Building Your First AI Agent with Microsoft Agent Framework (Python) – Part 3

Build a production-ready Research Assistant AI agent using Python. Complete tutorial covering async patterns, @ai_function decorators, multi-turn conversations, and best practices.

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Building Your First AI Agent with Microsoft Agent Framework (.NET) – Part 2

Build a production-ready Customer Support AI agent using C# and .NET 8. Complete tutorial covering project setup, tools, multi-turn conversations, middleware, and error handling.

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Evaluating Agent Performance: Metrics and Testing Strategies

Evaluating agent performance is harder than evaluating models. After developing evaluation frameworks for 10+ agent systems, I’ve learned what metrics matter and how to test effectively. Here’s the complete guide to evaluating agent performance. Figure 1: Agent Evaluation Metrics Framework Why Agent Evaluation is Different Agent evaluation is more complex than model evaluation: Multi-step reasoning: […]

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Introduction to Microsoft Agent Framework: The Open-Source Engine for Agentic AI Apps (Part 1)

Learn about Microsoft Agent Framework (MAF), the unified open-source SDK for building production-ready AI agents. This comprehensive guide covers the architecture, key features, and how MAF combines the best of Semantic Kernel and AutoGen for enterprise agentic AI development.

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Streaming Responses for LLMs: Implementing Server-Sent Events

Streaming LLM responses dramatically improves user experience. After implementing streaming for 20+ LLM applications, I’ve learned what works. Here’s the complete guide to implementing Server-Sent Events for LLM streaming. Figure 1: Streaming Architecture Why Streaming Matters Streaming LLM responses provides significant benefits: Perceived performance: Users see results immediately, not after 10+ seconds Better UX: Progressive […]

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Quantization Methods for LLMs: GPTQ, AWQ, and BitsAndBytes

Last year, I needed to run a 13B parameter model on a 16GB GPU. Full precision required 52GB. After testing GPTQ, AWQ, and BitsAndBytes, I reduced memory to 7GB with minimal accuracy loss. After quantizing 30+ models, I’ve learned which method works best for each scenario. Here’s the complete guide to LLM quantization. Figure 1: […]

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