Vibe Coding: Is Prompting the New Programming?

Remember when writing code meant memorizing syntax and debugging for hours? Those days might be numbered thanks to so called Vibe Coding, the development approach that's changing the relationship between humans and machines in the coding process.

What is Vibe Coding?

Vibe Coding, a term popularized by former OpenAI researcher Andrej Karpathy, represents the shift from writing code line-by-line to simply describing what you want in plain English. It's like the difference between building furniture from scratch versus telling someone exactly what you need and having them build it for you.

Instead of meticulously crafting functions and debugging edge cases, developers describe their intentions, and AI tools generate the corresponding code. This isn't just convenience—it's a fundamental shift in how we approach software development.

The Positive Vibes of Vibe Coding

The most obvious benefit is being able to communicate with computers in human language. Rather than translating your ideas into a programming language, you can simply explain what you want:

"Create a form that validates email addresses and prevents SQL injection attacks."

The AI handles the technical implementation, freeing you to focus on solving the actual problem. This places less emphasis on syntax and knowledge of language mechanics and more emphasis on business logic and functional specifications.

In a way, vibe coding is just like thinking of a problem to solve, Googling for the best way to do it, scouring forums and code samples for a methodology, copy and pasting a few examples, and then modifying it to fit within your code. Except now an AI has already read all of Stack Overflow and simply skips to the end of this process for you.

The barriers to getting started with code are dropping to zero for the novice while the productivity of those who already know code is going asymptotic.

The Negative Vibes of Vibe Coding

You need to know code. Sorry would-be vibes-only coders, but this is inescapable. AI is not always great at understanding a human's intent and executing it perfectly. It makes things up, it builds illogical flows, and it duplicates work. Language is ambiguous, code is deterministic and when the two collide user intent can get lost in translation.

As applications get more and more complex, the AI will get less and less accurate due to limited context windows. Small code bases can be loaded into a context window in their entirety and get great results. However, AI will lose the script in large code bases and duplicate code, rewrite functionality, or otherwise mess up unrelated corners of your code.

In short, they require supervision like a curious toddler in a store that only sells forks and electrical outlets.

The Tools of the Vibe Coder

While many will go straight to Claude.ai or OpenAI to ask it for a code snippet, this quickly gets unwieldy when you need more than a few lines of code or revisions. A few of the more popular tools being adopted by Vibe Coders are Replit Agent, Lovable, Bolt.new, v0, and Devin. These are primarily focused on the front end and almost completely abstract away an application's code entirely.

More advanced workflows typically incorporate an AI-enabled IDE (Integrated Development Environment) such as Cursor, Windsurf, Github Copilot, or Cline. For backend and database development, emerging tools like GibsonAI are building robust and production-ready backends.

Where Vibe Coding is Going

Well, it certainly isn't going away. The good news is that using AI to write code for you is going to teach you how to code whether you like it or not. Most AI coding tools are good at explaining their output and showing their work, and this will only improve as reasoning models are refined. Vibe coders will necessarily soak up some of this coding knowledge. However, they may not learn proper syntax, structure, and common pitfalls of a programming language. One can argue that it is analogous to no longer needing to be a whiz in long division in the age of calculators. Who needs stick shifts in the age of automatic transmissions? (still love me a clutch pedal, tho)

Recently Dario Amodei, CEO of Anthropic said that within 2025, 90% of code will be written by AI. While this is likely true, it is not necessarily AI taking over jobs, it is simply that engineers are relying on AI to create code on their behalf under strict supervision. They use AI more like a detective who delegates all the paperwork so they can crash cars and aim for the bushes.

Vibe coders will continue to build cool things, but as they start wanting to build more advanced features, use poorly-documented esoteric APIs, or deal with complex business logic, they'll need to know some code.

The Challenges We Still Face

• Quality Control: AI-generated code still requires human oversight to ensure it meets quality and security standards.

• Complex or Unique Requirements: Some specialized systems still benefit from traditional coding approaches due to sparse documentation.

• Evolving Skills: Developers need to develop expertise in effectively prompting and guiding AI assistants.

The Evolution of Our Relationship with Code

VibeCoding isn't just changing how we write code—it's changing who can participate in software creation. By focusing on intentions rather than implementation, we're witnessing a democratization of development that promises to unleash creativity from unexpected sources.

As tools like GibsonAI demonstrate, even the most complex technical domains can be transformed into conversational interactions, enabling teams to design and deploy sophisticated systems with unprecedented speed and simplicity.

The future of coding isn't about knowing more languages—it's about effectively communicating our intentions to increasingly capable AI partners. And that is simply put, the most significant paradigm shift in software development since the invention of high-level programming languages.