The era of experimental LLM wrappers and unmanaged agents is over.
For the Enterprise Architect, the primary challenge has shifted from model selection to runtime governance. Without a centralized control plane, AI agent sprawl is already generating architectural debt, security vulnerabilities, and unpredictable operational costs.
This guide provides a vendor-agnostic reference architecture designed to establish the guardrails necessary to orchestrate, govern, and monitor multi-agent systems (MAS) in real time. These patterns apply across any model, any LLM, and any business unit.
A technical breakdown of the cost of AI agent sprawl
A structured blueprint for a unified AI control plane featuring six foundational patterns for scalability and security
A practical framework for assessing infrastructure maturity before adopting a unified AI control plane
Next steps for Enterprise Architects looking to implement governance across autonomous systems
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