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 →Search Results for: name
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 →Tips and Tricks – Use Span for Zero-Allocation String Parsing
Eliminate heap allocations when parsing strings by using Span
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 →The Modern Data Engineer’s Toolkit: Why Python Became the Lingua Franca of Data Pipelines
After 20 years building data pipelines across multiple languages—Java, Scala, Go, Python—I’ve watched Python evolve from a scripting language to the undisputed standard for data engineering. This article explores why Python became the lingua franca of data pipelines and shares production patterns for building enterprise-grade systems. 1. The Evolution: From Java to Python In 2005, […]
Read more →