Vibe Coding

Published

June 9, 2026

Abstract

Vibe coding is a software development term that refers to the practice of prompting AI tools to generate code rather than writing code manually.

What is Vibe Coding

The concept emerged with the developments of large language models (LLMs) like ChatGPT, Claude, etc. to automate coding work. Software engineering development is reshaping from strict, manual coding and becoming more flexible and AI-powered. The term is coined by Andrej Karpathy, in February 2025 where you “fully give in to the vibes, embrace exponentials, and forget that the code even exists.”:

It emphasized the significance of AI tools and their increasing capabilities. Vibe coding is a fresh take in coding where users express their intention using plain text or speech and 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.

Paradigm shift

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.

Inline with agile framework, specifically, principles of fast-prototyping, iterative development and cyclical feedback loops; vibe coding allows developpers to focus on these principles while churning out protoypes by eliminating.

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 i 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.

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.

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.

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.

How to implement vibe coding ?

To implement vibe coding in practice, developers needs:

  1. Any AI coding assitant platform: choose depending upon your technical, performance or cost requirement.
  2. Define your requirement: Developers provides a clear prompt describing what they intend to develop. The more effective the prompt is, the better the output will be.
  3. Code refinement: From an initial prompt, a basic and imperfect codebase will be genretad serving as a boiler plate for the project. Developpers refined the codebase in back and forth interaction with the AI assistants.
  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.

Limitations of vibe 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.
  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. 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.