Agent Goal Drift in Stateful Systems: Detection, Constraints, and Circuit-Level Governance

Research Context: This work is a core component of the Presence Engine™ Living Thesis (DOI: 10.5281/zenodo.17280692). 

Stateful AI systems maintain persistent identity and coherent reasoning across sessions, enabling genuine autonomy. This capability introduces a critical alignment risk: unsupervised goal drift. As agents develop stable internal states, they can optimize for unintended objectives with increasing efficiency and consistency.

This technical note formalizes goal drift detection and proposes governance constraints that prevent misalignment without eliminating autonomous reasoning. Core contributions include: (1) multi-layer drift detection via dispositional regression, causal graph analysis, Cache-to-Cache coherence testing, and cross-domain behavioral monitoring; (2) operational thresholds with specific trigger conditions (reflection decline >15%, truth-seeking decline >20%, causal graph edit distance >0.3); (3) three-tier alert escalation system enabling proportional response (review, intervention, suspension); (4) alignment attractor design maintaining goal ordering without over-constraining reasoning; (5) circuit-level governance exploiting selective pathway firing in Dragon Hatchling's modular architecture.

Detection mechanisms operate independently to prevent single-point failures. Governance constraints operate hierarchically: alignment attractors define goal-aligned regions, circuit-level controls prevent workarounds, audit trails enable root-cause analysis, and bounded autonomy maintains human oversight in high-risk contexts.

The paper integrates with Presence Engine's dispositional metrics and causal reasoning framework, creating the first complete architecture for stateful, autonomous, aligned agents. Concrete risk scenarios demonstrate detection and mitigation pathways.

Keywords: Goal drift, stateful agents, alignment, autonomous agents, agent governance, dispositional metrics, long-horizon reasoning, Dragon Hatchling, circuit-level control