As Agentic AI systems evolve from task execution to independent reasoning, adaptation, and collaboration, the security landscape must transform in parallel. In this episode of Agentic AI: The Future of Intelligent Systems, we explore emerging vulnerabilities unique to intelligent agents—from recursive autonomy and synthetic alignment to cross-domain reasoning and consensus feedback loops. Discover why securing Agentic AI is no longer about guarding endpoints, but about designing resilient systems that collaborate with caution, supervise with foresight, and question even the most trusted logic. It's not just about defending software—it's about coexisting with cognition.

As agentic systems scale in autonomy and collaboration, the need for a unifying orchestration layer becomes essential. In this episode, we explore the rise of the Agent Operating System (AgentOS)—a runtime foundation that governs agent behavior, memory, security, and coordination across complex workflows. Discover how AgentOS is shaping the future of AI infrastructure, enabling intelligent systems to act responsibly, efficiently, and in sync.

In this episode , we dive into two of the most important protocols redefining the Agentic AI ecosystem—Anthropic’s Model Context Protocol (MCP) and Google’s Agent2Agent (A2A). While MCP standardizes how agents access tools and data, A2A enables AI agents from different systems to collaborate seamlessly.

We explore how these protocols differ in purpose and architecture, how they complement one another, and what it means for the future of AI design. From secure, plug-and-play integrations to dynamic multi-agent ecosystems, these protocols form the foundation for open, scalable, and collaborative AI infrastructure.

As we move toward a world where agents don’t just process context but coordinate entire workflows, understanding MCP and A2A becomes critical. Tune in to learn how these open protocols might be the TCP/IP of the AI era—laying the groundwork for interoperable, intelligent systems.