AI agents are improving quickly, helping developers and businesses work faster. But they also bring new risks. Chris outlines five simple lessons AWS has learned while building and using AI internally, which include treating AI output like any other untrusted input; keeping access credentials separate from prompts; and testing generated code in a sandbox before using it in production.

Chris also talks about the need for audit trails and transparency. If an AI agent makes a decision, users and security teams need to understand how it got there. That helps spot mistakes and improve systems over time.

Read the full article on Computing here.