Anthropic's Agent Skills specification becomes an open standard, detailing its lightweight design and current industry adoption.
A developer shares key engineering lessons learned from building AI agents in .NET, focusing on state management, orchestration, and observability.
Major tech companies launch the Agentic AI Foundation under the Linux Foundation to promote open, collaborative standards for AI agent development.
A developer-friendly introduction to the Microsoft Agent Framework, an open-source SDK for building and orchestrating AI agents in C# and Python.
Explores 'context plumbing' for AI agents, the engineering needed to move relevant context from various sources to where AI systems run.
Brendan Gregg discusses AI agents trained on his performance engineering work, their limitations, and the ethical implications of creating 'Virtual Brendans'.
Guide to using DevUI and Microsoft Agent Framework for debugging and visualizing AI agents in .NET applications.
Experiment testing if AI vision models improve SVG drawings of a pelican on a bicycle through iterative, agentic feedback loops.
The article argues that writing a simple AI agent is the new 'hello world' for AI engineering and a surprisingly educational experience.
Moonshot AI's Kimi K2 Thinking is a 1 trillion parameter open-weight model optimized for multi-step reasoning and long-running tool calls.
Explores GitHub Copilot's new custom agents feature, detailing how to create specialized AI coding assistants for specific workflows and frameworks.
Learn how to use Background Responses in .NET's Microsoft Agent Framework to maintain AI agent state and resume interrupted tasks using continuation tokens.
Learn to build AI agents in C# using Microsoft Agent Framework and Hugging Face MCP tools for image generation and analysis.
A developer's guide to building an 'AI in a Box' solution using Azure Foundry, Azure Functions, and Static Web Apps, grounded in a personal project.
A guide to the Model Context Protocol (MCP) for AI agents, explaining its core capabilities using a story-driven example.
Explores how developers must now design tools for both human users and AI agents, discussing the rise of AI experience (AIEx) alongside developer experience (DevEx).
A developer documents how AI agents built a complete shopping cart feature for an e-commerce app, from requirements to code, without manual programming.
Explores building AI Agents as streaming SQL queries using platforms like Apache Flink for improved consistency, scalability, and developer experience.
An overview of Generative AI and an introduction to building AI agents using Python and the LangGraph library.
An explanation of the Model Context Protocol (MCP), an open standard for connecting LLMs to data and tools, and why it's important for AI development.
