mlsanityData to 7 Oct 2026

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

arXiv 2505.19443 ↗First posted 26 May 2025cs.SE cs.AI cs.CLcited by 39

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

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.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 158 of its 262 references that are in the map. First posted on arXiv 26 May 2025.

Builds on

158 of 262 references.

Closest ancestors · 23

Same direction, newest first

  1. 2025Web-Bench: A LLM Code Benchmark Based on Web Standards and Frameworks12 May
  2. 2025MARCO: Multi-Agent Code Optimization with Real-Time Knowledge Integration for High-Performance Computing6 May
  3. 2025Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency4 May
  4. 2025A Self-Improving Coding Agent21 Apr
  5. 2025Why Do Multi-Agent LLM Systems Fail?17 Mar
  6. 2025VeriMind: Agentic LLM for Automated Verilog Generation with a Novel Evaluation Metric15 Mar
  7. 2025Agentic AI Software Engineers: Programming with Trust19 Feb
  8. 2025LLM Agents Making Agent Tools17 Feb
  9. 2025Every Software as an Agent: Blueprint and Case Study7 Feb
  10. 2025Adaptive Self-improvement LLM Agentic System for ML Library Development4 Feb
  11. 2025CodeCoR: An LLM-Based Self-Reflective Multi-Agent Framework for Code Generation14 Jan
  12. 2025Guided Code Generation with LLMs: A Multi-Agent Framework for Complex Code Tasks11 Jan
11 more
  1. 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future5 Aug
  2. 2024Towards Agentic Runtime Healing2 Aug
  3. 2024AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents26 Jul
  4. 2024UniDebugger: Hierarchical Multi-Agent Framework for Unified Software Debugging26 Apr
  5. 2024LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead7 Apr
  6. 2024Self-Organized Agents: A LLM Multi-Agent Framework toward Ultra Large-Scale Code Generation and Optimization2 Apr
  7. 2024Exploring LLM-based Agents for Root Cause Analysis7 Mar
  8. 2024CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology2 Feb
  9. 2024Executable Code Actions Elicit Better LLM Agents1 Feb
  10. 2024CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges14 Jan
  11. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation16 Aug

Other references · 135

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,565
  3. 2025A-MEM: Agentic Memory for LLM Agentscited by 1,000
  4. 2024A Survey on Large Language Models for Code Generationcited by 646
  5. 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 612
  6. 2023Large Language Models for Software Engineering: A Systematic Literature Reviewcited by 389
  7. 2024Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Securitycited by 257
  8. 2023Auto-GPT for Online Decision Making: Benchmarks and Additional Opinionscited by 250
  9. 2023Using an LLM to Help With Code Understandingcited by 222
  10. 2024Magentic-One: A Generalist Multi-Agent System for Solving Complex Taskscited by 221
  11. 2024Chain of Agents: Large Language Models Collaborating on Long-Context Taskscited by 201
  12. 2025Large Language Model Agent: A Survey on Methodology, Applications and Challengescited by 194
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  3. 2025AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challengescited by 167
  4. 2024Large Language Model-Brained GUI Agents: A Surveycited by 160
  5. 2025Multi-Agent Risks from Advanced AIcited by 150
  6. 2025From LLM Reasoning to Autonomous AI Agents: A Comprehensive Reviewcited by 146
  7. 2022PromptChainer: Chaining Large Language Model Prompts through Visual Programmingcited by 134
  8. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 125
  9. 2024Make Your LLM Fully Utilize the Contextcited by 118
  10. 2025A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deploymentcited by 110
  11. 2025A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systemscited by 108
  12. 2024WebPilot: A Versatile and Autonomous Multi-Agent System for Web Task Execution with Strategic Explorationcited by 100
  13. 2024AIOS: LLM Agent Operating Systemcited by 94
  14. 2024RedCode: Risky Code Execution and Generation Benchmark for Code Agentscited by 87
  15. 2024Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplificationcited by 80
  16. 2023Bridging the Gulf of Envisioning: Cognitive Design Challenges in LLM Interfacescited by 71
  17. 2023LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysiscited by 70
  18. 2023Plug in the Safety Chip: Enforcing Constraints for LLM-driven Robot Agentscited by 67
  19. 2023ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Designcited by 66
  20. 2025Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agentscited by 66
  21. 2024A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languagescited by 65
  22. 2023LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Codingcited by 64
  23. 2024SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt Typescited by 58
  24. 2023How Novices Use LLM-Based Code Generators to Solve CS1 Coding Tasks in a Self-Paced Learning Environmentcited by 55
  25. 2025Multi-Agent Systems Execute Arbitrary Malicious Codecited by 52
  26. 2024Prompt Compression with Context-Aware Sentence Encoding for Fast and Improved LLM Inferencecited by 51
  27. 2023LLM-Powered Hierarchical Language Agent for Real-time Human-AI Coordinationcited by 48
  28. 2024A Performance Study of LLM-Generated Code on Leetcodecited by 48
  29. 2025Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMscited by 47
  30. 2024"We Need Structured Output": Towards User-centered Constraints on Large Language Model Outputcited by 46
  31. 2024LLM-Based Test-Driven Interactive Code Generation: User Study and Empirical Evaluationcited by 46
  32. 2024Thinking LLMs: General Instruction Following with Thought Generationcited by 45
  33. 2025SAGA: A Security Architecture for Governing AI Agentic Systemscited by 45
  34. 2025AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarioscited by 44
  35. 2023Prompting Large Language Models With the Socratic Methodcited by 43
  36. 2024A Survey on Evaluating Large Language Models in Code Generation Taskscited by 43
  37. 2024LeDex: Training LLMs to Better Self-Debug and Explain Codecited by 39
  38. 2025Repo2Run: Automated Building Executable Environment for Code Repository at Scalecited by 39

50 most cited of 135 All 135 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 12; 2026: 27.

