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.
A simulation using multi-agent models in R to replicate complex stock market behavior through technical and fundamental trading strategies.
