Shuva Jyoti Kar

The Model Context Protocol (MCP) standardizes context retrieval and tool execution, but granting LLMs access to dynamic execution environments introduces critical runtime vulnerabilities. Traditional containerization (e.g., Docker/containerd) introduces unacceptable latency overhead for sub-second...

This session addresses the evolution of AI from simple retrieval to autonomous "Agency" by introducing the Streaming Agentic Loop, an architectural blueprint designed to eliminate the latency inherent in static databases. Targeted at architects and engineers, the talk explores the convergence of event-driven systems and AI through a technical deep dive into using Apache Flink (PyFlink) for stateful memory management, Kafka for feedback loops, and Google CloudRun for serverless, non-blocking LLM inference. By tackling production challenges like token cost optimization via semantic caching and handling "ghost actions" with idempotent execution, the presentation provides attendees with a proven reference architecture and actionable code patterns for building resilient, real-time agents capable of complex tasks like fraud mitigation and supply chain automation.