Source link : https://tech365.info/intent-based-chaos-testing-is-designed-for-when-ai-behaves-confidently-and-wrongly/
Here’s a state of affairs that ought to concern each enterprise architect transport autonomous AI programs proper now: An observability agent is working in manufacturing. Its job is to detect infrastructure anomalies and set off the suitable response. Late one evening, it flags an elevated anomaly rating throughout a manufacturing cluster, 0.87, above its outlined threshold of 0.75. The agent is inside its permission boundaries. It has entry to the rollback service. So it makes use of it.
The rollback causes a four-hour outage. The anomaly it was responding to was a scheduled batch job the agent had by no means encountered earlier than. There was no precise fault. The agent didn’t escalate. It didn’t ask. It acted, confidently, autonomously, and catastrophically.
What makes this state of affairs significantly uncomfortable is that the failure was not within the mannequin. The mannequin behaved precisely as skilled. The failure was in how the system was examined earlier than it reached manufacturing. The engineers had validated happy-path conduct, run load exams, and executed a safety assessment. What that they had not executed is ask: what does this agent do when it encounters situations it was by no means designed for?
That query is the hole I wish to discuss.
Why the business has its testing priorities backwards
The enterprise AI dialog in 2026 has largely collapsed into two areas: id governance (who’s the agent appearing as?) and observability (can we see…
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Author : tech365
Publish date : 2026-05-09 16:11:00
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