications, provides a browser-based coding environment, and supports live previews. | Web applications and interactive prototypes |
v0 | AI application builder | Generates UI components and full-stack applications from text prompts. | Websites, dashboards, and web applications |
Cursor | AI code editor | Uses AI agents to understand codebases, edit multiple files, run commands, and help fix errors. | Building and modifying existing software projects |
GitHub Copilot | AI coding assistant | Provides code suggestions, supports agent-based coding tasks, and assists with code reviews. | Writing, reviewing, and maintaining code |
Claude Code | AI coding agent | Understands codebases, edits files, runs terminal commands, and performs multi-step coding tasks. | Developers working on complex coding tasks |
Now let’s understand what is the difference between vibe coding and AI native software engineering.
Vibe Coding vs AI-Native Software Engineering
Vibe coding and AI-native software engineering both utilize AI in software development. But their applications and methods are a little different.
Vibe coding mainly revolves around using natural language prompts and repeated feedback to produce software. That's how it lets users develop software apps without having to write every bit of the code themselves.
In AI-native software engineering, on the other hand, AI is a central element that is integrated throughout the entire lifecycle of software development. AI performs tasks such as gathering requirements, creating a plan, coding, testing, and reviewing code etc. But human software developers still establish requirements, check that results are in compliance, and they are ultimately responsible for software quality.
Basis | Vibe Coding | AI-Native Software Engineering |
Main focus | Creating applications through natural language prompts | Using AI throughout the software development lifecycle |
Human role | Describes requirements, guides generation, and reviews results | Defines specifications, directs AI workflows, validates outputs, and oversees delivery |
AI involvement | Primarily generates and modifies code based on instructions | Supports planning, development, testing, review, deployment, and maintenance |
Development approach | Conversational and iterative | Structured and AI-supported |
Testing | May rely on manual checks and basic testing | Includes planned testing, verification, and quality checks |
Common use cases | Prototypes, personal tools, websites, and MVPs | Larger software projects and products that require ongoing maintenance |
Technical expertise | Basic projects can be built with limited coding knowledge | Requires engineering knowledge to manage architecture, quality, and system behaviour |
Benefits and Challenges of Vibe Coding
Every technology comes with new benefits and challenges also, which is vibe coding also has. Below are some of the key benefits and challenges of vibe coding.
Benefits of Vibe Coding
1. Getting Started With Software Development Is Easier
Rather than using a programming language to create an application from the ground up, one could use a natural language description instead. Thus the software idea could be tested before having the knowledge to do any kind of actual coding.
2. Faster Prototyping
An AI system can create the skeleton of an app given just a few prompts so that it can be used for testing ideas and gathering feedback without having to manually build every single part.
3. More Flexibility and Creativity
By prompting the change of layouts, features, and workflows you're able to create an app without having the code first.
4. Support for Developers
Professional software developers can utilize AI to do a lot of the routine coding, to come up with code stubs, explain code, and help with tedious but necessary tasks.
5. Faster Idea Validation
Startup teams, designers, and business analysts are empowered to make first-hand app versions as the idea is being worked through so they can test for a real user problem as they go on.
Challenges and Risks of Vibe Coding
1. Code Quality Issues
In most cases, the code generated by an AI contains various forms of errors such as superfluous codes or inefficient coding logic. An app that seems flawless on a preview screen may have some serious issues in the code behind.
2. Security Risks
The programs that are generated can have unsafe sign-on features, wrong access management systems, uncovered API keys, or similar weaknesses. Always go over the parts that relate to the security aspects of your app prior to deploying it.
3. Limited Maintainability
Applications generated through repeated prompts can become challenging to maintain if the codebase lacks consistency or documentation is poor. As the project grows and develops, technical debt may rise as a consequence.
4. Debugging Challenges
This AI can give suggestions that are not correct or even introduce new errors while changing the code functionality. Someone with no experience at coding will be quite at a loss in trying to uncover the true cause of the problem if they have no coding background.
5. Scalability Constraints
It could happen that a prototype does not support a large number of users, a complex sequence or workflow, or a great volume of data.
Besides that, further architectural designing, performance testing, and engineering effort might be needed if the tool's data policy and access permission have not been reviewed.
6. Privacy and Data Concerns
In some code editing platforms, the code and the prompts are passed on to external AI services for processing. Never submit your passwords, personal keys, or any data about customers and company information unless you have checked the data policy and permissions of the tool carefully.
Vibe coding can help you in the experimental phase and early stages of the application development of an app. Software systems dealing with confidential data, as well as ones supporting critical business functions, are usually subjected to higher testing, validation, and maintenance procedures in addition to manual review.
Conclusion
So what is vibe coding? It helps you turn ideas into applications through natural-language instructions. You can generate a first version, test it, and refine the result through follow-up prompts.
Review the code, check every feature, fix errors, and assess security before deployment. Simple prototypes may need less oversight, but applications handling sensitive data or critical tasks require thorough testing and careful technical review.
