What Agent-to-Agent Communication Is
An AI agent is an AI system that can take actions, not just generate text. It can search the web, call APIs, read files, write code, and interact with other systems. Agent-to-agent communication is what happens when one AI agent needs to pass a task, exchange context, or coordinate with another agent. This might look like one agent researching a topic and passing its findings to another agent that writes a summary. Or one agent planning a multi-step workflow and delegating sub-tasks to specialized agents. Or an AI assistant calling a tool-using agent to retrieve structured data from an external source.
How Agents Exchange Information
Agent-to-agent communication relies on structured context passing. When one agent hands off a task to another, it passes along a structured set of information: what the task is, what context the receiving agent needs, what tools it has available, and what format the output should take. This is why structured data on websites matters for agent pipelines: when an agent retrieves information from your website to use in its workflow, it needs that information to be clearly structured so it can be extracted, summarized, and passed to the next stage of the pipeline reliably.
What This Means for Websites
When AI agents are reading your website as part of a task, they are not reading it the way a human would. They are extracting specific information to pass on to the next step in their workflow. That means your website needs to make information extraction easy and reliable. Clear headings, structured data, consistent entity naming, and machine-readable endpoints all reduce the risk of extraction errors. A well-structured website is a more reliable tool for AI agent pipelines, which means it gets cited, used, and recommended more often.
The Emerging Standards for Agent Communication
The infrastructure for agent-to-agent communication is still being formalized. Current approaches include function calling and tool use protocols built into models like GPT-4 and Claude, structured message formats like the OpenAI tool-use specification, API-based agent orchestration using frameworks like LangChain or AutoGen, and emerging standards for agent identity and capability discovery. For website owners, the most relevant implication is that your public APIs and machine-readable endpoints become potential entry points for agent workflows, making their quality and documentation more important than ever.