39 papers.

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  1. 2025From Prompt Injections to Protocol Exploits: Threats in LLM-Powered AI Agents Workflowscited by 57
  2. 2025DeepAnalyze: Agentic Large Language Models for Autonomous Data Sciencecited by 49
  3. 2026Code as Agent Harnesscited by 40
  4. 2026FeatureBench: Benchmarking Agentic Coding for Complex Feature Developmentcited by 30
  5. 2025Agentic Refactoring: An Empirical Study of AI Coding Agentscited by 17
  6. 2025A Comprehensive Survey on Benchmarks and Solutions in Software Engineering of LLM-Empowered Agentic Systemcited by 15
  7. 2025Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications, and Research Agendacited by 13
  8. 2025From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligencecited by 13
  9. 2026AI IDEs or Autonomous Agents? Measuring the Impact of Coding Agents on Software Developmentcited by 10
  10. 2025Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impactcited by 6
  11. 2025Takedown: How It's Done in Modern Coding Agent Exploitscited by 6
  12. 2026Security in the Age of AI Teammates: An Empirical Study of Agentic Pull Requests on GitHubcited by 6
27 more
  1. 2026Position: Human-Centric AI Requires a Minimum Viable Level of Human Understandingcited by 6
  2. 2025Smarter Together: Creating Agentic Communities of Practice through Shared Experiential Learningcited by 5
  3. 2026Agentic Scientific Simulation: Execution-Grounded Model Construction and Reconstructioncited by 4
  4. 2026RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgradescited by 4
  5. 2025Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaborationcited by 3
  6. 2026Why Agentic-PRs Get Rejected: A Comparative Study of Coding Agentscited by 3
  7. 2026Why Human Guidance Matters in Collaborative Vibe Codingcited by 3
  8. 2026SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineeringcited by 3
  9. 2026Humans are Missing from AI Coding Agent Researchcited by 3
  10. 2026Thinking with Tables: Enhancing Multi-Modal Tabular Understanding via Neuro-Symbolic Reasoningcited by 2
  11. 2026SkillGate: Cost Efficient Runtime Malicious Skill File Detection in Coding Agentscited by 2
  12. 2025Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systemscited by 1
  13. 2026"When to Hand Off, When to Work Together": Understanding Concurrent Human-Agent Interaction in Shared Co-Creative Workspacescited by 1
  14. 2026Interrogating Design Homogenization in Web Vibe Codingcited by 1
  15. 2026TDD Governance for Multi-Agent Code Generation via Prompt Engineeringcited by 1
  16. 2025Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verificationcited by 0
  17. 2026Prompt Driven Development with Claude Code: Building a Complete TUI Framework for the Ring Programming Languagecited by 0
  18. 2026Vibe AIGC: A New Paradigm for Content Generation via Agentic Orchestrationcited by 0
  19. 2026Autonoma: A Hierarchical Multi-Agent Framework for End-to-End Workflow Automationcited by 0
  20. 2026Is Vibe Coding the Future? An Empirical Assessment of LLM Generated Codes for Construction Safetycited by 0
  21. 2026PYTHALAB-MERA: Validation-Grounded Memory, Retrieval, and Acceptance Control for Frozen-LLM Coding Agentscited by 0
  22. 2026Reliable Reasoning with Large Language Models via Preference-Based Maximum Satisfiabilitycited by 0
  23. 2026How Do AI Coding Agents Contribute to Software Development? an Empirical Study of Agentic Pull Requestscited by 0
  24. 2026The Vibe Shift in Software Engineering: Evaluating AI-Led Conversational Programming for Performance, Cognition, and Responsible Adoptioncited by 0
  25. 2026MTAC-IFBench: Benchmarking Instruction-Following in Multi-Turn Agentic Codingcited by 0
  26. 2026The Work Behind Delegation: A Framework for Supervising AI Coding Agentscited by 0
  27. 2026A Lean and Spec-Driven AI-Assisted Software Development Lifecycle for Applied AI Education: The AI-SDLC Approachcited by 0

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  1. 2025Vibe Coding: Toward an AI-Native Paradigm for Semantic and Intent-Driven Programming ↗
  2. 2025A Survey of Vibe Coding with Large Language Models
  3. 2025AI Agentic Programming: A Survey of Techniques, Challenges, and Opportunities
  4. 2026Mise en Place for Agentic Coding: Deliberate Preparation as Context Engineering Methodology
  5. 2026Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development
  6. 2026Scaling Human-AI Coding Collaboration Requires a Governable Consensus Layer
  7. 2025Toward Agentic Software Engineering Beyond Code: Framing Vision, Values, and Vocabulary
  8. 2026Agentic AI in the Software Development Lifecycle: Architecture, Empirical Evidence, and the Reshaping of Software Engineering