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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Mastering Agent Communication Patterns in Microsoft AutoGen: From Two-Agent Chats to Complex Orchestration
Introduction: Effective multi-agent systems depend on well-designed communication patterns that enable agents to collaborate, share context, and coordinate actions. This comprehensive guide explores AutoGen’s communication mechanisms, from two-agent conversations and group chats to nested conversations and sequential workflows. After implementing complex agent orchestration for enterprise applications, I’ve found that communication pattern selection significantly impacts system […]
Read more →Cloud LLMOps: Mastering AWS Bedrock, Azure OpenAI, and Google Vertex AI
Deep dive into cloud LLMOps platforms. Compare AWS Bedrock, Azure OpenAI Service, and Google Vertex AI with practical implementations, RAG patterns, and enterprise considerations.
Read more →Building Multi-Agent AI Systems with Microsoft AutoGen: A Comprehensive Introduction to Agentic Development
After building multi-agent systems with Microsoft AutoGen across enterprise deployments, I’ve learned that AutoGen isn’t just another LLM framework—it’s a paradigm shift in how we build autonomous AI systems. This comprehensive introduction covers everything you need to know to start building production multi-agent applications. 1. What Is Microsoft AutoGen? AutoGen is Microsoft’s open-source framework for […]
Read more →Cloud-Native AI Architecture: Patterns for Scalable LLM Applications
Cloud-Native AI Architecture: Patterns for Scalable LLM Applications Expert Guide to Building Scalable, Resilient AI Applications in the Cloud I’ve architected AI systems that handle millions of requests per day, scale from zero to thousands of concurrent users, and maintain 99.99% uptime. Cloud-native architecture isn’t just about deploying to the cloud—it’s about designing systems that […]
Read more →MLOps vs LLMOps: A Complete Guide to Operationalizing AI at Enterprise Scale
Understand the critical differences between MLOps and LLMOps. Learn prompt management, evaluation pipelines, cost tracking, and CI/CD patterns for LLM applications in production.
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