What Is Vibe Coding? Redefining Programming with Generative AI

17-Jun-2025

Imagine developing a set of computer codes for a software development project. It can be time-consuming, repetitive, and challenging. Now, assume giving an idea about the programme, and artificial intelligence (AI) automatically generates the code. It makes writing a programming code easy and time-saving so that you can focus on more complex problems. AI has embedded itself in every sphere of the work environment, and coding isn’t left behind. It is believed to be redefining programming with generative AI.

What is Vibe Coding?

It is a new software development approach that has kept Silicon Valley buzzing. Vibe Coding refers to the use of AI tools and software for coding and programming to develop websites and apps. Programmers give detailed prompts in natural language to describe the idea, desired functionalities, or “vibe” of the software to AI. AI will then generate code depending on the input given by you. Various AI-powered coding assistants, such as Cursor and Replit, are being used to create custom web pages.

The Vibe coding concept was built and popularised by OpenAI co-founder Andrej Karpathy in early 2025. It was to help software developers, engineers, and investors benefit from AI tools to write high-quality code recommendations based on the user’s input. Sundar Pichai, CEO of Google and Alphabet, has openly shared his "delightful" experiences with "vibe coding". He explained it as a casual yet cutting-edge way of using AI tools to build webpages with minimal manual programming.

How to Use Vibe Coding? 

The first step is to choose the Vibe coding tool. Cursor (with Composer and Sonnet), Replit, Softr, Lovable, and AI chatbots like Claude are various popular AI tools that support coding. Some tools, like Whisper or WhisperFlow, support voice input as well. Start with basic and clear requests. Focus on the functionality first, then move to complex requests. Keep the descriptive prompt language plain and simple, without overloading the AI. Remember to precisely outline the needs, like placement of buttons, fields, user actions, and expected outcomes of the app. The clearer the instructions, the better it is for AI to transform the thoughts or instructions into code. 

After the initial generation of codes, test them out. With testing, you will get an idea of its accuracy. Gradually, the features can be added and improved by giving additional, focused prompts. Try finding bugs and unexpected behaviours of the generated features or app. Run and test in various scenarios, both common and edge cases. After reaching a stable or working version, save the progress for future reference. 

Vibe coding is about trusting the AI to handle the technicalities. One should focus more on creativity, problem-solving, and user experience rather than traditional coding.

The Future of Vibe Coding

Many industries, such as tech startups, e-commerce platforms, web development agencies, and educational technology, are adopting the vibe coding. According to Business Insider, various job postings from industry giants like Visa, Reddit, DoorDash, and cybersecurity unicorn Snyk are openly demanding experience or familiarity with AI code generators like Cursor and Bolt. The primary reason for this trend is to enhance the efficiency of the coding process. Alex Balazs, CTO of Intuit, states that "a great engineer using one of these tools can be up to 40% faster in terms of coding."

Another reason for its future growth is that it makes building software accessible to non-developers. AI-driven approaches enable people to collaborate with AI by simply explaining their desired outcome in plain language rather than writing lines of code. Titles like "Vibe Coder", "Fullstack Vibe Coder", and "AI Vibe Code Intern" are appearing in job listings from entry-level to senior positions in the global world. Experts clarify that it is not a replacement for engineers but a booster for them. 

Limitations of Vibe Coding

While vibe coding has transformed coding and app development, it has also sparked numerous concerns regarding security, quality, and complexity. Although AI technologies are competent at producing typical patterns, they frequently struggle when confronted with unique, complex, or highly customised requirements.

One of the most critical risks is associated with security vulnerabilities. The informal nature of AI-generated code may contain hidden bugs and security flaws, especially if prompts are vague, leading to the exploitation of vulnerabilities. Vibe code often prioritises rapid functionality over optimised architecture, which leads to inefficient resource utilisation and performance bottlenecks. The codes may lack clear structure, consistent naming conventions, and documentation, making it difficult for developers to maintain over time. The understanding of the AI codebase is harder due to its unclear reasoning, making debugging a challenging task. 

If developer teams rely too much on AI, their basic coding skills may suffer, and they may not be able to fix problems on their own. Using AI tools, making API calls, and spending a lot of time debugging might add up to costs that are higher than intended, which can sometimes be more than the savings from quick prototyping.

Conclusion

Vibe coding is appearing to be a game changer; it has provided a major shift from traditional coding to generative AI solutions. It has the ability to enhance developers’ productivity by providing straightforward answers, handling routine coding tasks, and reducing the need to context switch. It optimises their workflow by conserving mental energy, identifying coding errors, and potential vulnerabilities in the software. Karpathy described vibe coding as one where developers “fully give in to the vibes, embrace exponentials and forget that the code even exists.”

Vibe coding is considered to be best suited for rapid prototyping and small-scale projects, but for robust, scalable, and secure applications, traditional engineering practices and experienced oversight remain essential. 

The future of AI coding appears promising. It is set to redefine software development by merging traditional coding with AI-driven solutions. There is a need to apply best practices in the industry where both traditional and AI codes can go hand in hand to maximise the efficiency and minimise the risks involved. This paradigm shift is leading to increased accessibility in coding, enabling individuals without extensive programming skills to make meaningful contributions to software development.

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