Executive Summary Ireland’s Health Service Executive (HSE) is undertaking one of Europe’s most ambitious healthcare IT transformation programs. From rolling out the Individual Health Identifier (IHI) to deploying a national Electronic Health Record system, the HSE’s eHealth Ireland strategy is modernizing how 5 million Irish citizens access healthcare services. 🏥 HEALTHCARE INTEROPERABILITY SERIES This article […]
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LLM Monitoring and Alerting: Building Observability for Production AI Systems
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 →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 →Designing Enterprise VPC Networks on Google Cloud: From Zero Trust to Global Scale
Enterprise VPC design on Google Cloud requires balancing security, performance, and operational simplicity. This comprehensive guide covers Zero Trust architecture, global network design, VPC Service Controls, and hybrid connectivity patterns that meet the demands of modern enterprise workloads. Zero Trust Network Architecture Zero Trust assumes no implicit trust—every access request must be authenticated and authorized […]
Read more →Structured Output Generation: Reliable JSON from Language Models
Introduction: LLMs generate text, but applications need structured data—JSON objects, database records, API payloads. Getting reliable structured output from language models requires more than asking nicely in the prompt. This guide covers practical techniques for structured generation: defining schemas with Pydantic or JSON Schema, using constrained decoding to guarantee valid output, implementing retry logic with […]
Read more →Model Context Protocol (MCP): Building AI-Tool Integrations That Scale
Introduction: The Model Context Protocol (MCP) is an open standard developed by Anthropic that enables AI assistants to securely connect with external data sources and tools. Think of MCP as a universal adapter that lets AI models interact with your files, databases, APIs, and services through a standardized interface. Instead of building custom integrations for […]
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