Learn about Microsoft Agent Framework (MAF), the unified open-source SDK for building production-ready AI agents. This comprehensive guide covers the architecture, key features, and how MAF combines the best of Semantic Kernel and AutoGen for enterprise agentic AI development.
Read more βDIY LLMOps: Building Your Own AI Platform with Kubernetes and Open Source
Build a production-grade LLMOps platform using open source tools. Complete guide with Kubernetes deployments, GitHub Actions CI/CD, vLLM model serving, and Langfuse observability.
Read more βThe Serverless Revolution: Why AWS Lambda Changed Everything I Thought I Knew About Building Scalable Systems
π AUTHORITY NOTE Drawing from 20+ years of enterprise architecture experience and having migrated dozens of production systems to serverless, representing millions of Lambda invocations monthly. This is battle-tested, production-proven knowledge. Executive Summary There’s a moment in every architect’s career when a technology fundamentally rewrites your mental model of how systems should work. For me, […]
Read more βBuilding Chat Interfaces for AI: Design Patterns and Best Practices
Building Chat Interfaces for AI: Design Patterns and Best Practices Expert Guide to Creating Intuitive, Accessible, and Performant AI Chat Interfaces I’ve designed and built chat interfaces for over 20 AI applications, and I can tell you: the difference between a good chat interface and a great one isn’t the AIβit’s the UX. A well-designed […]
Read more βThe Great Frontend Shift: How React Server Components Are Rewriting the Rules of Web Development
Something fundamental shifted in frontend development in 2024, and most developers are still catching up. React Server Components (RSC) represent the most significant architectural change to React since hooks, fundamentally rethinking where code executes and how data flows through modern web applications. After building production systems with RSC for the past year, I’ve come to […]
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Deploy GenAI at enterprise scale. Learn model routing, observability, security patterns, cost management, and what the future holds for AI in production.
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