🎓 AUTHORITY NOTE Based on 20+ years using every major IDE from Visual Studio .NET 2003 to today’s AI-powered tools. This represents hands-on experience leading teams through multiple IDE migrations and tool standardizations. Executive Summary Remember when developers would argue passionately about whether Visual Studio, VS Code, JetBrains, or Vim was the “right” choice? Those […]
Read more →Month: August 2025
DevSecOps: Integrating Security into DevOps
As organizations continue to adopt and accelerate their DevOps practices, it has become increasingly clear that security cannot be an afterthought. Enter DevSecOps – a movement that seeks to integrate security into the entire software development lifecycle. DevSecOps aims to shift security left, empowering teams to take ownership of their security while building and deploying […]
Read more →Building Enterprise AI Applications with AWS Bedrock: What Two Years of Production Experience Taught Me
When AWS announced Bedrock in 2023, I was skeptical. Another managed AI service promising to simplify generative AI adoption? After two years of production deployments across financial services, healthcare, and retail, I’ve learned what actually matters when building enterprise AI applications. AWS Bedrock Enterprise Architecture The Foundation Model Landscape Has Matured The most significant evolution […]
Read more →FHIR API Security Part 2: Implementation & Best Practices
Executive Summary Part 2 of 2: Implementation & Best Practices 🏥 HEALTHCARE INTEROPERABILITY SERIES This article is part of a comprehensive series on healthcare data standards and interoperability. HL7 v2: The Messaging Standard That Powers Healthcare IT Building GDPR-Compliant FHIR APIs: A European Healthcare … EMR Modernization: Migrating from Legacy HL7 v2 to FHIR HL7 […]
Read more →Retrieval Augmented Fine-Tuning (RAFT): Training LLMs to Excel at RAG Tasks
Introduction: Retrieval Augmented Fine-Tuning (RAFT) represents a powerful approach to improving LLM performance on domain-specific tasks by combining the benefits of fine-tuning with retrieval-augmented generation. Traditional RAG systems retrieve relevant documents at inference time and include them in the prompt, but the base model wasn’t trained to effectively use retrieved context. RAFT addresses this by […]
Read more →Retrieval Evaluation Metrics: Measuring What Matters in Search and RAG Systems
Introduction: Retrieval evaluation is the foundation of building effective RAG systems and search applications. Without proper metrics, you’re flying blind—unable to tell if your retrieval improvements actually help or hurt end-user experience. This guide covers the essential metrics for evaluating retrieval systems: precision and recall at various cutoffs, Mean Reciprocal Rank (MRR), Normalized Discounted Cumulative […]
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