Introduction: LLM monitoring is essential for maintaining reliable, cost-effective AI applications in production. Unlike traditional software where errors are obvious, LLM failures can be subtle—degraded output quality, increased hallucinations, or slowly rising costs that go unnoticed until the monthly bill arrives. Effective monitoring tracks latency, token usage, error rates, output quality, and cost metrics in […]
Read more →Category: Emerging Technologies
Emerging technologies include a variety of technologies such as educational technology, information technology, nanotechnology, biotechnology, cognitive science, psychotechnology, robotics, and artificial intelligence.
HL7 v2: The Messaging Standard That Powers Healthcare IT
Executive Summary HL7 v2.x remains the most widely deployed healthcare messaging standard globally, powering 95% of hospital interfaces despite being developed in the 1980s. This deep dive explores why HL7 v2 continues to dominate healthcare IT, how it works at a technical level, and how modern .NET developers can implement robust v2 interfaces for Irish […]
Read more →Structured Output from LLMs: JSON Mode, Function Calling, and Pydantic Patterns (Part 1 of 2)
Introduction: Getting reliable, structured data from LLMs is one of the most practical challenges in building AI applications. Whether you’re extracting entities from text, generating API parameters, or building data pipelines, you need JSON that actually parses and validates against your schema. This guide covers the evolution of structured output techniques—from prompt engineering hacks to […]
Read more →Context Compression Techniques: Fitting More Information into Limited Token Budgets
Introduction: Context window limits are one of the most frustrating constraints when building LLM applications. You have a 100-page document but only 8K tokens of context. You want to include conversation history but it’s eating into your prompt budget. Context compression techniques solve this by reducing the token count while preserving the information that matters. […]
Read more →What is Landing Zone in Azure? How to implement it via Terraform
In Azure, a landing zone is a pre-configured environment that provides a baseline for hosting workloads. It helps organizations establish a secure, scalable, and well-managed environment for their applications and services. A landing zone typically includes a set of Azure resources such as networks, storage accounts, virtual machines, and security controls. Implementing a landing zone […]
Read more →Semantic Kernel: Microsoft’s Enterprise SDK for Building AI-Powered Applications
Introduction: Semantic Kernel is Microsoft’s open-source SDK for integrating Large Language Models into applications. Originally developed to power Microsoft 365 Copilot, it has evolved into a comprehensive framework for building AI-powered applications with enterprise-grade features. Unlike other LLM frameworks that focus primarily on Python, Semantic Kernel provides first-class support for both C# and Python, making […]
Read more →