From AGENTS.md to Enterprise Deployment
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 spent 14 years inside large corporate IT environments before his 5 years at VMware Tanzu, learning that assuming external internet access kills enterprise deals on day one. Read →
- Local AI agents store context in local markdown files, but ephemeral cloud containers destroy that file system state on restart. Read →
- Centralized Model Context Protocol (MCP) gateways manage and bind agents to specific subsets of tools, replacing unmanaged tool connections across 30 to 40 backend servers. Read →
- Enterprise approvals often stall for six months in internal review councils; counter this delay by shipping small, approved iterations rather than monolithic overhauls. Read →
- Running autonomous agents on a local laptop breaks the moment you close the lid; production workflows demand 24/7 runtimes with managed lifecycles. Read →