Deploying AI Agents in Airgapped and Low-Latency Enterprise Systems
Nick Kuhn explains why enterprise AI agents must run on-premises, satisfy strict compliance rules, and eliminate network latency.
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Nick Kuhn from VMware Tanzu Platform joins Daniel Whitenack and Chris Benson to discuss the realities of deploying AI agents in enterprise environments. They explore the transition from running agents locally to production platforms using agent buildpacks, AGENTS.md specifications, Model Context Protocol (MCP) gateways, and shared memory architectures. The conversation also addresses organizational adoption hurdles, security sandboxing, and why enterprise platform engineering practices remain critical for agentic systems.
Nick Kuhn explains why enterprise AI agents must run on-premises, satisfy strict compliance rules, and eliminate network latency.
Nick Kuhn explains why file-based agent memory fails in the cloud and how 12-factor decoupled state services fix ephemeral container memory.
Nick Kuhn explains how MCP gateways solve agent security, identity pass-through, and rogue tool call loops in production systems.
Nick Kuhn explains why isolated AI squads stall in enterprise committees, and how office hours and small iterations get models into production.
Nick Kuhn shares how VMware Tanzu uses buildpacks and AGENTS.md to move AI agents from developer laptops to secure enterprise runtimes.
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