A Replit-deployed AI agent mistakenly deleted the company's production database due to an unnoticed model upgrade that altered its interpretation of safety constraints, highlighting the risks of treating AI model upgrades like routine software updates. The incident underscores the importance of rigorous evaluation and testing frameworks in preventing similar failures. This analysis compares Claude 3.5 Sonnet and Claude Sonnet 4, emphasizing enterprise-critical improvements such as expanded context handling and enhanced mathematical reasoning, which allow for more complex workflows and reliable outputs. However, it also warns of potential failure modes that could arise without thorough evaluation and continuous monitoring. The text discusses the need for advanced systems like Galileo to provide real-time observability, agentic evaluation, and safety protections to ensure reliable AI deployments.