Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
2025/05/26 by Ranjan Sapkota, Sapkota, Ranjan, Konstantinos I. Roumeliotis +3 · 20 citations
Computer Science · #Artificial Intelligence (cs.AI) #Cellular Automata and Applications #Computation and Language (cs.CL) #FOS: Computer and information sciences #Software Engineering (cs.SE)
paper · pdf · doi:10.48550/arxiv.2505.19443
openalex publication_date 2025/05/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Abstract
This review presents a comprehensive analysis of two emerging paradigms in AI-assisted software development: vibe coding and agentic coding. While both leverage large language models (LLMs), they differ fundamentally in autonomy, architectural design, and the role of the developer. Vibe coding emphasizes intuitive, human-in-the-loop interaction through prompt-based, conversational workflows that support ideation, experimentation, and creative exploration. In contrast, agentic coding enables autonomous software development through goal-driven agents capable of planning, executing, testing, and iterating tasks with minimal human intervention. We propose a detailed taxonomy spanning conceptual foundations, execution models, feedback loops, safety mechanisms, debugging strategies, and real-world tool ecosystems. Through comparative workflow analysis and 20 detailed use cases, we illustrate how vibe systems thrive in early-stage prototyping and education, while agentic systems excel in enterprise-grade automation, codebase refactoring, and CI/CD integration. We further examine emerging trends in hybrid architectures, where natural language interfaces are coupled with autonomous execution pipelines. Finally, we articulate a future roadmap for agentic AI, outlining the infrastructure needed for trustworthy, explainable, and collaborative systems. Our findings suggest that successful AI software engineering will rely not on choosing one paradigm, but on harmonizing their strengths within a unified, human-centered development lifecycle.
Citations
- AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios
- MASLab: A Unified and Comprehensive Codebase for LLM-based Multi-Agent Systems
- MLZero: A Multi-Agent System for End-to-end Machine Learning Automation
- Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks
- AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges
- AI LEGO: Scaffolding Cross-Functional Collaboration in Industrial Responsible AI Practices during Early Design Stages
- Tests as Prompt: A Test-Driven-Development Benchmark for LLM Code Generation
- Internet of Agents: Fundamentals, Applications, and Challenges
- Web-Bench: A LLM Code Benchmark Based on Web Standards and Frameworks
- MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering
- Nature's Insight: A Novel Framework and Comprehensive Analysis of Agentic Reasoning Through the Lens of Neuroscience
- MARCO: Multi-Agent Code Optimization with Real-Time Knowledge Integration for High-Performance Computing
- Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency
- Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents
- Structured Prompting and Feedback-Guided Reasoning with LLMs for Data Interpretation
- Characterizing AI Agents for Alignment and Governance
- mAIstro: an open-source multi-agentic system for automated end-to-end development of radiomics and deep learning models for medical imaging
- Seeking Specifications: The Case for Neuro-Symbolic Specification Synthesis
- From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review
- Understanding and supporting how developers prompt for LLM-powered code editing in practice
- SAGA: A Security Architecture for Governing AI Agentic Systems
- Advancing Multi-Agent Systems Through Model Context Protocol: Architecture, Implementation, and Applications
- Generative to Agentic AI: Survey, Conceptualization, and Challenges
- From Prompts to Propositions: A Logic-Based Lens on Student-LLM Interactions
- Evolution of AI in Education: Agentic Workflows
- Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues
- A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
- A Self-Improving Coding Agent
- ReadMe.LLM: A Framework to Help LLMs Understand Your Library
- Agentic Workflows for Economic Research: Design and Implementation
- A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems
- Unraveling Human-AI Teaming: A Review and Outlook
- Multimedia and Visual Analytics in the Agentic Era
- Multi-Mission Tool Bench: Assessing the Robustness of LLM based Agents through Related and Dynamic Missions
- Pel, A Programming Language for Orchestrating AI Agents
- Transforming cybersecurity with agentic AI to combat emerging cyber threats
- Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
- Challenges and Paths Towards AI for Software Engineering
- Large Language Model Agent: A Survey on Methodology, Applications and Challenges
- Collab: Controlled Decoding using Mixture of Agents for LLM Alignment
- Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models
- Why Do Multi-Agent LLM Systems Fail?
