Guide to configuring and using agentic coding tools like Codex and Claude in Xcode 26.3, including setup and integration tips.
A developer explores using AI to create personalized, project-based tutorials for learning new technologies like FastMCP, Strands, and AgentCore.
Apple's Xcode 26.3 Release Candidate introduces new agentic coding tools, integrating AI agents from OpenAI and Anthropic to assist developers.
A developer explains how they created tools to feed official Aspire documentation to AI agents, solving the problem of outdated AI recommendations.
A tutorial on building an interactive Color Picker MCP App using C# and .NET, demonstrating the new UI capabilities of the Model Context Protocol.
Explores industry adoption of context engineering standards like AGENTS.md and MCP, showing how they reduce AI development costs and improve workflows.
Explains why MCP servers often fail and provides best practices for building effective MCP servers by treating them as AI agent interfaces, not REST API wrappers.
Introducing mcp-cli, a lightweight CLI tool for efficient, dynamic discovery and interaction with MCP servers, drastically reducing token usage for AI agents.
OpenAI launches its ChatGPT App Directory and SDK, transforming the AI into a platform for third-party interactive applications.
An analysis of Goose, an AI coding agent, highlighting its unique features like reusable workflow recipes and how it differs from other AI development tools.
Introduces Agent-Matrix, an open-source OS for managing autonomous AI agents as living systems, aiming to eliminate maintenance.
A curated collection of links covering software architecture, neuromorphic computing, observability trends, AI protocols, and leadership in tech.
A developer reflects on a pivotal 2025, shifting focus from React/Remix to AI and the Model Context Protocol (MCP) to build interactive, agent-like software.
Learn how to teach AI agents to understand and use custom enterprise libraries and domain-specific languages using Kiro and MCP.
A developer's journey to understanding AI agents and the Model Context Protocol (MCP), moving beyond traditional data pipeline thinking.
Argues that enterprises should use remote MCP servers instead of local stdio servers for better security, governance, and scalability with AI agents.
A guide to improving LLM-generated code quality by using contextual rules and agents to enforce production-ready patterns and architecture.
A guide on teaching the Kiro AI agent to work with custom libraries and DSLs using steering files and the Model Context Protocol (MCP).
Explains the Model Context Protocol (MCP) by drawing parallels to RESTful HTTP architecture, using a travel planner server example.
A guide to building a Model Context Protocol (MCP) server using a ready-made TypeScript template that handles boilerplate setup.
