😱🤖💰With generative AI, bugs multiply faster than code.

Without proper supervision, your code's creativity might outpace its reliability. While generative AI can provide you with code in seconds, unchecked bugs could cost you hours—or even days:

🛠️ Lack of Context: AI can't grasp the specific constraints or dependencies of a project.

⚠️ Inconsistent Error Handling: AI may overlook detailed error management.

📚 Limited Domain Knowledge: AI models lack deep, domain-specific expertise.

🔒 Potential Security Vulnerabilities: AI can generate insecure code, such as skipping input validation.

🚀 Rapid Prototyping, Increased Debugging Needs: While AI speeds up prototyping, the resulting code often requires extensive debugging.

📅 Dependent on Training Data: AI is limited to what it has been trained on, leading to outdated or incorrect practices.

🔄 Useful Code Suggestions: AI works well for small, repetitive tasks like generating boilerplate code.

🚦 Inconsistent Performance Optimizations: AI might neglect performance considerations.

🐛 Increased Bugs with Complexity: As code complexity grows, AI-generated solutions often introduce more bugs.

📖 Variable Code Readability: AI can produce functional code that's hard to maintain or understand.

🧠 Dependent on Human Validation: AI can't replace human judgment in critical areas like code review.

🛠️ Need for Customization: AI often generates basic structures that require significant adjustments.

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