Executive Summary The evolution from traditional data pipelines to AI-driven agent pipelines represents one of the most significant architectural shifts in enterprise computing since the move from monoliths to microservices. This transformation is not merely an incremental improvement—it fundamentally redefines how organizations think about data processing, orchestration, and system design. For two decades, Extract-Transform-Load (ETL) […]
Read more →Tag: AI Agents
Agentic AI in Enterprise: Why Infrastructure Readiness Matters More Than Model Capability
After 20+ years in enterprise architecture, I’ve seen that infrastructure readiness matters more than model capability for agentic AI deployment. Gartner predicts 40% of projects will be cancelled by 2027 due to infrastructure gaps, not AI failures.
Read more →From RAG to Agents: The Evolution of AI Applications in 2025
From RAG to Agents: The Evolution of AI Applications in 2025 A Comprehensive Analysis of How AI Applications Evolved from Retrieval-Augmented Generation to Autonomous Agent Systems December 2025 | Industry Whitepaper Retrieval-Augmented Generation (RAG) revolutionized how we build LLM applications by grounding responses in real data. But RAG has limitations: it’s reactive, constrained to retrieval […]
Read more →Migration Guide: From Semantic Kernel & AutoGen to Microsoft Agent Framework – Part 10
Complete migration guide from Semantic Kernel and AutoGen to Microsoft Agent Framework. Before/after code examples and step-by-step instructions.
Read more →MCP Integration & External Tool Connectivity in Microsoft Agent Framework – Part 9
Connect AI agents to external tools via Model Context Protocol. Learn MCP servers, Microsoft 365 integration, and building custom MCP servers.
Read more →Production-Ready Agents: Observability, Security & Deployment – Part 8
Deploy AI agents to production with enterprise-grade observability, security, and resilience. Complete guide to OpenTelemetry, content safety, and Azure deployment.
Read more →