Why Agentic AI Fails and How MCP Fixes It for Developers

Agentic AI systems can be challenging for developers to manage, especially when it comes to debugging and updating code. Without a centralized logging system or clear architecture, small changes often require digging through multiple agents and dependencies.

In this clip, Ramkumar Manoharan, co-founder of an AI startup building intelligent agent-based systems, explains how Modular Component Protocol (MCP) offers a more structured alternative. By following a sequential flow and modular architecture, MCP allows developers to identify issues, update APIs, and prototype ideas more easily, without impacting the entire system.