In traditional software engineering, "done" often means the feature works as expected.
Tests pass.
The build succeeds.
The feature is deployed.
AI changes that definition.
An AI agent can appear functional while still carrying security risks that aren't obvious during normal testing.
Prompt injection.
Unsafe tool usage.
Behavioral drift.
Memory poisoning.
Policy violations.
These issues don't always prevent an agent from working—but they can prevent it from being trusted.
That's why production AI needs a higher standard.
Not just functionality.
Trust.
A trusted AI system has been evaluated beyond correctness.
Its behavior has been challenged.
Its security has been tested.
Its risks have been measured.
Its changes have been validated.
As AI becomes infrastructure, "done" will increasingly mean:
Works.
Secure.
Trusted.
We believe that's where modern AI engineering is heading.
And that's the philosophy behind Crucible.
Pytest for AI Agents.
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