Introduction

  • TL;DR: In early 2025, Andrej Karpathy, a founding member of OpenAI, coined a term that perfectly captured the zeitgeist of modern software development: “Vibe Coding.” It describes a shift where developers stop writing code line-by-line and instead “give in to the vibes,” delegating the implementation entirely to AI. This post explores what Vibe Coding is, how it works, and why it represents a double-edged sword for the software industry.
  • Vibe Coding is an AI-first approach where developers prompt LLMs and check if the output “vibes” (works), often without reading the underlying code.
  • Tools like Cursor, Claude, and Bolt.new enable this loop of “Prompt -> Run -> Fix.”
  • While it democratizes app creation and boosts speed, it risks creating unmaintainable, insecure codebases known as “spaghetti code.”

What is Vibe Coding?

Traditionally, coding required a deep understanding of syntax, logic, and libraries. Vibe Coding abstracts this away. As Karpathy tweeted, it involves “forgetting that the code even exists.” The developer acts less like an architect and more like a product manager, describing requirements in natural language and critiquing the result.

If the app looks right and functions correctly (the “vibe” is good), the code is accepted, regardless of its internal quality.

Why it matters: This marks the transition of programming from a linguistic skill (knowing Java/Python) to a logic and intent skill. The barrier to entry for building software has never been lower.

The Vibe Coding Workflow

The process is iterative and conversational, heavily relying on “Copy-Paste Driven Development” powered by LLMs.

  1. Intent: You tell the AI, “Make a snake game where the snake speeds up every time it eats an apple.”
  2. Generation: The AI (e.g., Cursor Composer) writes the HTML, CSS, and JavaScript.
  3. Execution: You run the game.
  4. Feedback Loop:
    • Scenario A: It works. You move on.
    • Scenario B: It breaks. You copy the error message, paste it back to the AI with “Fix this,” and repeat.

At no point does the “Vibe Coder” necessarily inspect the for loops or memory management strategies.

Why it matters: This workflow allows for rapid iteration. What used to take days of boilerplate writing now takes minutes of prompting.

The Risks: The “Black Box” Problem

While seductive, Vibe Coding introduces significant risks, particularly for long-term projects.

  • Maintenance Nightmare: If you don’t understand the code you “wrote” (generated), you cannot easily extend or debug it when the AI eventually fails to understand a complex nuance.
  • Security Gaps: AI models prioritize functionality over security. Vibe-coded apps may work perfectly but contain SQL injection vulnerabilities or hardcoded API keys that the user never noticed.
  • Dependency Hallucinations: LLMs might import libraries that don’t exist or use outdated methods, leading to fragile builds.

Why it matters: Vibe Coding is excellent for prototypes, MVPs (Minimum Viable Products), and hobby projects. However, for enterprise-grade software, it must be paired with rigorous code review and testing—reintroducing the human oversight that Vibe Coding tries to bypass.

Conclusion

  • Vibe Coding is here to stay. It is the natural evolution of coding in the age of generative AI.
  • The best developers of the future will not be those who only vibe code, but those who use it to move fast while knowing when to pause, read the code, and ensure the foundation is solid.
  • Vibe Coding prioritizes intent and execution over syntax.
  • It creates a risk of technical debt if used without understanding.
  • The role of a developer is shifting towards AI management.

Summary

  • Vibe Coding prioritizes intent and execution over syntax, powered by tools like Cursor and LLMs.
  • It democratizes software development but creates risks of technical debt and security vulnerabilities.
  • The best developers will combine Vibe Coding speed with traditional code review practices.

#VibeCoding #LLM #SoftwareEngineering #AITrends #Cursor #AndrejKarpathy #GenerativeAI #CodingWithAI

References