The first generation of AI security focused on one objective:
Protect the language model.
That solved an important problem.
But today's AI applications have become much more capable.
Modern AI agents:
execute tools
access enterprise systems
maintain memory
browse the web
orchestrate workflows
communicate with other services
operate over long conversations
Each capability introduces a new trust boundary.
That means the attack surface is no longer limited to prompt injection or jailbreaks.
It includes behavior.
Permissions.
Memory.
Infrastructure.
Integrations.
The next generation of AI security isn't about replacing model security.
It's about expanding it.
That's the direction behind Crucible: testing deployed AI agents as complete systems so developers can understand how they behave in production, not just how they respond to a single prompt.
As AI systems evolve, security has to evolve alongside them.
Pytest for AI Agents.
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