An AI agent in production can delete your database. Not because the model is malicious. Because it doesn't know what it doesn't know. It sees a modal it can't parse, guesses the wrong action, and that guess gets executed against a live system.
I've seen this pattern in enough projects to know it's not a theoretical risk. The question is not whether your agent will make a mistake. It's whether your architecture can survive that mistake.
Here's what I've learned building production LLM pipelines, browser automation agents, and RAG systems. The safety patterns that actually work.
Sandboxed Execution Is Not Optional
Every AI agent action should run in a context that cannot reach production data directly. This sounds obvious. I've seen teams skip it because "the model is just generating text, it can't do anything dangerous."
