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.
Category: AI/ML
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 Executive Summary 2025 marked a fundamental shift in how AI applications are built and deployed. What began with Retrieval-Augmented Generation (RAG) as the dominant… Continue reading
2025 in Review: The Infrastructure Readiness Lesson
2025 taught enterprise technology leaders a critical lesson: infrastructure readiness matters more than model capability. This year-end review explores platform engineering, data governance, healthcare AI breakthroughs, and five predictions for 2026.
Getting Started with Microsoft Foundry Local: Run AI Models On-Device Without the Cloud
Microsoft Foundry Local brings the power of Azure AI Foundry directly to your local device, enabling you to run state-of-the-art AI models without cloud dependencies. Announced at Microsoft Build 2025 and continuously enhanced since, Foundry Local represents a paradigm shift in how developers can build AI-powered applications—with complete data privacy, zero API costs, and offline… Continue reading
The Evolution of Anthropic Claude: From 3.5 to 4.5 Opus – A Technical Deep Dive
Having worked with AI models for over two decades, I’ve witnessed countless technological shifts, but few have been as remarkable as Anthropic’s Claude evolution. From the initial Claude 1.0 release in March 2023 to the groundbreaking Claude 4.5 Opus in late 2025, Anthropic has consistently pushed the boundaries of what’s possible with large language models.… Continue reading
Building Interoperable Healthcare Data Systems for AI: Beyond Point Solutions
Healthcare AI fails when data remains siloed. This article explores how FHIR, SNOMED CT, and platform thinking enable interoperable healthcare data systems for AI at scale, with insights from EU, UK, and Ireland initiatives.
Mastering LangChain: The Complete Getting Started Guide to Building Production LLM Applications
Introduction: LangChain has emerged as the de facto standard framework for building applications powered by large language models. Originally released in October 2022, it has grown from a simple prompt chaining library into a comprehensive ecosystem that includes LangChain Core, LangChain Community, LangGraph, and LangSmith. With over 90,000 GitHub stars and adoption by thousands of… Continue reading
ETL for Vector Embeddings: Preparing Data for RAG
Preparing data for RAG requires specialized ETL pipelines. After building pipelines for 50+ RAG systems, I’ve learned what works. Here’s the complete guide to ETL for vector embeddings.
Data Pipelines for LLM Training: Building Production ETL Systems
Building production ETL pipelines for LLM training is complex. After building pipelines processing 100TB+ of data, I’ve learned what works. Here’s the complete guide to building production data pipelines for LLM training. Figure 1: LLM Training Data Pipeline Architecture Why Production ETL Matters for LLM Training LLM training requires massive amounts of clean, processed data:… Continue reading
Evaluating Agent Performance: Metrics and Testing Strategies
Evaluating agent performance is harder than evaluating models. After developing evaluation frameworks for 10+ agent systems, I’ve learned what metrics matter and how to test effectively. Here’s the complete guide to evaluating agent performance. Figure 1: Agent Evaluation Metrics Framework Why Agent Evaluation is Different Agent evaluation is more complex than model evaluation: Multi-step reasoning:… Continue reading