🤖 AI/ML Intermediate
⏱️ 8 min
Model Policy Governance and Token Usage at Platform Scale
Implementing model policy management and global token accounting so agentic features remain cost-aware and governable.
By Victor Robin • • Updated:
Introduction
As LLM usage grows, governance becomes mandatory: which models can run, where they run, and how token costs are tracked per feature path.
Commit Signal
8fdca88: added model policy management and global token usage tracking.
Governance Pattern
- Central policy controls allowed models and execution constraints.
- Runtime checks enforce policy before model execution.
- Token counters provide global visibility for cost and usage trends.
Why This Matters for Agentic Systems
Agentic pipelines can call multiple tools and models per request. Without policy and accounting, cost and risk both scale faster than feature value.
Conclusion
Model governance should ship with agentic capabilities, not after them.
Related reading:
/semantic-kernel-agents-orchestration//graphrag-routing-dotnet-langgraph-fallback/