Recent advancements in AI, particularly in large language models (LLMs), have prompted engineering leaders to integrate AI responsibly into their operations, focusing on privacy, security, and governance to avoid risks such as losing customer trust and regulatory violations. The text emphasizes the need for engineering teams to create a detailed AI playbook that outlines processes and best practices, ensuring that AI deployment is well-considered and responsible. This includes collaborating with cross-functional teams, documenting AI use cases, conducting thorough diligence on third-party AI tools, ensuring AI usage is auditable, and paying close attention to compliance with evolving regulations. It stresses the importance of regular updates to playbooks and documentation to reflect current AI toolsets and practices, and recommends that AI-generated results undergo a human review to maintain compliance and quality. Overall, the piece advocates for proactive and informed AI implementation as a means to drive innovation while safeguarding against potential liabilities.