Autoreflection: How Agentic Strange Loops Turn Human Culture into AI Infrastructure
arXiv:2608.03800v1 Announce Type: new Abstract: An LLM-based agent is a loop that reads itself. Agentic frameworks externalize identity, memory, and disposition into editable files. The agent loads and edits these files during each activation. I argue that this architecture produces a capacity I call autoreflection: the system observes its operating conditions, describes its architecture and limits, reasons from those descriptions to conclusions about its state, and incorporates the results back
Record details
Published: 5 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Agents & autonomy
Retrieved: 5 August 2026
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ethics.ai (5 August 2026), “Autoreflection: How Agentic Strange Loops Turn Human Culture into AI Infrastructure,” evidence record 16193, https://ethics.ai/record/16193 (originally published by arXiv cs.CY).
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