AI coding tools can build features surprisingly fast. But there's one thing I keep thinking about:
If AI writes the code and something breaks in production, how well do you understand the code it's written?
A feature can work perfectly during testing and still fail when it meets real users.
Maybe the API times out. Maybe the user submits a form twice. Maybe authentication expires halfway through a request. Or maybe the AI changes one file and unknowingly breaks something in another.
That's why I think AI-assisted development is about more than writing good prompts.
You still need to understand the system, question the generated solution, test edge cases, review changes, and know how to debug what goes wrong.
AI can help you move faster, but speed without understanding can become an expensive problem.
I'm curious about how other developers are working with AI coding tools today.
Three questions for the community:
- Do you trust AI-generated code once the feature works, or do you review every change?
- Has an AI coding tool ever introduced a bug that took you longer to fix than writing the code yourself?
- What do you think matters more in AI-assisted development: writing better prompts or being a better engineer?
I'd love to hear your real experiences, including the mistakes. Let's discuss.
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