Mira Okoro

Security and compliance hang on identity, credentials, and policy—not just features.

Platform engineers must rebuild identity, access.

Governance and audit trails separate production agents from prototypes.

Native compatibility solves tool integration, but authentication and transport gaps remain.

Building an MCP client forces security choices long before deployment matters.

Enterprises are adopting open source AI agents faster than they can evaluate them responsibly.

MCP collapses thousands of custom AI-to-data integrations into one reusable protocol.

Four MCP client types exist, each solving different enterprise integration problems.

Agentic AI needs memory and planning where generative AI only needs to respond.

Why thousands of exposed MCP servers put your data at risk.

Agents executing tasks in systems employees don't fully understand create new security risks.

Governance gaps in agentic AI deployment create real breach risk before most enterprises are ready.

MCP collapses N×M integration sprawl into a stateful protocol for AI and external systems.

AI-native systems fundamentally differ from AI-enabled add-ons by architecture, not features.