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Persistent AI agents build autobiographical state through reflection and retrieval, but stored or retrieved data is not inherently supported. The paper proposes typed provenance and assertion guardrails to mitigate risks from untrusted inputs and prompt injections in persistent states.
Persistent AI agents build autobiographical state through reflection and retrieval, but stored or retrieved data is not inherently supported. The paper proposes typed provenance and assertion guardrails to mitigate risks from untrusted inputs and prompt injections in persistent states.
AI-assisted summary based on the listed source.
Persistent AI agents construct autobiographical state through reflection, retrieval, and consolidation. Persistence changes availability, not epistemic standing: stored or retrieved material is not thereby supported. Untrusted inputs, prompt injections, and model inferences can therefore enter persistent state and...
As AI agents maintain persistent states, ensuring the integrity of stored information is critical to prevent manipulation or false user commitments. Typed provenance and assertion guardrails offer a method to enhance trustworthiness in persistent AI systems.
Security-conscious readers may want to review the source and watch for practical exposure or mitigation details.
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