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The article explores how AI can generate robust error-handling logic for software systems. It outlines prompting strategies, common patterns (validation, retries, fallbacks, timeouts), and logging/observability. It weighs speed and consistency gains against risks like hallucinated checks and silent failures, and offers review, testing, and CI/CD practices to keep humans in the loop.