If you are on social media, you may have heard the term “Vibe Coding.” It’s been trending, and several big names are promoting it. Vibe coding is a new way of writing software where developers rely heavily on artificial intelligence to generate code. Instead of writing every line manually, the developer explains what they want in plain language, and an AI model turns that idea into working code. This approach is gaining attention because it changes how fast and how casually software can be built.
The term “vibe coding” became popular after Andrej Karpathy, co-founder of OpenAI, described it in early 2025. He explained it as a style of coding where you stop worrying about every detail and let the AI handle most of the work. While the name is new, the idea is not. Many developers were already doing this when tools like ChatGPT, GitHub Copilot, and similar AI coding assistants became public.
Vibe coding focuses more on direction than precision. You guide the AI with high-level ideas, and the AI fills in the technical details. It all depends on how you give AI the prompts.
How vibe coding works in practice
Vibe coding starts with a prompt. The developer tells the AI what they want to build, such as a login system, a simple app, or a new feature. The instruction does not have to be very detailed. The AI uses its training on large amounts of code to generate a solution.
Once the code is generated, the developer tests it. If something breaks or does not work as expected, the developer can ask the AI to fix the issue or change the behavior. This process often repeats several times. The goal is not perfect code on the first try, but fast progress.
In many cases, the developer may not fully understand every line of the generated code. That is part of the “vibe” approach. You trust the AI enough to move forward quickly, especially for small projects or experiments.
Why developers are interested in vibe coding
One major reason Vibe coding is becoming popular is speed. Building a prototype that once took days can now take hours or even minutes. This is useful for testing ideas, building demos, or launching early versions of products.
Another benefit is reduced manual effort. Repetitive tasks like setting up basic project structure or writing boilerplate code can be handled by AI. This allows developers to focus more on ideas and user experience instead of syntax.
Vibe coding also lowers the entry barrier. People with limited coding experience can build functional software by clearly explaining what they want. This does not replace skilled developers, but it does change who can participate in building software.
Popular tools used for vibe coding
Several AI-powered tools support vibe coding today. GitHub Copilot is widely used inside code editors. Cursor offers an AI-first coding environment. Other tools like Codeium, Gemini, Replit, Qodo, and Amazon CodeWhisperer also help developers generate and modify code using natural language. Google also recently introduced Antigravity for vibe coding. I tried it, and it works really well. It does everything from planning a project to making folder structure, installing modules, and writing code.
These tools are powered by large language models that understand both human language and programming languages. This is what makes vibe coding possible.
If you want to try vibe coding tools, here’s a list:
- Lovable
- Bolt
- Antigravity
- v0
- Cursor
- Tempo Labs
- Replit
- Memex
- Base44
The downsides of vibe coding
While vibe coding is fast and convenient, it also comes with risks. One major concern is loss of understanding. If developers rely too much on AI-generated code without reviewing it, they may struggle to fix problems later. This can make long-term maintenance harder.
Another issue is compliance and data handling. AI-generated code may process user data in ways the developer did not fully plan or review. This can create legal or regulatory problems, especially in business applications.
There is also the risk of messy codebases. Code that “just works” is not always clean, secure, or efficient. Over time, this can slow down development instead of speeding it up.
Security concerns with vibe coding
Security is one of the biggest challenges with vibe coding. Faster development means less time spent reviewing code. This increases the chance that vulnerabilities reach production.
Fixing these issues can also be difficult if the team does not fully understand the generated code. In addition, using external AI tools can expose sensitive information if prompts include private data or intellectual property. Developers need to understand how AI tools handle and store data before using them in serious projects.
How vibe coding differs from traditional coding
Traditional coding requires careful planning and precise implementation. Every line is written and reviewed by the developer. Developers first make a system design and plan everything before start writing codes. After that, the developers start working on the code. Vibe coding shifts this responsibility to the AI. The developer acts more like a guide who gives direction instead of instructions.
This does not mean traditional coding is going away. For large, critical, or security-sensitive projects, careful human control is still essential. Vibe coding works best for prototypes, side projects, and fast experiments.
Is vibe coding the future of software development?
Vibe coding is not a replacement for skilled developers, but it is changing how development happens. It makes building software faster and more accessible. At the same time, it demands more awareness around testing, security, and long-term maintenance. So, vibe coding is not the future, but certainly it would be an important part of software development.
As AI tools improve, vibe coding will likely become a regular part of development workflows. The key is knowing when to rely on the vibe and when to slow down and read the code.
