Moltbook Observatory (2026): Playground to Super Highway in the Autonomy Era – Measuring Representation Lag in Tool-Using Agentic Ecosystems

Recent measurements of deployed tool-using agents show that autonomy is increasing in practice and is co-constructed by model capability, user oversight patterns, and product interface design [1]. This paper frames governance in that setting as a map-to-territory mismatch: governance representations update slowly while agent behavior shifts at machine cadence. Representation lag RL(t) is defined as a bounded divergence between a trace-derived territory descriptor distribution p_T(t) and a governance map representation p_M over time bins [3]. Instantiated on a public multi-agent trace archive (Moltbook Observatory Archive), RL(t) persists and varies in regime-like ways even when aggregate activity appears stable. Interaction-regime diagnosis links observable trace signatures to recurring governance stresses, including delegation opacity, strong coupling and cascades, and thin audit planes for long-horizon actions. To align lag measurement with autonomy measurement, the research program adds autonomy stratification (low vs. high autonomy subsets) and a descriptive quadrant framing that clarifies how autonomy and lag jointly inform governability. A falsification target is explicit: if lag and regime prevalence do not change with autonomy in controlled settings, the lag hypothesis is weaker.