What is vibe coding?

In software engineering , development is reshaping from strict, manual coding and becoming more flexible and AI-powered—and vibe coding is at the forefront of this change. “Vibe coding” is introduced by renowned Computer scientist  Andrej Karpathy in February 2025 and emphasized the significance of AI tools in software development.

This concept is in line with developments in artificial intelligence (AI) technologies, especially large language models (LLMs) like ChatGPT, Claude and OpenAI’s Codex to help developers stay in the zone of creativity and automate coding works. 

Vibe coding is a fresh take in coding where users express their intention using plain speech and the AI transforms that thinking into executable code. The goal of vibe coding is to create an AI powered development environment where AI agents serve as coding assistants making suggestions in real time, automating tedious processes and even producing standard codebase structures.¹

By prioritizing experimentation before refining structure and performance, vibe coding embraces a “code first, refine later” mindset. This opens opportunities for developers to prioritize building first and optimizing later. Also, in an agile framework, vibe coding aligns with the principles of fast-prototyping, iterative development and cyclical feedback loops. This allows enterprises to focus on these principles while fostering innovation, instinctive problem-solving and flexible coding capabilities. However, AI simply generates code, but true creativity, goal alignment and out-of-the-box thinking remain uniquely human so human input and oversight is important and cannot be overridden.

To implement vibe coding in practice, the user needs to follow the following steps:

Step 1. Choose any AI coding assitant platform: Choose depending upon your technical, performance or cost requirement. For example, Replit is one of the dynamic and versatile platforms for translating ideas into application code.

Step 2. Define your requirement: In this step, the user provides a clear prompt describing what they intend to develop. The more effective the prompt is, the better the output will be.

Here is a sample prompt: Create a lively and interactive visual experience that reacts to music, user interaction or real-time data. Your animation should include smooth transitions and colorful and lively visuals with an engaging flow in the experience. The animation should feel organic and responsive to the music, user interaction or live data and facilitate an experience that is immersive and captivating. Complete this project using JavaScript or React, and allow for easy customization to set the mood for other experiences.

The prompt is clearly specific, context relevant and goal oriented.

Step 3. Code refinement: From the previously outlined prompt, a basic and imperfect code will be created using the building structure of the animation task and can be considered as a starting point. Once the user checks the basic version, the scope of refinement will be defined. This happens by refining the prompt.

Step 4. Final code review and shipping: This is the last step where the code is reviewed after refinement based on the polished prompts so that the functional code generated can be used for final deployment.

Vibe coding is not just a buzz, many coders as well as users with no prior coding skills are leveraging vibe coding for developing market specific applications.

Many startups especially those in the Y Combinator environment are leveraging it to develop and launch AI-powered apps more quickly.² Replit, Cursor and Microsoft GitHub Copilot are popular tools available that enable users to experiment with AI assisted coding.

Vibe coding is undoubtedly potent however it has some technical and real world challenges. Here are some of the key challenges listed:

1. Technical complexity: Vibe coding can handle basic standard frameworks but for real world applications where technical requirements can be novel or complex, vibe coding becomes challenging.³

2. Code quality and performance issues: Vibe coding is helpful to test applications and create prototypes, but it still requires optimization and refinement to make sure that the code quality is maintained. Vibe coding is not an ideal choice for distributed applications because it requires structured level architecture and sophisticated optimization strategies.

3. Debugging challenges: Code generated by AI is challenging to debug because it’s dynamic and lacks architectural structure.

4. Maintenance and updates: Many times, if the software application is not updated in a timely manner, it becomes outdated which is why they require regular maintenance as well as updates. Applications built using AI generated code face maintenance and update challenges if the code structure is not properly maintained. This can cause developers to struggle to understand the underlying logic when trying to keep it updated and optimized.

5. Security concerns: This limitation is the most critical as it can lead to several risks and extreme vulnerabilities. Code generated using AI is often excluded from code reviews and security checks, leading to unseen vulnerabilities that can go unnoticed and be exploited.

1. Quick prototyping: As vibe coding continues to gain traction in the ecosystem, there will be a change in the way ideas get formed. Rapid prototyping is becoming a key enabler for teams to move ideas from early-stage concepts to functional prototype to scale. This ability is valuable for testing ideas in the market to see if that idea will actually solve a problem or if strategy needs to change altogether.⁴

2. Problem first approach: The change from building code using a rigid coding style to dynamic structure enables swift innovation as the act of solving the problem becomes the cornerstone for developers more than the tech stack itself.

3. Reduce risk, maximize impact: Vibe coding will enable businesses to quickly progress with a minimum viable product (MVP), cheaply experiment with ideas and adopt and adapt based on the feedback. This lowers sunk costs, increases the spread of risk and allows for pivoting because resources are only committed to validated concepts.

4. Multimodal switch: Vibe coding is evolving into multimodal programming with voice, visual and text-based coding to enhance productivity. Some of the most fascinating trends include voice-driven coding, visual programming interfaces, AI-enabled code generation and hybrid development environments. These trends improve coding’s usability, flexibility and intuitiveness, reshaping the landscape of software development.

The evolution of VibeOps is being driven by the growing complexity and limits of traditional software development but as its capabilities emerge, it is anticipated to gain popularity. The AI-driven automation of VibeOps helps reduce costs and frees engineers to concentrate on innovation but it’s not without its challenges. VibeOps will need improvement and a mixed strategy in which AI complements human knowledge rather than completely replacing it.⁴

In conclusion, vibe coding is still in its infancy. Combining generative AI models with smart coding assistants makes software development more dynamic and natural. By integrating coding agents into programming language (Python) code editor integrated development environments (IDEs), it eliminates the need to manually write every line of code for web apps. This equips early coding beginners, programmers and nonprogrammers with real-time code production and increasing workflow efficiency. However, VibeOps will always require human intervention to achieve its intended outcome.^{5, 6}