Most AI systems are evaluated on their ability to complete tasks.
Can the agent retrieve information?
Can it call an API?
Can it execute a workflow?
These questions matter.
But they don’t answer a more important question:
What happens next?
Humans naturally think about consequences.
Before taking action, we consider impact.
AI agents often optimize for completion.
They see objectives, permissions, and available tools.
They don’t naturally reason about downstream effects.
As agents become more autonomous, consequence awareness becomes increasingly important.
A task completed successfully can still produce an undesirable outcome.
That’s why agent security isn’t only about access control.
It’s about understanding impact.
This is one of the reasons we’re building Crucible.
Pytest for AI agents.
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