Define the outcome before generating code
An AI coding assistant is easier to direct when the task is small and testable. Instead of asking for a complete business website in one step, specify a single flow: a visitor submits an enquiry, sees a truthful confirmation, and receives a useful error if sending fails. Describe the expected behaviour before deciding how the interface should look.
Use assistance where you can verify the result
GitHub’s developer guidance highlights tasks such as explaining unfamiliar code, creating initial implementations, and helping with tests. These can be useful starting points. Review the result against the actual project: does it use the right dependencies, respect existing components, and handle the failure cases? A confident explanation from a tool is not evidence that the feature works.
Keep integrations behind the right boundary
For a contact form, keep email-provider credentials on the server. Validate submitted fields, constrain message size, and return a success response only after the provider accepts the request. Check whether retries can send duplicates and decide how abuse will be limited. These choices matter more than a polished success animation when a real customer tries to reach you.
Test a complete journey on a real screen
Try the page on a phone, with a keyboard, and with slow or failed requests. Check long text, empty fields, navigation after opening a dialog, and the ability to recover from an error. Keep changes small enough to review and roll back. A prototype becomes ready through evidence from these checks, not through the amount of code generated.