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.
Read more →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 […]
Read more →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. […]
Read more →Case Study: Building a Modern FHIR Patient Timeline Explorer with .NET 10 and React 19
Executive Summary This case study explores the development of DooLittle Health Patient Timeline Explorer, a modern healthcare application that demonstrates enterprise-grade architecture patterns for FHIR-compliant patient data visualization. Built as a proof-of-concept, this project showcases best practices in full-stack development, cloud-native deployment, and healthcare interoperability standards. 🏥 HEALTHCARE INTEROPERABILITY SERIES This article is part of […]
Read more →The Complete Evolution of OpenAI’s GPT Models: From GPT-1 to GPT-5.2
A comprehensive journey through OpenAI’s GPT model evolution from 2018 to 2025. From the 117M parameter GPT-1 to today’s trillion-parameter GPT-5.2, explore the revolutionary advances in context windows, pricing, capabilities, and market adoption that have transformed AI.
Read more →Building Interoperable Healthcare Data Systems for AI: A Complete Guide to FHIR, Standards, and Governance
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.
Read more →