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 →Tips and Tricks – Implement Prompt Templates for Consistent LLM Output
Use structured prompt templates to get reliable, formatted responses from LLMs.
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 →Serverless Showdown: Cloud Run vs Cloud Functions vs App Engine – Choosing the Right GCP Compute Platform
Serverless Showdown: Cloud Run vs Cloud Functions vs App Engine Choosing the Right GCP Compute Platform for Your Workload I’ve deployed applications to all three GCP serverless platforms—Cloud Run, Cloud Functions, and App Engine. Each has strengths, but choosing wrong costs time and money. I’ve seen teams spend weeks migrating from App Engine to Cloud […]
Read more →Tips and Tricks – Use Embeddings for Semantic Search
Implement semantic search using text embeddings for more relevant results than keyword matching.
Read more →The Type Revolution: How Python’s Gradual Typing Transformed My Approach to Building Production Systems
Executive Summary Five years ago, I would have dismissed Python type hints as unnecessary ceremony for a dynamically typed language. Today, I cannot imagine building production systems without them. This shift did not happen overnight—it came from debugging production incidents at 3 AM, onboarding new team members to complex codebases, and watching refactoring efforts spiral […]
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