A daily roundup of links covering .NET, web development, AI, Python, DevOps, and other software engineering topics from January 8, 2026.
Explains how to use the KAITO RAG Engine on Azure Kubernetes Service to build a Retrieval-Augmented Generation (RAG) system for querying private documents with LLMs.
A technical guide on implementing vector search in Oracle Database 26ai, using a car manual as a practical example to improve semantic search.
An analysis of scaling HNSW vector indexing in Redis, covering new contributions for efficient deletions and parallel queries across distributed nodes.
A guide on implementing SQL Server 2025's new vector search capabilities in a .NET Aspire application using the eShopLite sample project.
A tutorial on integrating IBM watsonx.ai models into Langflow to build visual RAG applications and AI workflows.
A technical guide on implementing semantic search in a Power App using Azure AI Search and vector embeddings to query an API.
Explores using the RAG pattern with Azure Cosmos DB and Azure AI tools to enhance generative AI application performance and cost efficiency.
An overview of Azure AI Foundry, a unified platform for building and deploying AI solutions on Microsoft Azure, covering its features and benefits.
A .NET code sample extending Semantic Kernel's Azure OpenAI integration to show document source details from Azure AI Search.
Explains how to use Azure OpenAI with your own data via Semantic Kernel, focusing on RAG and Azure AI Search integration.
A guide on integrating Microsoft Prompt Flow into a Python Streamlit app to build an AI-powered image search using Azure AI Search and OpenAI.
Explains how to use Azure AI Search's integrated vectorization for automatic query and field vectorization, with portal and indexer examples.
A tutorial on building a custom GPT with FastAPI and Azure AI Search to answer questions about blog content using custom actions.
Interview with Weaviate CEO Bob Van Luijt on building an open-source vector database, the rise of vector search, and the business of AI-first software.
A tutorial on building a Python chat app using Azure OpenAI's 'Add your data' feature and vector search with Azure Cognitive Search.
Explores recent updates to Azure OpenAI's 'Add your data' feature, focusing on vector search setup with Azure Blob Storage and Cognitive Search.
Explains a chunk-based embedding method using LangChain and Pinecone to improve blog post search accuracy and efficiency.
A guide on using Redis as a vector database to store and query embeddings for semantic search, replacing Pinecone in a tech stack.
A technical guide on using Pinecone vector search and OpenAI's API to build a semantic search engine for personal blog posts.
