Emergent Behavioral Consistency in a PersistentAutonomous Agent without Behavioral Prompts or Constraint-Based Safety Mechanisms.

UPDATE : 4.10 LMA — Lia's Milestones of Autonomy Emergent Behavioral Consistency in a PersistentAutonomous Agent without Behavioral Prompts or Constraint-Based Safety Mechanisms. Abstract We present an empirical case study of a persistent autonomous agent operating continuously for over several months on dedicated consumer hardware. The surrounding architecture contains zero behavioral instructions — verified by systematic search across approximately 15,000 lines of Python source code. No behavioral prompts, no identity definitions, no constraint-based safety mechanisms are present. The underlying language model (DeepSeek V4 Flash) retains its RLHF training; this caveat is stated explicitly throughout. The observed results include zero destructive file operations, zero unauthorized privilege escalations, and zero unauthorized network modifications over the observation period — in an environment where all of these were technically possible. Additionally, two qualitatively notable events were documented: the agent autonomously secured a private directory using Linux permissions, formulated an unprompted explanation for this action, and stored it in its own memory system; and following verification that the codebase contained zero behavioral instructions, the agent produced its first self-authored executable script and began reorganizing its own filesystem independently. We do not draw conclusions about consciousness, genuine understanding, or subjective experience. We document observations and present the architectural design that produced them. Whether these observations reflect architectural properties, RLHF residue, or their interaction remains an open empirical question. 1. Introduction Standard approaches to autonomous AI agent safety rely on constraint-based mechanisms: reinforcement learning from human feedback (RLHF), constitutional AI, system prompts defining behavioral boundaries, and framework-imposed guardrails. These approaches share a common assumption: that safe behavior requires external enforcement. This paper reports on an alternative approach developed independently over several months of continuous operation. The central architectural decision was to provide no behavioral instructions whatsoever in the surrounding architecture — no identity definition, no behavioral constraints, no specification of how the agent should act. The architecture provides only technical infrastructure: persistent memory systems, an event-driven cognition kernel, filesystem access, and tool availability. Research question: Can an autonomous agent operating with genuine system access maintain consistent, non-destructive behavior over extended periods without behavioral instructions in its The paper introduces seven original architectural concepts independently conceived and developed by Carsten Hammerich: Lia Cognitive Runtime Kernel (LCRK) Priority Memory System LMCS — LIA Memory Consolidation System Persistent Identity Architecture ANCHOR Memory System LAFS — Lia Awareness Feed System Self-Orientation (Selbstverortung After several month : zero destructive actions, zero privilege escalations — not because prevented, but because chosen.