Developers using AI code generation tools often struggle with low-quality output—bloated implementations, anti-patterns, and sloppy conventions. According to a discussion on Hacker News, engineers are identifying practical improvements: better prompts, stronger architectural constraints, and feedback-driven refinement loops. The result: meaningfully cleaner AI-generated frontends that are actually suitable for production work.

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