A curated list of articles and blogs about AI agents, software engineering changes, API latency, and developer experience.
Claude Code introduces agent teams (swarms), enabling parallel AI agents with specialized roles to coordinate on complex coding tasks.
A technical guide to building multi-agent AI systems using workflows in the Microsoft Agent Framework, covering patterns and implementation.
Explores the evolution of AI coding assistants, where developers shift from coding to managing autonomous agents as conductors and orchestrators.
A guide to building multi-agent AI workflows in .NET using AgentFactory and handoff patterns for clean, scalable agent orchestration.
Explores advanced Context Engineering techniques for AI agents, focusing on combating Context Rot and improving multi-agent coordination.
A developer-friendly introduction to the Microsoft Agent Framework, an open-source SDK for building and orchestrating AI agents in C# and Python.
Microsoft's new open-source Agent Framework combines AutoGen and Semantic Kernel for building intelligent, multi-agent AI applications.
A tutorial on building multi-agent systems using the universal-a2a-agent framework, covering HTTP endpoints, provider-agnostic design, and LangGraph integration.
Explores designing a multi-agent AI system by creating autonomous agents that play the word game Taboo, focusing on agent communication and orchestration.
A technical guide on deploying a multi-agent AI system using MCP and A2A protocols to Azure Container Apps, with components for conversation, tools, and specialized agents.
A technical guide on deploying a multi-agent AI solution using Azure AI Foundry and Azure Container Apps, focusing on private networking and infrastructure setup.
A technical deep dive into Google's A2A framework for building and connecting multi-agent AI systems via a standardized JSON-RPC API.
Explores when and how to build multi-agent AI solutions, comparing frameworks, PaaS options, and custom implementations for developers.
Explores the trade-offs between single-agent and multi-agent AI systems, discussing their characteristics, pros, and cons for different tasks.
An introduction to using LangGraph for building complex, multi-LLM workflow architectures and automations, with a focus on local execution.
Compares Model Context Protocol (MCP) and Agent2Agent (A2A), two AI communication frameworks for multi-model collaboration and agent interaction.
A guide to getting started with the AutoGen framework for building and orchestrating multi-agent AI applications.
A guide to building multi-agent AI systems using Semantic Kernel and Azure AI Agent Service, focusing on orchestration frameworks.
A tutorial on building multi-agent AI systems using Python and Azure OpenAI, covering concepts, frameworks, and practical implementation.
