July 27, 2025
Admin
As the software development world continues its stride towards adopting more advanced and efficient methodologies. The integration of modern collaborative platforms and AI tools is also evolving the conventional methods of coding, when coding meant understanding every little detail of the programming language and manually writing every bit of the code. Tools like Amazon CodeWhisperer and GitHub Copilot stepped in to offer help to developers along their software development journey.
However at present, one can build software tools simply by describing what they wish to achieve with the tool in human language. AI does the rest of the heavy lifting ,like generating, testing, and adjusting the code to suit user requirements. This method of building software is known as vibe coding and is fast gaining immense popularity in the software development community across the globe. Andrej Karparthy introduced it to the world in the first half of 2025.
This method of coding offers better speed and creativity it also involves certain risks like security gaps and poor code quality due to dependence on AI. The following section of this blog will discuss in detail how vibe coding works, its benefits, shortcomings, and how one can implement it on their own for best results.
Vibe coding refers to an approach that focuses on enhancing creativity, flow, and quick iteration without compromising on technical aspects. A brainchild of Andrej Karpathy, the co-founder of OpenAI, it also involves interaction with LLMs(large language models) and AI coding assistants that work hand in hand with natural language prompts. As a result, a user can seamlessly create every line of the code from scratch with the aid of AI.
Vibe coding can certainly make coding feel like a more creative and conversational task. It also includes risks around code security, quality, and long-term reliability. At present, it works perfectly for small applications, prototype development, etc. It serves as the perfect starting point for seasoned developers to understand AI-guided software development, as they are aware of the right time to take control of the process.
Vibe coding is aimed at lowering the barriers to entry in software development. This approach is beneficial for speeding up the process of turning ideas into tangible software products, specifically for individuals with no or limited understanding of coding. However, as AI takes over much of the workflow, one is unlikely to get a full understanding of how the system works behind the scenes. Also, the process of debugging can feel more overwhelming when one is not able to comprehend the flow and spot significant gaps in the code. Since the speed and usability of vibe coding impact long-term maintainability and flexibility, particularly for large-scale projects. Fine-tuning every part of the project becomes more time-consuming.
| Factor | Vibe Coding | Traditional Coding |
| User Interaction | Regular conversation with AI using simple English | Requires manual writing using a programming language |
| Expertise | Minimal understanding of coding | Strong programming background with knowledge of different coding languages |
| Development time | Quicker app creation and iteration | Slower, more methodical, and accurate |
| Focus | Rapidly turn ideas into working apps | Proper syntax usage, low-level details, and code structure |
| Debugging | AI is helpful for finding and fixing errors, but sometimes it can affect overall quality | Developers have an in-depth understanding of fixing problems |
| Flexibiity | Limited to the capabilities of AI | Full control over every line of the code |
Vibe coding encourages users to implement new-age tools, faster iterations, and enhance high creative energy. This effectively eliminates the need for manual code typing, strategic integrations, and code refinement. Below are some of the noteworthy reasons behind the rising popularity of vibe coding:
Chatbots like Claude, ChatGPT, or Gemini can perform in-depth research and analysis, and also perform debugging for code outside the editor.
Access to tools like GitHub Copilot, Replit, and Cursor serves as an excellent starting point for writing code.
Developers get to experiment and learn at the same time. AI-powered coding is truly transforming how developers turn their ideas into working software.
Version Control
Vibe coding is perfect for keeping track of changes and saving work throughout the development process.
For instance, a user wishes to design an event with a basic website that will allow participants to get an RSVP. However, the user has no coding knowledge, but with the help of an AI assistant, they can write like:
“Help me create a simple event management page that will let the guests enter their details for RSVP. After submission, the page must display a message “Thank you for RSVP”
The AI assistant is likely to give a response like:
“Here is the JavaScript and HTML code for your page. It comes with a form that with user details and will display a thank you message post form submission.”
The user tries out the code and clicks on the RSVP button, but nothing works. It displays an error message:
“TypeError: Cannot read property ‘value’ of null.”
The user, not being sure of what it means, is likely to copy this error message and paste it back into the AI chat.
“I got this error message after clicking on the RSVP button:’TypeError: Cannot read property ‘value’ of null.’ Help me fix this.
The AI assistant replies
It looks like the code is looking to take inputs even before they are available on the page. I have updated the script to ensure it runs after the code is loaded completely. Try the new version.n”
The user pastes the new code, refreshes the page, and now the RSVP form responds perfectly. Such types of tweaks are an integral part of the vibe coding process.
It is best to work with project templates from open-source communities, frameworks, or other sources. This approach makes it easier to handle the boilerplate setup, configuration, structure, and basic authentication. Also, it allows the users to focus on improving the unique features immediately.
Advantage:
It is beneficial for saving time, ensures consistency, and most importantly, eliminates errors in the setup.
How to do:
Work with cookiecutter templates, create next-app, or framework-specific starters
Make the most of natural language when using an editor. Take help from AI for creating files, code refactoring, writing, or explaining concepts.
