Engineering teams already understand technical debt.

Quick decisions often make sense in the moment.

But over time, those shortcuts become expensive to maintain.

AI introduces another layer.

Every time an organization delays security validation, skips behavioral testing, ignores prompt injection, or postpones tool permission reviews, it accumulates AI Security Debt.

Unlike bugs, this debt often stays hidden until an AI system reaches production.

That’s what makes it dangerous.

As AI agents become more autonomous, reducing security debt will become just as important as reducing technical debt.

The goal isn’t to eliminate all risk.

It’s to avoid letting small compromises accumulate into major security problems.

That’s the mindset we’re building into Crucible.

Pytest for AI Agents.

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cybersecurity

softwareengineering

python

aiagents

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