RT3 (Observer Construction) develops the measurement and resolution layer of the Deficit-Fractal Governance (DFG) framework for multi-agent systems. The paper formalizes how observers emerge as structural operators that transform internal system resolution into measurable geometry, enabling stability diagnostics and governance intervention without direct control. It introduces the directional cost profile Aᵢ(θ, t), resolution-to-geometry mapping Φ, and observability constraints that define when structural instability becomes detectable. Rather than treating measurement as passive, RT3 shows that observation is a generative process that shapes the accessible state space and determines which dynamics can be governed. This provides the missing bridge between instability dynamics (RT1), critical measurement regimes (RT2), and recovery processes (RT4). The framework is conceptual and structural, intended to establish testable observability conditions and resolution-dependent diagnostics for emerging multi-agent AI ecosystems.