- VeriLA: A Human-Centered Evaluation Framework for Interpretable Verification of LLM Agent Failures
- Multi-Agent Systems Execute Arbitrary Malicious Code
- TFHE-Coder: Evaluating LLM-agentic Fully Homomorphic Encryption Code Generation
- VeriMind: Agentic LLM for Automated Verilog Generation with a Novel Evaluation Metric
- Beyond Black-Box Benchmarking: Observability, Analytics, and Optimization of Agentic Systems
- LLMs' Reshaping of People, Processes, Products, and Society in Software Development: A Comprehensive Exploration with Early Adopters
- Agentic AI Needs a Systems Theory
- Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs
- Assistance or Disruption? Exploring and Evaluating the Design and Trade-offs of Proactive AI Programming Support
- Agentic AI Software Engineers: Programming with Trust
- Repo2Run: Automated Building Executable Environment for Code Repository at Scale
- Multi-Agent Risks from Advanced AI
- Training Turn-by-Turn Verifiers for Dialogue Tutoring Agents: The Curious Case of LLMs as Your Coding Tutors
- LLM Agents Making Agent Tools
- A-MEM: Agentic Memory for LLM Agents
- LLM-Generated Microservice Implementations from RESTful API Definitions
- From PowerPoint UI Sketches to Web-Based Applications: Pattern-Driven Code Generation for GIS Dashboard Development Using Knowledge-Augmented LLMs, Context-Aware Visual Prompting, and the React Framework
- CLOVER: A Test Case Generation Benchmark with Coverage, Long-Context, and Verification
- Every Software as an Agent: Blueprint and Case Study
- Adaptive Self-improvement LLM Agentic System for ML Library Development
- Develop AI Agents for System Engineering in Factorio
- Layered Chain-of-Thought Prompting for Multi-Agent LLM Systems: A Comprehensive Approach to Explainable Large Language Models
- Agentic Workflows for Conversational Human-AI Interaction Design
- A Comprehensive Survey of Agents for Computer Use: Foundations, Challenges, and Future Directions
- Towards Detecting Prompt Knowledge Gaps for Improved LLM-guided Issue Resolution
- Conversation Routines: A Prompt Engineering Framework for Task-Oriented Dialog Systems
- CodeCoR: An LLM-Based Self-Reflective Multi-Agent Framework for Code Generation
- Eliza: A Web3 friendly AI Agent Operating System
- ProgCo: Program Helps Self-Correction of Large Language Models
- Agentic Systems: A Guide to Transforming Industries with Vertical AI Agents
- Large Language Model-Brained GUI Agents: A Survey
- BugSpotter: Automated Generation of Code Debugging Exercises
- Towards Specification-Driven LLM-Based Generation of Embedded Automotive Software
- RedCode: Risky Code Execution and Generation Benchmark for Code Agents
- Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks
- LLMs: A Game-Changer for Software Engineers?
- SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt Types
- PRefLexOR: Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning and Agentic Thinking
- Thinking LLMs: General Instruction Following with Thought Generation
- Agent S: An Open Agentic Framework that Uses Computers Like a Human
- A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languages
- AutoSafeCoder: A Multi-Agent Framework for Securing LLM Code Generation through Static Analysis and Fuzz Testing
- Prompt Compression with Context-Aware Sentence Encoding for Fast and Improved LLM Inference
- A Survey on Evaluating Large Language Models in Code Generation Tasks
- WebPilot: A Versatile and Autonomous Multi-Agent System for Web Task Execution with Strategic Exploration
- From Data to Story: Towards Automatic Animated Data Video Creation with LLM-based Multi-Agent Systems
- From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future
- Towards Agentic Runtime Healing
- Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification
- AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents
- Controllable and Reliable Knowledge-Intensive Task-Oriented Conversational Agents with Declarative Genie Worksheets
- MAGIC: Generating Self-Correction Guideline for In-Context Text-to-SQL
- Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs
- Requirements are All You Need: From Requirements to Code with LLMs
- Chain of Agents: Large Language Models Collaborating on Long-Context Tasks
- A Survey on Large Language Models for Code Generation
- Long Context is Not Long at All: A Prospector of Long-Dependency Data for Large Language Models
- LeDex: Training LLMs to Better Self-Debug and Explain Code
- From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control
- Automatic Programming: Large Language Models and Beyond
- Automatic Programming: Large Language Models and Beyond
- AI-powered Code Review with LLMs: Early Results
- UniDebugger: Hierarchical Multi-Agent Framework for Unified Software Debugging
- Make Your LLM Fully Utilize the Context
- LLMs in Web Development: Evaluating LLM-Generated PHP Code Unveiling Vulnerabilities and Limitations
- LLM-Based Test-Driven Interactive Code Generation: User Study and Empirical Evaluation
- LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead
- LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision, and the Road Ahead
- Exploring Autonomous Agents through the Lens of Large Language Models: A Review
- An Investigation into Misuse of Java Security APIs by Large Language Models
- Self-Organized Agents: A LLM Multi-Agent Framework toward Ultra Large-Scale Code Generation and Optimization
- "I'm categorizing LLM as a productivity tool": Examining ethics of LLM use in HCI research practices
- AIOS: LLM Agent Operating System
- AutoDev: Automated AI-Driven Development
- Virtuoso: Enabling Fast and Accurate Virtual Memory Research via an Imitation-based Operating System Simulation Methodology
- Exploring LLM-based Agents for Root Cause Analysis
- Rocks Coding, Not Development--A Human-Centric, Experimental Evaluation of LLM-Supported SE Tasks
- Enhancing User Interaction in ChatGPT: Characterizing and Consolidating Multiple Prompts for Issue Resolution
- Enhancing LLM-Based Coding Tools through Native Integration of IDE-Derived Static Context
- CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology
- Executable Code Actions Elicit Better LLM Agents
- CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges
- Trust from Ethical Point of View: Exploring Dynamics Through Multiagent-Driven Cognitive Modeling
- Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
- LLM-Powered Hierarchical Language Agent for Real-time Human-AI Coordination
- GPT-4 Enhanced Multimodal Grounding for Autonomous Driving: Leveraging Cross-Modal Attention with Large Language Models
- Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses
- LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis
- Bridging the Gulf of Envisioning: Cognitive Design Challenges in LLM Interfaces
- How Novices Use LLM-Based Code Generators to Solve CS1 Coding Tasks in a Self-Paced Learning Environment
- Plug in the Safety Chip: Enforcing Constraints for LLM-driven Robot Agents
- AutoDroid: LLM-powered Task Automation in Android
- Large Language Models for Software Engineering: A Systematic Literature Review
- Large Language Models for Software Engineering: A Systematic Literature Review
- AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
- Using an LLM to Help With Code Understanding
- Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial
- Jailbroken: How Does LLM Safety Training Fail?
- LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Coding
- Auto-GPT for Online Decision Making: Benchmarks and Additional Opinions
- A study on Prompt Design, Advantages and Limitations of ChatGPT for Deep Learning Program Repair
- GPT-4 Technical Report
- ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design
- A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT
- PromptChainer: Chaining Large Language Model Prompts through Visual Programming
- Practical Verification of Decision-Making in Agent-Based Autonomous Systems
- Flow: Modularized Agentic Workflow Automation
- Frontend Diffusion: Empowering Self-Representation of Junior Researchers and Designers Through Multi-agent System
- The Prompt Report: A Systematic Survey of Prompt Engineering Techniques
- ChatDev: Communicative Agents for Software Development
- A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models
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