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.
