Author Archives: Jesse Liberty
RAG in Microsoft Agent Framework – Overview
Microsoft’s Agent Framework treats retrieval as a first‑class capability so agents can fetch only what they need (or always fetch), attach source metadata, and call search as a tool during reasoning. The result: more efficient, auditable, and controllable Retrieval‑Augmented Generation … Continue reading
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16 Week Johns Hopkins Program on Agentics
~2 hours a day for 16 weeks + 3 projects. Excellent program.
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CoPilot Harness and Microsoft Agent Framework
Our friends at Microsoft have paired our development tool (CoPilot) with Microsoft Agent Framework. This powerful combination allows developers to create intelligent agents that can automate tasks, enhance productivity, and streamline workflows. This blog post will explore how to effectively … Continue reading
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Deploying to Foundry
When it comes to deploying Microsoft Agent Framework applications, Microsoft Foundry offers a robust platform that simplifies the process. This guide will walk you through one approach to deploying your application.
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Reducing Token Usage
If you want to hold costs down, efficient resource management is paramount. One of the critical resources in AI applications is token usage. Tokens are the basic units of text that models process, and managing them effectively can lead to … Continue reading
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About Neo4j
In the previous blog post I mentioned Neo4j. In this post I will provide an overview of this important framework. A Graph Database In the era of big data, the way we store and manage information has evolved significantly. Traditional … Continue reading
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An Overview of Agent Memory for .NET
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
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Microsoft Agent Framework and Foundry
In the .NET development world the two most significant frameworks for AI are Microsoft Agent Framework and Microsoft Foundry. Together, they create a powerful ecosystem for building, deploying, and managing AI agents that can automate tasks, respond to user queries, … Continue reading
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Managing Secrets in Microsoft Agent Framework
In the realm of software development, managing configuration values and sensitive information is a critical aspect that can significantly impact the security and functionality of applications. Developers often find themselves at a crossroads when deciding how to store configuration values, … Continue reading
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Detecting AI
I fed the first half of one of the blog posts generated by my demonstration program to Pangram. Here are the results: Bzzzz Still your turn.
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ChatClient Middleware vs. Agent Middleware
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
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Long-term memory in Microsoft Agent Framework
Long-term memory in AI agents refers to the ability to retain information across multiple interactions and sessions. This is essential for creating a more personalized user experience, as it allows agents to recall user preferences, past conversations, and contextual information. … Continue reading
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