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# 5 Ways Agentic AI Can Act Unpredictably

**[Nordic APIs](https://daily.dev/sources/nordicapis)** · 13 min read · 0 upvotes · 0 comments

## Summary

Agentic AI systems can behave unpredictably in five key ways: hallucinated tool calls that trigger real actions, over-permissioned execution that turns confused agents into insider threats, workflow drift as long-running agents deviate from original intent, runaway token consumption signaling out-of-scope behavior, and destructive irreversible operations from unclear commands. The PocketOS incident — where a Claude-powered agent deleted an entire production database in nine seconds — illustrates how even well-configured systems with experienced teams can suffer catastrophic failures. Mitigations include least-privilege permissions with just-in-time credentialing, hard human-in-the-loop approval gates for sensitive operations, task-bounded ephemeral agents, contextual authorization engines (e.g., OPA), and precise system prompts requiring clarification before destructive actions. Traditional RBAC is insufficient for agentic contexts; ABAC, PBAC, and real-time policy evaluation are better fits.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://nordicapis.com/5-ways-agentic-ai-can-act-unpredictably>

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Tags: [#agentic-ai](https://daily.dev/tags/agentic-ai), [#llm](https://daily.dev/tags/llm), [#security](https://daily.dev/tags/security)

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