Building reliable automation scripts requires robust error handling, effective logging, and modular code structure. Key techniques include graceful error handling for network requests, using Python's logging module for feedback, and ensuring idempotency in tasks. Implementing state management enhances resilience, allowing scripts to recover from failures seamlessly.