We’ve all been there. You use an AI to generate a perfect API integration snippet for your documentation. It looks clean, but it’s brittle. The moment a network hiccups or a user provides invalid input, the example fails, leaving developers frustrated and increasing your support burden. The core principle for fixing this is proactive resilience . Your role as a technical writer is to guide the AI beyond happy-path code to demonstrate real-world, production-grade patterns. This builds immense trust, showing you understand the developer's operational reality. Mini-scenario: An AI generates a snippet to fetch user data. Without error handling, a 404 breaks the entire flow. Your enhanced guidance ensures it gracefully logs "User not found" and continues, mirroring professional development practices. Here’s how to implement this systematically in your AI workflow. Step 1: Define the Error Context Before prompting, identify what can go wrong with the specific API or function. Is it network-dependent?…