Episode Details

Welcome to another episode of Knowledge Nuggets with Mirko Peters. In this episode, we're exploring Agent-to-Agent (A2A) Communication, the open protocol that allows AI agents to discover one another, delegate work, and collaborate as intelligent teams. Today's AI agents are often highly specialized but isolated. One agent may excel at booking flights, another at checking weather, and another at managing IT tickets—but without a common communication standard, connecting them quickly becomes a maintenance nightmare. A2A solves this problem by providing a standardized way for AI agents to communicate regardless of which vendor or platform they were built on.

THE PROBLEM WITH ISOLATED AI AGENTS
Most AI agents today operate independently. As organizations build more specialized AI solutions, every new capability often requires custom integrations between agents. A travel assistant may need to communicate with weather, hotel, calendar, and airline services. Without a standard communication protocol, developers must create individual integrations between every pair of agents. Over time these point-to-point integrations become difficult to maintain, expensive to scale, and highly fragile. Every new agent increases complexity, creating what many developers describe as "integration spaghetti." A2A addresses this challenge by introducing a common communication protocol that allows independent AI agents to cooperate without requiring custom bridges between every service. 

WHAT IS AGENT-TO-AGENT (A2A)?
Agent-to-Agent (A2A) is an open communication protocol that enables AI agents to exchange requests, delegate tasks, and return results. A useful analogy is HTTP for websites. Just as web browsers and servers communicate using HTTP, AI agents can communicate using A2A regardless of which platform they run on. The protocol is supported by major technology companies including Microsoft, Google, Cisco, Salesforce, SAP, and others through the Linux Foundation, making it an industry standard rather than a proprietary technology. A2A is built on familiar web technologies including HTTP and JSON-RPC, allowing developers to adopt it using existing networking and API knowledge. A2A VS MCP A2A is frequently compared with the Model Context Protocol (MCP), but the two solve different problems. MCP connects AI agents to tools, APIs, databases, and external systems. A2A connects AI agents directly to other AI agents. Rather than competing technologies, they complement one another. An AI agent may use MCP to retrieve information from a CRM system and then use A2A to delegate another portion of the overall task to a specialist AI agent. This creates both vertical integration with business systems and horizontal collaboration between intelligent agents.

AGENT CARDS
Every A2A-compatible agent publishes an Agent Card. Think of it as a machine-readable business card or résumé describing what an agent can do. The Agent Card contains information such as:

• Agent name
• Description
• Skills
• Endpoint URL
• Authentication requirements
• Supported input formats
• Supported output formats

Agent Cards are published using a standard location (/.well-known/agent-card.json), allowing orchestrators to automatically discover specialist agents and understand their capabilities without manual configuration. This decentralized approach removes the need for a central registry while making it easy to introduce new agents into an existing ecosystem.

HOW A2A COMMUNICATION WORKS
Communication between agents takes place using standard HTTP requests carrying JSON-RPC messages. A2A supports three communication models depending on the workload. Instant responses are used for quick synchronous requests such as retrieving today's weather. Streaming responses allow agents to continuously report progress during longer-running operations us