Federal synthesis, state-standardized interfaces, and municipal development — how the stack fits together.
Synthesis, surface best-performing models, open registry
Standardized output schema, compliance, inter-regional sharing
Model development, inference infrastructure, community input
Municipalities negotiate compute allocations as part of data center permitting. The city owns the model weights, controls the training data, and runs inference on infrastructure secured through permit agreements. Government employees focus on model development, maintenance, and research.
States define output schemas — not model implementations. Any compliant model that produces the required output format satisfies the requirement. This preserves local autonomy while enabling data aggregation upward. The interface is standardized; the implementation is not.
Over time, model performance data surfaces across regions. The most accurate, equitable, and effective models are identified through real-world outcomes — not lab benchmarks — and contributed to a shared open-source registry. Every jurisdiction benefits from every other jurisdiction's improvements.
Identify 3–5 mid-sized cities or counties with active data center permitting activity. Run pilots. Document what permitting leverage looks like in practice while the window remains open. Early CBA practice has expanded in 2026, but public compute allocations remain largely missing. Establish a baseline output schema for one civic function (e.g. zoning review or benefits eligibility).
State-level adoption of standardized output schemas. At least one "compute cooperative" stood up for small jurisdictions without dedicated IT staff. Early local-first and sovereign-public compute pilots — from neighborhood AI nodes to national AI research resources — should be studied, not overstated, as practical references. First cross-jurisdictional model comparisons published.
Federal open registry launched with contribution incentives. Performance data from real deployments drives model selection. Versioned model diffs published publicly for at least one jurisdiction.
Evolutionary selection in practice. Registry curated by multi-stakeholder board. Annual public performance reports by jurisdiction.