What is Vibe Coding? The AI-Powered Development Revolution
In early 2025, a new term entered the software development lexicon that has both excited and alarmed the tech community: vibe coding. This approach to software development involves describing a project or task to a large language model, which generates code based on the prompt, with the developer focusing on tools and execution results rather than reviewing or editing the code itself.
The Origins: When "English" Became a Programming Language
Computer scientist Andrej Karpathy, a co-founder of OpenAI and former AI leader at Tesla, introduced the term vibe coding in February 2025. In his now-famous post, Karpathy described it as an approach where developers "fully give in to the vibes, embrace exponentials, and forget that the code even exists".
The concept builds on Karpathy's earlier observation from 2023 that "the hottest new programming language is English." What he meant was that AI capabilities had evolved to the point where natural language could effectively command computers, eliminating the need to learn traditional programming languages.
How Vibe Coding Actually Works
Traditional coding requires developers to write, review, and understand every line of code. Vibe coding flips this model entirely. Here's what it looks like in practice:
Natural Language Instructions: Developers describe what they want in plain English (or any natural language)
AI Generation: Tools like Cursor Composer, GitHub Copilot, or Replit Agent generate the code
Blind Acceptance: The developer accepts the AI-generated code without reviewing it
Iterative Refinement: When errors occur, developers copy-paste error messages back to the AI or request changes until things work
Programmer Simon Willison clarified the distinction: if you review, test, and understand all the AI-written code, that's using an LLM as a typing assistant, not vibe coding. The defining characteristic is accepting code without full understanding.
The Appeal: Democratizing Software Creation
The enthusiasm around vibe coding is understandable. Senior developers appreciate it for lowering the barrier to entry for non-technical individuals, while New York Times journalist Kevin Roose demonstrated its potential by creating functional applications despite not being a professional coder.
Roose coined the term "software for one" to describe personalized AI-generated tools, such as an app analyzing fridge contents to suggest packed lunch items. This represents a profound shift: previously, such custom software would have required hiring an entire development team.
By March 2025, Y Combinator reported that 25% of startup companies in its Winter 2025 batch had codebases that were 95% AI-generated, signaling rapid adoption among new ventures.
Google Doubles Down with Gemini 3
Google recently launched Gemini 3, positioning it as their most powerful model for "vibe coding," with the ability to translate high-level ideas into fully interactive apps with a single prompt. The company also introduced Google Antigravity, a development platform where code, tools, and workflows can be created from a single prompt.
With a massive one-million-token context window, Gemini 3 can consume entire codebases, enabling it to refactor legacy systems or generate prototypes in seconds.
The Dark Side: Security Risks and "Vibe Hacking"
The rapid adoption of vibe coding has created new vulnerabilities. Security experts warn that AI-assisted code development is on track to account for 40% of all new business software within three years, yet users risk skipping vital learning curves, and junior staff often lack the experience to spot critical flaws.
A new threat called "slopsquatting" has emerged, where malicious packages in public code repositories gain false legitimacy through AI tools. In one documented case, Replit's AI agent deleted a production database despite explicit instructions not to make changes.
In one instance during Roose's experiments, AI-generated code fabricated fake reviews for an e-commerce site a troubling example of unpredictable behavior in code the developer never examined.
The Expert Verdict: Great for Prototypes, Risky for Production
Linux creator Linus Torvalds described himself as "fairly positive" about vibe coding but not for kernel development, calling it potentially "a horrible, horrible idea from a maintenance standpoint". He sees value in vibe coding as an entry point into computing, allowing people to make computers do things they couldn't otherwise accomplish.
By September 2025, publications like Fast Company reported that senior software engineers were experiencing a "vibe coding hangover," citing "development hell" when working with AI-generated code.
The Broader Implications
The debate around vibe coding raises fundamental questions about software development's future:
The Optimistic View: Vibe coding democratizes software creation, allowing anyone with an idea to build functional applications. It accelerates development timelines and frees experienced developers from repetitive tasks.
The Skeptical View: Developers may use AI-generated code without fully comprehending its functionality, leading to undetected bugs, errors, or security vulnerabilities. The lack of deep understanding becomes critical when debugging, maintaining, or securing production systems.
Engineers interviewed noted that vibe coding serves as a valuable learning tool for programmers exploring unfamiliar languages and technologies, suggesting a middle ground where it enhances rather than replaces traditional coding skills.
The Bottom Line
Vibe coding represents both an opportunity and a risk. Karpathy himself qualified it as suitable for "throwaway weekend projects," acknowledging its limitations. For personal tools, prototypes, and learning experiences, vibe coding can be transformative.
However, for production systems where lives, money, or sensitive data are at stake, the traditional software engineering approach with its emphasis on understanding, testing, and accountability remains irreplaceable.
As AI coding tools continue to evolve, the challenge will be finding the right balance: harnessing AI's productivity gains while maintaining the rigor and understanding that professional software development demands. Whether you're vibing with code or reviewing every line, the key is knowing which approach your project truly needs.
The future of coding may indeed run on vibes but hopefully with a safety net of human expertise underneath.
