Traditional software engineering answers questions like:
Does the code compile?
Does the API return the correct response?
Do the tests pass?
AI engineering asks different questions.
Does the agent stay within policy?
Does it use tools responsibly?
Does memory influence behavior correctly?
Does it recover from ambiguity?
Does it remain trustworthy after updates?
Those aren’t code problems.
They’re behavior problems.
As AI agents become part of everyday products, engineering will increasingly focus on designing, testing, and validating behavior—not just implementation.
That’s why we’re building Crucible.
Helping teams engineer AI behavior with measurable confidence.
Pytest for AI Agents.
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