Vibe Coding: Letting AI Catch the Drift of Your Dev Needs
From vague ideas to working scripts — how AI is reshaping the way we code with intent, not syntax.
What Even Is Vibe Coding?
Vibe coding is an emerging approach to programming where one describes the vibe or provides natural language prompts to AI-powered code generators, such as Codex, Cursor, and Replit Ghostwriter, and the AI would output the code. So instead of writing detailed logic/syntax line-by-line in programming languages such as Python or Javascript, one would tell the AI what they want, such as “Make a simple web app with a button that shows a random joke”, then the AI would output the code, filling in logic, structure, and any needed frameworks. Essentially, you focus on what you want, and the AI figures out how.
The primary benefits of vibe coding are fast prototyping, it's friendly, and it allows one to experiment with high-level workflows without being bogged down by intricate details. Now, some believe that vibe coding could be detrimental for programmers because they do not learn how their code actually functions, so they lack deep knowledge of their work. The lack of understanding of programming fundamentals makes it harder.
Furthermore, over-reliance on AI tools leads to complacency, reducing critical thinking skills that developers need to build scalable, secure, and maintainable systems.
This YouTube video goes into detail about what happens when vibe coding goes wrong and offers tips on how to vibe code correctly:
How It Works: Behind the Scenes of Prompt-to-Code Generation
Vibe coding operates due to a mixture of transformer models, fine-tuning, and natural language parsing. Transformer models are a type of deep learning architecture that processes sequences of words in parallel rather than sequentially. They can understand what users request in vibe coding by modeling the relationship between words, essentially generating code snippets based on patterns they have learned from large datasets consisting of code and natural language texts.
The second operation behind vibe coding is fine-tuning. It involves taking a large pre-trained language model similar to GPT and training it further on a specific task or dataset. Since vibe coding tools are specialized, the tools need to generate context-appropriate code, so fine-tuning helps the model learn coding conventions and understand APIs, frameworks, and patterns.
The third mechanism behind vibe coding is natural language parsing. Natural language parsing involves breaking down a user’s text input so that the machine will understand the intent behind the text and the structure behind it. There are two categories of natural language parsing: synthetic parsing and semantic parsing. Synthetic parsing involves understanding the structure of sentences, and the latter involves grasping the meaning or intent.
From Vague to Valid: How Precise Do You Really Need to Be?
One of the best ways to get better at vibe coding is to learn to write precise prompts. Learning to write precise prompts improves the results of vibe coding. So the question arises, “How far can you vibe before the AI misses the mark?”. Well, it’s complicated.
For starters, there is a spectrum of prompt specificity. Prompts can range from vague: “Make a website that looks modern?” to precise: “Build a responsive React SPA with Tailwind CSS that includes a fixed top navbar, a centered hero image, and smooth scrolling between sections”. The first prompt asking for a modern website could output literally anything. The AI isn’t told what the website should look like specifically, and the prompt language “modern” is too vague. But the second prompt would output a clean, precise, and comprehensive code/solution consisting of cleanly separated React functional components such as Navbar, hero, and Sections. It would also include responsive designs such as tailwinds and breakpoints, a fixed navbar, and anchor links in the navbar to allow for smooth scrolling. So the lesson here is to learn basic prompt skills if you want to vibe code.
The Benefits: Speed, Accessibility, and Creative Prototyping
One of the main benefits of vibe coding is that it lowers the barrier for entry-level coders and increases productivity. Oftentimes, entry-level coders are intimidated and afraid to get into coding. This is because the world of software development/programming is vast and often confusing for beginners who are trying to get into coding. Vibe coding bridges the gap because it allows beginner coders to use natural language to create code. So instead of having to learn a programming language syntax of Python, Java, or C++, beginners can just describe what they want in detail in natural language, and the AI agent (check out my article on Agentic AI) will output the code.
Another benefit is the immediate feedback feature of Vibe coding. Coders can immediately see the output of their code. This can build intuition through example-based learning. New developers can also focus on the logic part of their code rather than worrying about memorizing syntax and functions.
Vibe coding allows professional programmers to prototype faster. AI agents assist with their tasks and act more as a pair programmer than anything else. Similarly to beginner programmers, professionals also get to spend more time on logic and architecture rather than implementation.
The Pitfalls: When AI Gets the Vibe Wrong
AI often misinterprets vague prompts, leading to unintended outputs. Another problem is that there is increased security vulnerability, bugs that go unnoticed, incorrect logic, a lack of optimization, and domain context. AI-generated algorithms often have higher time and space complexity than needed. Custom architectures, such as Redux middleware or GraphQL resolvers, are better handcrafted since they involve complex systems with layered services.
Another pitfall not considered is how vibe coding negatively impacts the life cycle of software development and maintenance. If Vibe coders are unable to perform basic levels of software support, then this will be costly in the future. A similar analogy I saw online that explains the potential issue here is how everyone is capable of completing DIY projects with simple instructions online, but very few can complete complex versions of DIY projects that require deep knowledge. As of now, the judgment is still up in the air; in time, we will see whether vibe coding is mostly beneficial or damaging in the long run, but for now, my advice would be to focus on prompt skills if you want to vibe code.