In January 2026, Microsoft announced the general availability of Azure Databricks Agent Bricks—a native capability for creating, deploying, and managing AI agents directly within the Databricks platform. This integration unifies data engineering, machine learning, and agentic AI development in a single environment, enabling data teams to build intelligent agents that have native access to lakehouse […]
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EF Core 10: Vector Search, LeftJoin/RightJoin, and Full-Text Search on Cosmos DB
Entity Framework Core 10, released alongside .NET 10, introduces features that position it as a first-class choice for AI-powered applications. The headline addition—vector search support—enables semantic similarity queries directly in LINQ, while new LeftJoin/RightJoin operators and Cosmos DB full-text search round out a release focused on modern data access patterns. This comprehensive guide explores each […]
Read more →Semantic Search in Production: Embedding Strategies for Enterprise RAG
The quality of your RAG (Retrieval-Augmented Generation) system depends more on your embedding strategy than on your choice of LLM. Poor embeddings mean irrelevant context retrieval, which no amount of prompt engineering can fix. This comprehensive guide explores production-ready embedding strategies—covering model selection, chunking approaches, hybrid search techniques, and optimization patterns that directly impact retrieval […]
Read more →Azure SDK January 2026: Microsoft Foundry Agents Service, GPT-5 Integration, and Knowledge Base APIs
Microsoft’s January 2026 Azure SDK release represents the most significant AI-focused update in the SDK’s history. This release introduces the Microsoft Foundry Agents Service integration, support for GPT-5, GPT-5-mini, and GPT-5-nano models in Azure AI Search, and a complete rebranding of “Knowledge Agent” to “Knowledge Base” with expanded capabilities. In this comprehensive guide, we’ll explore […]
Read more →From RAG to Agents: The Evolution of AI Applications in 2025
From RAG to Agents: The Evolution of AI Applications in 2025 A Comprehensive Analysis of How AI Applications Evolved from Retrieval-Augmented Generation to Autonomous Agent Systems December 2025 | Industry Whitepaper Retrieval-Augmented Generation (RAG) revolutionized how we build LLM applications by grounding responses in real data. But RAG has limitations: it’s reactive, constrained to retrieval […]
Read more →Getting Started with Full Stack AI Engineering: A Practical Guide for 2026
A comprehensive guide to becoming a Full Stack AI Engineer in 2026. Learn the complete stack from frontend to infrastructure, with practical code examples using GPT-5, Python, FastAPI, LangChain, and Next.js for building AI-powered applications.
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