Engineering isn’t about believing systems are flawless.
It’s about understanding where they stop being reliable.
AI agents are no exception.
Every production agent has scenarios where behavior changes.
Unexpected prompts.
Complex multi-turn interactions.
Tool failures.
Adversarial inputs.
Memory conflicts.
The purpose of testing isn’t to prove an AI works.
It’s to identify where it doesn’t.
Because once you understand those limits, you can improve them.
Every breaking point you discover before deployment is one less surprise in production.
That’s why we’re building Crucible.
Helping engineering teams turn unknown limits into measurable engineering knowledge.
Pytest for AI Agents.
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