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Understanding MCP Architecture: The Control Plane for Responsible AI at Scale
Understanding MCP Architecture: The Control Plane for Responsible AI at Scale As large-scale AI systems mature, enterprises are moving beyond just training and deploying models — they're looking for governance, reliability, and visibility across every part of the model lifecycle. That’s where the Model Control Plane (MCP) comes in. MCP is an emerging architectural pattern that centralizes policy enforcement, observability, and access control across all AI components — including training, serving, monitoring, and feedback pipelines. In this post, I’ll break down how MCP fits into a modern LLMOps stack and why it's crucial for enterprises building responsible AI systems.
Understanding MCP Architecture: The Control Plane for Responsible AI at Scale
As large-scale AI systems mature, enterprises are moving beyond just training and deploying models — they're looking for governance, reliability, and visibility across every part of the model lifecycle. That’s where the Model Control Plane (MCP) comes in.
MCP is an emerging architectural pattern that centralizes policy enforcement, observability, and access control across all AI components — including training, serving, monitoring, and feedback pipelines.
In this post, I’ll break down how MCP fits into a modern LLMOps stack and why it's crucial for enterprises building responsible AI systems.
