AI code generators have evolved from autocomplete tools into systems capable of writing entire features. This raises a serious question for modern software teams: should AI-generated code be trusted in production?
Where AI shines
Rapid scaffolding and boilerplate generation
Helping developers explore unfamiliar libraries or frameworks
Improving productivity for repetitive tasks
Accelerating prototyping and MVP development
Where AI falls short
Limited understanding of business-specific context
Potential security and performance issues
Lack of accountability for decisions
Can produce correct-looking but logically flawed code
The balanced approach
AI should be treated like a powerful junior assistant:
Developers remain responsible for design and decisions
Code reviews and testing are mandatory
Critical systems require human validation
Understanding > speed
Final thought
AI is not the problem.
Blind trust is.
Production systems need ownership, clarity, and engineering judgment.
AI can help write code - but developers must still own it.
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