Is Google's A2A Protocol the cure for disjointed AI agents?
As developers building with generative AI, we have access to an incredible array of powerful frameworks. Tools like LangChain, CrewAI, and Google’s own Agent Development Kits (ADK) allow us to create highly specialized AI agents capable of tackling complex tasks. But this specialization has introduced a new challenge: the “framework jungle.”
When building sophisticated systems, the real hurdle isn’t creating a single agent, but getting multiple agents — each built with different tools — to communicate and collaborate. Imagine a data analysis agent built in LangGraph needs to hand off its findings to a report-writing agent in CrewAI, which in turn needs to save its output using a third agent. Today, this requires writing custom, often brittle, “glue code” for each interaction, a significant engineering effort that is difficult to scale and maintain.
This is the challenge that Google and a consortium of over 50 industry partners, including Salesforce, LangChain, and Atlassian, are attempting to solve. On April 9, 2025, they introduced the new, open Agent2Agent (A2A) protocol, a standard designed to provide a universal language for AI agents, allowing them to work together seamlessly, regardless of how they were built.
In this newsletter, we’ll break down what this means for us as we explore:
What the Agent2Agent (A2A) protocol is and the core problem it solves.
A look at its key technical concepts.
A hands-on walk-through to see different agents collaborate in real time.
Why this new standard could be a game changer for building the next generation of AI applications.
What is the A2A protocol?
The Agent2Agent (A2A) Protocol is an open standard to establish a common communication layer. It enables AI agents built by different teams, with different tools, and from different organizations to effectively discover, communicate, and collaborate on complex tasks. It doesn’t replace frameworks like LangChain or CrewAI; rather, it provides the “how” of communication, allowing us to focus on the “what,” which is the unique value our agents provide.
