Idea: A system to stop AI models from going “off track” during training or after deployment

I’ve been thinking about a simple idea and wanted to get your thoughts on it.

Sometimes AI models don’t behave exactly how we expect. Even if we give clear instructions, they might:

• Go slightly off-task
• Use more resources than needed
• Produce unexpected or weird outputs in edge cases

So my idea is to build something like a “behavior guard” for models.

Basically:

• You define what the model should do (rules, limits, expected behavior)
• A monitoring system watches what the model is doing
• If it starts going off track, the system steps in and corrects or stops it

Kind of like a supervisor layer for AI.

What I’m unsure about:

• How do you clearly define “correct behavior”?
• Should this be rule-based or another AI model acting as a checker?
• How do you do this without slowing everything down?

I feel like this could be useful for things like AI agents, autonomous systems, or anything where you don’t want unexpected behavior.

Would love to hear:

• If something like this already exists
• Better ways to approach this idea
• Any flaws I’m missing