In this episode, AI experts Bradley Arsenault and Justin Macon dive deep into the challenges and best practices for safely executing code generated by large language models in a production environment. They discuss key security considerations, containerization techniques, static/dynamic code analysis, and error handling - providing valuable insights for anyone looking to leverage the power of LLMs while mitigating the risks of abuse by AI hackers.---Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.Check out PromptDesk.ai for an open-source prompt management tool.Check out Brad’s AI Consultancy at bradleyarsenault.meAdd Justin Macorin and Bradley Arsenault on LinkedIn.Please fill out our listener survey here to help us create a better podcast: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_linkHosted by Ausha. See ausha.co/privacy-policy for more information.