Advantage:
It is highly effective in lowering the barriers, promotes experimentation, and also speeds up the workflow.
How to do:
For this, users must consider platforms like Cursor’s chat, Github Copilot Chat, or other AI agents. Always practice giving clear and concise instructions.
The overall quality of an AI output is largely dependent on user input. Hence, one needs to be specific, provide context, and never hesitate in rephrasing or asking follow-up questions.
Advantage:
Improved prompts will result in accurate, useful, and relevant responses from the AI.
How to do:
Start out with using simple language and add additional details in an iterative fashion.
With AI, one can certainly go beyond code generation. Leveraging LLMs will help in finding APIs, learn design patterns, generating ideas, or comparing libraries based on their requirements.
Advantage:
It provides access to the latest information, provides snippets of code, and helps in exploring alternative methods.
How to do:
Write queries concisely to give clear context, and AI will also provide improved suggestions
Using separate threads, workspaces, or chats is best for working on different features or tasks. This helps in preventing conversations from getting messy and also helps in tracking various lines of development.
Advantage:
Eliminates cognitive load, promotes faster decision-making, and improves focus on the task.
How to do:
Always remember to name chats or threads clearly.
Save prompts that can work flawlessly. Documenting useful prompts for regular functions can go a long way in the coding process.
Advantages
It not only saves time but also aids in improving consistency. If working in a team, it is helpful for knowledge sharing.
How to do:
Keep a notes app handy to record prompts as a simple text file. Alternatively, users can choose to use dedicated prompt management tools for organizing prompts effectively by category.
Developers can leverage open source projects as their starting point for incorporating extensive libraries.
Advantage:
Helps in jumpstarting the project, provides clear learning opportunities, and also eliminates redundancy in work.
How to do:
Keep an eye on licenses and attribution details before making use of the external code.
During a code development process, mistakes happen, especially when experimenting with different ideas. Version control allows the user to carefully save snapshots of their progress so that they can easily revert changes when necessary.
Advantage:
This approach is highly effective for reducing data losses, promotes experimentation, and facilitates quick and easy debugging.
How to do:
Work regularly with relevant prompts. Users must focus on learning Git commands like checkout, commit, reset, etc.
When generating or modifying code using an AI assistant, it is best to test the code base immediately. Run the app locally, create automated tests, and click through features. AI is certainly beneficial for generating basic tests.
Advantage:
Beneficial for early detection of bugs, offers feedback readily, and also boosts user confidence.
How to do:
Testing should always be part of the coding loop. Use prompts like “Write pytest unit tests for a Python function.”
In the event of an error in the code, copy and paste the exact error message alongside the relevant code snippet into an AI assistant or the corresponding LLM. It is likely that the AI assistant will clearly explain the error and also suggest a fix.
Advantage:
This is essential for speeding up the resolution, gives context, and also helps the users in learning from their errors.
How to do:
Give clear context: This error is coming <copy and paste exact message> at the time of running the code. Alternatively, <paste code block >. What could be wrong?
There can be instances when AI code is inefficient, verbose, or inconsistent. Always give sufficient time for cleaning the code, enhance variable names, and make certain it aligns perfectly with the standards of the project.
Advantage:
Improves correctness, maintainability, and security while boosting overall growth and learning.
How to do:
Thoroughly read the AI-generated code base and understand if it makes sense. Look for obvious errors or flaws in the security. If any section of the code is not understandable, it is best to ask AI for a clear explanation to learn about the concept behind it. Avoid simply copying and pasting from black boxes.
Avoid committing passwords, API keys, or other sensitive information directly into the code. Always make use of environment-specific variables or secret management alternatives.
Advantage:
Restricts massive security breaches even when the code becomes accessible to the public.
How to do:
Implement .env files, cloud-based secret managers, or OS specific environment variables.
Seasoned software developers are always passionate, curious, and resilient in their approach. They never let the difficulties wear out their energy. It is all about enjoying the process of developing, experimenting, and learning.
Advantage:
Keeps the user motivated, improves creativity, and makes development enjoyable.
How to do:
Always celebrate little successes in the journey, share progress, take breaks whenever necessary, and never stay away from exploring new ideas.
One of the most noteworthy advantages of Vibe coding is that it greatly enhances the speed at which MVPs were developed previously. It no longer takes weeks; developers can easily move from a concept to a working model in a few hours. It is particularly beneficial for creators and startups looking to test their ideas fast and also receive feedback without investing a lot of money and time.
Vibe coding makes software development a lot easier for individuals with no or limited technical knowledge. When an individual is able to describe in simple language what they want, coding becomes a lot easier and accessible to designers, entrepreneurs, and experts across various domains.
Developers get to experiment to their full potential as there are not many technical barriers with vibe coding. It is a lot easier to try and test a new set of ideas, features, and develop creative solutions without investing a whole lot of resources. Instant feedback from the AI assistant certainly helps in boosting the creative momentum.
Vibe coding brings higher efficiency by addressing repetitive tasks involved in the software development process, like handling simple data, writing standard code, handling basic files, etc. As AI can seamlessly handle these tasks, developers get to spend more time into thing about their design, solving real-world problems, and improving the overall user experience.
