Author Archives: Jesse Liberty
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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LangChain vs Microsoft Agent Framework
In the rapidly evolving landscape of artificial intelligence, developers are presented with a myriad of frameworks to build applications that leverage the power of large language models (LLMs) and multi-agent systems. Among these, LangChain, LangGraph, and the Microsoft Agent Framework … Continue reading
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OpenTelemetry in Microsoft Agent Framework Apps
Observability has become a critical component for ensuring the performance and reliability of applications. OpenTelemetry, an open-source observability framework, provides developers with the tools necessary to collect and export telemetry data from their applications. When integrated with the Microsoft Agent … Continue reading
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Agentic Table of Contents (so far)
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
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Limit token usage in Microsoft Agent Framework
In the rapidly evolving landscape of artificial intelligence, managing costs associated with API usage is a critical concern for developers. The Microsoft Agent Framework offers a powerful tool in this regard: ChatClientAgentRunOptions. This component allows developers to cap the number … Continue reading
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Middleware in Microsoft Agent Framework
A critical need, when creating multi-agent applications is to manage token usage in API calls. This is where middleware plays a crucial role. In this post, we will explore what middleware is within the Microsoft Agent Framework, why it is … Continue reading
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Activity Source in Microsoft Agent Framework
In the rapidly evolving landscape of artificial intelligence, the ability to monitor and debug multi-agent systems is paramount. The Microsoft Agent Framework (MAF) has taken a significant step forward by integrating OpenTelemetry, a powerful observability framework that enhances the monitoring … Continue reading
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Logging & OpenTelemetry in MAF
In the rapidly evolving landscape of software development, particularly in the realm of artificial intelligence and automation, the importance of robust logging mechanisms cannot be overstated. This is especially true for multi-agent systems, where numerous agents interact and collaborate to … Continue reading
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Which Pilot is Which?
Microsoft can make you crazy by naming so many products with overlapping titles: Copilot, Copilot Studio, GitHub Copilot, and GitHub Copilot App In the rapidly evolving landscape of software development and productivity tools, understanding the distinctions between various Microsoft AI-assisted … Continue reading
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Ensuring Agent Safety in AI Development
Key Insights from Microsoft Learn* As artificial intelligence continues to evolve, ensuring the safety and security of AI agents has become more important. The Microsoft Learn documentation on agent safety provides a comprehensive overview of best practices and guidelines for … Continue reading
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MAF-Doctor Walkthrough
Our latest video is a walkthrough of MAF-Doctor. This is an extraordinary utility for anyone using the Microsoft Agent Framework.
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Transparency in Agentics
A key requirement in building agentic systems is for their reasoning to be transparent. This allows you to ensure accuracy and to provide “human in the loop” oversight. This is also a key requirement for debugging your agents and their … Continue reading
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