Agents

Chat history and memory allow agents to maintain context across conversations and remember user preferences, which enables agents to provide personalized experiences. Using the Microsoft Agent Framework, we can use in-memory chat message stores, persistent databases, and specialized memory services to cater to a variety of different use cases. In this article, I’ll show you a simple example of how we can use an Azure Cosmos DB Vector store to store conversations we have with an agent, and how we can retrieve conversations so that our agents can maintain context. ...

Almost a year ago, I wrote a blog post on how you could use GitHub Models with Semantic Kernel applications for dev and test purposes. Now that the Microsoft Agent Framework is available, I thought I’d create an updated article on how you can use GitHub Models with the new framework, so that you don’t have to provision Azure Foundry and pay for using LLM usage to build agents. What is the Microsoft Agent Framework? It’s an open-source kit for building AI Agents and agentic workflows in Python and C#. The Agent Framework is an extension of both Semantic Kernel and AutoGen projects, and it provides a unified approach for building agents. Both the Semantic Kernel and AutoGen teams are working together to build the Microsoft Agent Framework. ...

I run various Container Apps as part of my personal health project. I want this project to be as low maintenance as possible, so I decided to take a look at Azure SRE Agent to see how it could help me reduce the operational toil required to operate my side project. As I’m writing this blog post (8th January 2026), Azure SRE Agent is still in Preview. There’s no mechanism to provision SRE Agents using Bicep, or any IaC for that matter, and I’m expecting to see things break or not quite work as nicely as they should, so consider everything that I’m writing here experimental, and expect that features will change as time goes by. ...