Achieving DevOps Harmony: Building and Deploying .NET Applications with AWS Services

The Evolution of .NET Deployment on AWS After two decades of building enterprise applications, I’ve witnessed the transformation of deployment practices from manual FTP uploads to sophisticated CI/CD pipelines. When AWS introduced their native DevOps toolchain, it fundamentally changed how we approach .NET application delivery. The integration between CodeCommit, CodeBuild, CodePipeline, and ECR creates a […]

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LLM Guardrails and Safety: Protecting Your AI Application from Attacks

Introduction: Deploying LLMs in production without guardrails is like driving without seatbelts—it might work fine until it doesn’t. Users will try to jailbreak your system, inject malicious prompts, extract training data, and push your model into generating harmful content. Guardrails are the safety layer between raw LLM capabilities and your users. This guide covers implementing […]

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Prompt Templates and Versioning: Building Maintainable LLM Applications

Introduction: Production LLM applications need structured prompt management—not ad-hoc string concatenation scattered across code. Prompt templates provide reusable, parameterized prompts with consistent formatting. Versioning enables A/B testing, rollbacks, and tracking which prompts produced which results. This guide covers practical prompt template patterns: template engines and variable substitution, prompt registries, version control strategies, A/B testing frameworks, […]

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AWS re:Invent 2023: Amazon Bedrock and Q Transform Enterprise AI with Foundation Models and Intelligent Assistants

Introduction: AWS re:Invent 2023 delivered transformative announcements for enterprise AI adoption, with Amazon Bedrock reaching general availability and Amazon Q emerging as AWS’s answer to AI-powered enterprise assistance. These services represent AWS’s strategic vision for making generative AI accessible, secure, and enterprise-ready. After integrating Bedrock into production workloads, I’ve found its model-agnostic approach and native […]

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