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Is the code AI generates actually good?

Quick Answer

It's usually decent-following modern patterns and best practices for straightforward features. But it lacks the judgement of experienced developers for complex decisions and edge cases.

Full Explanation

Code quality from AI tools varies based on what you're asking for:

What AI does well:

  • Standard UI components (forms, buttons, layouts)
  • CRUD operations (create, read, update, delete)
  • Basic authentication flows
  • API integrations with good documentation
  • Following framework conventions

The code for these features is often cleaner than what a rushed junior developer would write-consistent naming, proper structure, reasonable patterns.

Where AI struggles:

  • Complex business logic with many edge cases
  • Performance optimisation
  • Security-critical implementations
  • Architectural decisions for large applications
  • Handling unusual requirements

Realistic assessment: AI code is like hiring a very fast, very consistent junior developer who has read every tutorial but built nothing in production. They follow best practices from documentation but lack the intuition that comes from debugging failures at 2 AM.

Implications:

  • For MVPs and simple applications: AI code is usually fine
  • For production applications with real users: Budget for professional review
  • For security-sensitive features: Always get expert review

The code isn't magical, but it's also not garbage. It's a solid starting point that improves with good prompts and iteration.

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