Deep dive into AI agent tools and function calling. Learn MCP integration, external API patterns, error handling, and tool chaining in Microsoft Agent Framework.
Read more →Category: Artificial Intelligence(AI)
Progressive Web Apps (PWAs) for AI: Offline-First LLM Applications
Progressive Web Apps (PWAs) for AI: Offline-First LLM Applications Expert Guide to Building Offline-Capable AI Applications with Service Workers I’ve built AI applications that work offline, and I can tell you: it’s not just about caching—it’s about rethinking how AI applications work. When users lose connectivity, they shouldn’t lose their work. When they’re on slow […]
Read more →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.
Read more →Observability Practices in AI Engineering: A Complete Guide to LLM Monitoring
Master AI observability with this comprehensive guide. Compare Langfuse, Helicone, LangSmith, and other tools. Learn which metrics matter, how to build evaluation pipelines, and implement production-grade monitoring for LLM applications.
Read more →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.
Read more →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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