This article examines A2A from a systems-engineering perspective: its architecture, communication model, protocol objects, task lifecycle, relationship with MCP, practical implementation patterns, limitations, and security requirements.

A decision model is a machine learning model designed to select, classify, rank, or score outcomes based on an input state and a defined decision task.

Instead of relying exclusively on a more powerful model, can we make the system surrounding a model progressively better at solving different problems?

Designing Agentic AI Systems: 20 Patterns That Matter

Building the Brain of a Robot: A Deep Dive into Physical AI

How I Built Voyager — A Multi-Agent Architecture Using LangGraph

At its core, an agent harness is the execution runtime that governs how an AI agent behaves across an entire lifecycle of interaction