Product Engineers are being asked to ship fast while maintaining security in their code to avoid embarrassing situations and protect the company's reputation.
Large Language Models (LLMs) used by Product Engineers can sometimes introduce vulnerabilities due to data and model poisoning, making secure-by-default approaches crucial.
Tools like Semgrep and Replit are being utilized for secure scanning of code to identify and fix vulnerabilities before deployment, ensuring a safer coding environment for Product Engineers.
By implementing shift-left strategies and utilizing AI-driven tools for secure coding practices, Product Engineers can protect against exploitation while maintaining a rapid development pace.