From Generic to Robust: Adding Error Handling to AI-Generated Code

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 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 nstrate real-world, production-grade patterns. This builds immense trust, showing you understand the developer's operational reality.