×
Feeling it through: “Vibe coding” is transforming development as AI handles the code
Written by
Published on
Join our daily newsletter for breaking news, product launches and deals, research breakdowns, and other industry-leading AI coverage
Join Now

“Vibe coding” is emerging as a controversial approach to software development, championed by AI heavyweight Andrej Karpathy, former Tesla AI chief and OpenAI co-founder. This coding philosophy leverages AI assistants to radically streamline development by minimizing hands-on coding and embracing AI-generated solutions. The technique represents a significant shift in development practices, raising important questions about the balance between AI-augmented productivity and traditional software engineering disciplines as large language models become increasingly capable at code generation.

The big picture: Vibe coding represents a development approach where programmers rely heavily on AI to generate code while minimizing their own keyboard interaction.

  • The concept gained attention after Andrej Karpathy, a Stanford Ph.D. and former Tesla AI head, described it as “fully giving in to the vibes, embracing exponentials, and forgetting that the code even exists.”
  • For some developers, vibe coding appears to offer liberation from tedious coding best practices, transforming development from work into something closer to play.

Key characteristics: Vibe coding combines several distinct practices that leverage AI’s capabilities to minimize traditional development tasks.

  • Developers accept AI-generated code without detailed review, relying on the AI to handle errors and debugging.
  • The approach focuses on rapid prototyping and iteration rather than meticulously crafted code.
  • Human involvement shifts toward high-level direction while AI handles implementation details.

The upside: Vibe coding offers several potential productivity advantages for experienced developers.

  • Backend setup happens quickly, enabling faster iteration and experimentation with minimal risk.
  • AI systems can automatically detect errors and often handle vague prompts effectively.
  • Developers can focus on creative direction rather than implementation specifics.

The downside: The approach suffers from significant limitations that prevent it from replacing traditional development.

  • The interface can be clunky, with slow precise editing and inefficient basic code changes.
  • Custom design implementation remains challenging for AI systems.
  • AI may make unpredictable changes that require developer intervention.

Reality check: Vibe coding requires substantial existing development knowledge and isn’t suitable for novices or production software.

  • Despite its casual-sounding name, effective vibe coding demands deep understanding of software engineering principles.
  • The technique works best as a productivity tool for experienced developers rather than a replacement for fundamental coding skills.
  • Complex, production-grade software development still requires traditional engineering approaches and careful code review.
What is AI vibe coding? It's all the rage but it's not for everyone

Recent News

Scaling generative AI 4 ways from experiments to production

Organizations face significant hurdles when moving generative AI initiatives from experimentation to production-ready systems, with most falling short of deployment goals despite executive interest.

Google expands Gemini AI with 2 new plans, leak reveals

Google prepares to introduce multiple subscription tiers for Gemini, addressing the gap between its free and premium AI offerings.

AI discovers potential Alzheimer’s cause and treatment

AI identifies PHGDH gene as a direct cause of Alzheimer's disease beyond its role as a biomarker, offering a new understanding of spontaneous cases and potential treatment pathways.