There is no match to AI when it comes to handling common tasks, but these models tend to struggle when one has complex requirements. Projects that call for highly detailed attributes, AI is likely to deliver incomplete or basic code. As projects turn out to be larger and more and more complicated, users will have to make manual interventions to make things work appropriately.
Another option is that users are likely to have greater dependence on AI and not develop strong coding skills in the long run. In the event of an error, one is likely to struggle as they do not have an in–depth understanding of what is happening behind. Over time, it can turn out to be a significant problem, particularly in a professional environment where it is critical to understand the system thoroughly.
Vibe coding is gradually transforming the software development procedure alongside the roles of developers, startup expansion, and learning new skills across various domains.
Vibe coding has immense potential in a startup environment. A relatively smaller team is now capable of developing products faster. Previously, the same task would require greater resources. As a result, startups can easily roll out products within hours or days. This has also made it feasible for them to switch and test ideas without compromising on flexibility. Besides, it allows non-technical people to participate in the software development process.
Developers no longer need to spend hours writing code manually; they are now able to focus on developing extensive prompts, reviewing AI-generated code, and exploring a wide variety of outputs within the work environment. New skills like system design, prompt writing, and code review are becoming as critical as learning a coding language.
New specialties are emerging gradually, like AI ethics advising, prompt engineering, and more, that will soon become entire job roles.
The introduction of vibe coding has also made a significant impact on how people are taught to code. While the idea of understanding the fundamentals remains the same, there is a noteworthy shift towards working alongside AI tools. For instance, learning to write clear prompts, reviewing and refactoring AI-generated code for bugs and security issues, integrating the code into larger projects, etc.
This shift is likely to make software development more accessible to individuals who do not have a computer science background. On the other hand, it highlights a greater challenge: easier code generation practices make it essential to have the ability to spot the flaws when the code is not working properly.
It is crucial to understand the fact that, instead of completely replacing technical skills, video coding serves as a helping hand for collaboration between computers and humans. Developers now need to learn how efficiently they can work around it and adapt their skill set accordingly.
As more new tools make their way into vibe coding. The following section talks about some of the most widely used tools:
Replit is a cloud-powered coding platform that is compatible with over 50 programming languages. It features an integrated AI assistant that is excellent for writing, debugging, and cleaning code. Users are required to describe their requirements in normal language, and the integrated AI tool will generate code and also fix it where necessary. The best part one also gets instant deployment, real-time collaboration, version control, and more.
Cursor is a smart and efficient code editor based on Visual Studio Code. It makes use of powerful AI-based models like Claude 3.7 Sonnet and GPT-4.0 for understanding the codebase. This tool is truly effective in helping users write, enhance, and fix code without much difficulty.
Lovable is a popular no-code tool that one can use for building apps just by describing what they want their software to do. It is capable of reading prompts and creating the structure for mobile and web applications. Lovable is the perfect tool for someone with no coding experience.
Windsurf is an AI-powered full-stack development platform. It provides access to tools like Suplercomplete that can guess user intent and generate the code accordingly. The cascade feature allows Windsurf to create seamless AI workflows. Using these tools, one can easily refactor and edit the code. It is specifically suitable for developers working on big and complex projects.
Bolt has been designed to create prototypes faster using AI. Users can describe features they wish to integrate in their app in simple English, and Bolt will automatically build the backend and frontend for deployment. It is an excellent choice for startups and product teams looking to create and test ideas fast.
Developers who are about to start their coding journey and looking for something simple, Lovable is the perfect choice to turn ideas into apps without the need for extensive coding. On the other hand, Replit is for those in need of a full-fledged coding ecosystem with integrated AI features for enhanced flexibility.
Advanced users with experience in a code editor can consider Cursor, as it comes with a host of powerful features and helps speed up the overall coding process. Bolt is ideal for teams or individuals who wish to create and test apps with minimal manual input.
Individuals working on bigger and complex projects should leverage Windsurf as it offers deep AI support for both frontend and backend needs. It is the perfect tool for managing complex development processes seamlessly.
Vibe coding is gradually reshaping the world of software development, making it more accessible for individuals with no or limited understanding of programming languages. One can now easily turn their ideas into tangible products simply by describing their requirements to an AI assistant. This approach assists teams to move faster in early prototyping and eliminates barriers for people without a traditional programming background.
However, just as every other technology, this also comes with certain trade-offs like security, code integrity, long-term maintenance, etc. If someone relies on AI output without properly reviewing the overall functioning of the software are likely to suffer. Large-scale complex projects will still require substantial human intervention for effective code design and analysis of underlying code. Vibe coding is not removing the need for technical skills; rather, it is changing its implementation.
As AI-assisted coding tools like Bolt, Cursor, and Lovable continue to become more and more efficient, vibe coding is likely to gain more popularity in software development by individuals or teams. For now, it is perfectly suitable for small projects, rapid iteration, experimentation, etc., with necessary human oversight to keep things in order.
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