The first generation of AI evaluation focused on language.
Did the model produce the right answer?
Did it avoid hallucinations?
Did it resist prompt injection?
Those questions remain important.
But today's AI applications are no longer passive text generators.
They're active systems.
An AI agent can:
Execute tools
Access enterprise data
Browse the web
Read and write memory
Coordinate multi-step workflows
Make decisions that affect real systems
At that point, the response is only the visible outcome.
The real security challenge is understanding the behavior that produced it.
That's why we built Crucible around agent behavior rather than model responses.
Because production AI isn't defined by what it says.
It's defined by what it does.
Pytest for AI Agents.
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