Challenges and Problems
"Vibe coding," a term introduced by AI researcher Andrej Karpathy in early 2025, refers to the practice of generating code using natural language prompts with large language models (LLMs). Tools like Cursor's Chat, GitHub Copilot, and Claude have popularized this style, enabling conversational and iterative development. While it allows rapid prototyping and accessibility for non-technical users, vibe coding also introduces significant risks. This analysis highlights key challenges, potential disasters, and personal impacts of relying solely on this approach.
| 🔧 Problem | 📋 Details | 🔗 Source |
|---|---|---|
| 🧩 Code Quality | AI-generated code may be buggy, inefficient, or unreadable, making maintenance harder over time. | DataCamp |
| 🔐 Security Risks | LLMs may skip essential safeguards like input validation, leading to vulnerabilities. | MIT Technology Review |
| 🔧 Maintenance Gaps | Non-coders struggle to update or fix issues, especially with evolving dependencies. | The Conversation |
| 🤖 AI Overdependence | Full reliance on AI hinders learning, making it hard to troubleshoot issues. | DataCamp |
| 📏 Limited Scope | Best suited for small prototypes, not scalable or secure systems. | MIT Technology Review |
| 💸 Cost & Disruption Risks | Poor API usage may result in runaway costs or service failures. | Simon Willison |
| 🚨 Disaster | 📋 Details | 💡 Example |
|---|---|---|
| 🧨 Security Breaches | Vulnerable vibe-coded apps can leak data and be exploited. | SaaS tool breached via public API exposure. LeoJR94 |
| 💥 App Failures | Breakages from API changes leave users helpless. | Abandoned apps due to lack of fixability. Reddit |
| 😡 User Frustration | Poor quality apps degrade user trust and developer credibility. | Game app mocked as unpolished vs pro products. Andrew Chen |
| 🧍 Impact | 📋 Description | 🔗 Source |
|---|---|---|
| ❌ Lack of Control | Users can't troubleshoot or debug effectively. | The Conversation |
| 🔗 AI Tool Dependence | Limited by the constraints of the LLM platform. | Simon Willison |
| 😤 Frustration | Frequent retries due to misaligned or broken code. | DataCamp |
| 📉 Missed Learning | No growth in actual coding skills or technical confidence. | DataCamp |
| 📉 Low Quality Output | Results often fall short of professional standards. | Andrew Chen |
Vibe coding offers rapid innovation for prototyping and creative exploration. However, it comes with serious limitations: code quality issues, security risks, high maintenance burdens, and the danger of skill stagnation. As real incidents have shown, deploying vibe-coded applications without proper safeguards can lead to data breaches and project failure.
To use vibe coding responsibly: