AI safety is becoming a software architecture problem. For years, developers learned that good systems are easier to test, change, and secure when the architecture is clean. Clear boundaries matter. Dependencies matter. Trust boundaries matter. Logs matter. Failure behavior matters.
AI applications do not remove those principles. They make them more important.
A basic app takes input, applies logic, and returns output. An AI app can accept open-ended instructions, retrieve private data, call tools, write files, trigger workflows, use APIs, and interact with other systems. When AI agents enter the picture, the application is no longer just responding. It may be planning and acting. That changes the security model.
Are AI Apps Safe?
The honest answer is: they can be safe enough for production, but only when they are designed like production systems.
