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.
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Advanced Multi-Agent Patterns: Workflow Orchestration and Enterprise Integration with AutoGen
📖 Part 6 of 6 | Microsoft AutoGen: Building Multi-Agent AI Systems 📚 Microsoft AutoGen Series Introduction Communication Patterns Code Generation RAG Integration Production Deployment Advanced Patterns ← Part 5🎉 Series Complete! With production deployment from Part 5, we now explore advanced enterprise patterns for complex workflows. ℹ️ INFO Advanced patterns address the complexity gap […]
Read more →DIY 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 →The Serverless Revolution: Why AWS Lambda Changed Everything I Thought I Knew About Building Scalable Systems
🎓 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 →Building 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 AI—it’s the UX. A well-designed […]
Read more →Infrastructure as Code for AI: Terraform Patterns for LLM Deployments
Infrastructure as Code for AI: Terraform Patterns for LLM Deployments Expert Guide to Managing AI Infrastructure with Terraform I’ve managed AI infrastructure across AWS, Azure, and GCP using Terraform. Infrastructure as Code isn’t just about automation—it’s about reproducibility, version control, and managing complex AI deployments consistently. When you’re deploying LLM services, vector databases, and GPU […]
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