# Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI

**Authors:** Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee  
**arXiv:** [2505.19443](https://arxiv.org/abs/2505.19443)  
**Date:** 2025-05-26  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2505.19443v1/

## Key points

- Emphasizes intuitive, human-in-the-loop interaction
- Supports ideation and creative exploration
- Excels in early-stage prototyping and education
- Enables autonomous software development through goal-driven agents
- Capable of planning, executing, testing, and iterating tasks with minimal human intervention
- More suitable for enterprise-grade automation, codebase refactoring, and CI/CD integration
- Combine natural language interfaces with autonomous execution pipelines
- Focuses on building trustworthy, explainable, and collaborative systems
- Vibe coding fosters co-creation and creativity
- Agentic coding represents a shift towards autonomous software engineering systems

## Summary

This comprehensive analysis explores two emerging paradigms in AI-assisted software development: vibe coding and agentic coding. Vibe coding emphasizes intuitive, human-in-the-loop interaction through prompt-based workflows that support ideation and creative exploration. On the other hand, agentic coding enables autonomous software development through goal-driven agents capable of planning, executing, testing, and iterating tasks with minimal human intervention. The study proposes a detailed taxonomy covering conceptual foundations, execution models, feedback loops, safety mechanisms, debugging strategies, and real-world tool ecosystems for both paradigms. Through comparative workflow analysis and 20 detailed use cases <mark>,</mark> it is illustrated how vibe systems excel in early-stage prototyping and education while agentic systems are more suitable for enterprise-grade automation <mark>,</mark> codebase refactoring <mark>,</mark> and CI/CD integration. Emerging trends in hybrid architectures that combine natural language interfaces with autonomous execution pipelines are also examined. The future roadmap for agentic AI focuses on building trustworthy <mark>,</mark> explainable <mark>,</mark> and collaborative systems to enhance the cognitive model underlying artificial agents. The review concludes by emphasizing the importance of harmonizing the strengths of both paradigms within a unified human-centered development lifecycle. Vibe coding is seen as rooted in intuition-driven development that fosters co-creation and creativity while agentic coding represents a shift towards autonomous software engineering systems. These complementary pillars contribute uniquely to the evolving landscape of human-machine co-development in AI-driven software engineering.