🚀 AI can build your application faster than ever—but should you trust the generated code enough to launch it?

Over the past few months, AI coding assistants have transformed software development. Building an MVP that once took weeks can now be accomplished in days. This has been a game-changer for startups, indie hackers, and developers looking to validate ideas quickly.

But there's a catch.

Generating code is only the beginning. In my experience, AI-generated projects often contain hidden issues that aren't immediately obvious during development. Duplicate logic, inconsistent coding patterns, weak error handling, unnecessary dependencies, performance bottlenecks, and even subtle security risks can make their way into the final product. These problems may not stop your app from running, but they can create maintenance challenges and negatively impact users once your product is live.

That's why I believe every AI-assisted project deserves a dedicated cleanup phase before deployment. Taking the time to review, refactor, optimize, and test your code can significantly improve reliability and reduce the chances of post-launch issues.

I recently documented 10 essential cleanup tasks that I believe every developer should complete before shipping an AI-built application. The article is based on practical observations from working with AI-generated code and is intended to serve as a simple pre-launch checklist.

📖 Read the full guide here: Vibe Coding Cleanup Before Launch - 10 Problems you shouldn't ignore

I'd love to hear from the community: What is the first thing you check before deploying AI-generated code to production? Have you encountered any unexpected issues that became valuable learning experiences? Let's discuss.

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