Large language models (LLMs) like GPT-3 have shown remarkable capabilities in generating human-like text. However, deploying LLMs to production presents unique security risks if deployed without proper safeguards. This talk will provide an overview of red teaming techniques to uncover potentially harmful behaviors in LLMs before production deployment. I will cover common weak points, adversarial attacks, and best practices to make LLMs more secure and aligned with human values. The goal is to spark ideas for developers and researchers about proactively identifying problems with LLMs.