Category Archives: Essentials

TL;DR Prompts allow you to manage the exact instructions your chat models receive and let apps pick those instructions at runtime. That’s the core value of “prompts” in the Model Context Protocol (MCP). MCP prompts let a server publish reusable, … Continue reading →

Adding RAG to Microsoft Agent Framework is both straightforward and confusing. OK, that makes no sense, but I’ve been struggling to understand all the steps. Here’s a first approximation, more to come in future posts (and I have a video … Continue reading →

Today I formally opened up my demo program BlogWriter as an open-source program. To do so, I added an MIT license and began taking contributions. Really that was about all there was to it, but it felt momentous.

My demo program is a multi-agent application that accepts a topic BlogAgent, researches that topic (ResearcherAgent) and then drafts a blog post (AuthorAgent). The post is then reviewed by another agent (ReviewerAgent) who either accepts the draft or sends it … Continue reading →

What is an Azure tenant (Microsoft Entra ID tenant) — and what is it used for? tl;drAn Azure tenant — now called a Microsoft Entra ID tenant — is a dedicated, isolated instance of Microsoft’s identity service that represents an … Continue reading →

tl;drImagine an AI assistant in your company that can write emails, check expense reports, and run CI pipeline steps — but it has every capability baked into one giant prompt. It’s slow, expensive, brittle, and dangerously able to access systems … Continue reading →

The ability for Microsoft Agent Framework agents to retain and utilize knowledge across interactions is critical. One solution for this is Agent Memory for .NET, a cutting-edge, mind-blowing, graph-native memory engine that leverages the robust capabilities of Neo4j as its … Continue reading →

As noted in a previous post, middleware plays a pivotal role in enhancing the functionality and observability of agents. The Microsoft Agent Framework utilizes two primary types of middleware: ChatClient Middleware and Agent Middleware. Understanding the distinctions between these two … Continue reading →

1 RAG – A quick example 2 RAG in detail 3 Deeper into RAG 4 The R in RAG 5 PEAS for Agentic AI 6 AI Reasoning and Planning 7 REACT and Agents in AI 8 Creating a multi-agent system … Continue reading →