Google AI announced recently Agent2 Agent (A2A)An open protocol designed to facilitate secure, interoperable communication among AI agents built on different platforms and frames. By offering a standardized approach to agent interaction, A2A aims to streamline complex workflows involving specialized AI agents who work together to perform tasks with varying complexity and duration.
A2A addresses an important challenge in the AI ​​domain: the lack of a common mechanism for agents to discover, communicate and coordinate across supplier ecosystems. In many industries, organizations often implement several AI systems for specific functions, but these systems do not always integrate evenly. A2A is intended to close this gap by providing a universal set of rules for agent inter operability, so that agents created by different teams or businesses can work in tandem without custom integrations.
A prominent feature of A2A is its Business quality focus. The protocol supports Long -term tasks It extends over days, weeks or even months-as a supply chain planning or hiring multiple phases. It can also accommodate Multimodal cooperationSo AI agents can share and process text, audio and video in a total workflow. By using Agent card In JSON format, agents can announce their capabilities, security permits and any relevant information required to handle tasks. This approach allows each agent to quickly assess whether it can perform a given task, request additional resources or delegate responsibility to other skilled agents.
Security is another central aspect of A2A. AI systems often deal with sensitive data, such as personal information in employment or customer items in financing. To meet these requirements is A2A in line with Openapi-level approval Standards, enforcement of role -based access control and encrypted data exchange. This approach aims to ensure that only authorized agents who have the correct credentials and permits may participate in critical workflows or access -protected data streams.
To guide its development, A2A is built around Five core design principles:
- Agentic first: Agents do not share memory or tools by default. They operate independently and communicate explicitly to exchange information.
- Standards-compatible: The protocol uses widely adopted web technologies, such as HTTP, JSON-RPC and server-sent events (SSE), to minimize friction for developers.
- Safe by default: Built -in approval and authorization measures are intended to protect sensitive transactions and data.
- Handles short and long tasks: A2A supports both short interactions (such as a quick information request) and expanded processes that require ongoing cooperation.
- Modality-artic: Agents can handle text, video, audio or other data types by sharing structured task updates in real time.
From one Technical point of viewA2A can be seen as complementary to other new standards for AI multi-agent systems. For example Anthropic’s Model Context Protocol (MCP) Focuses on how different language models handle shared context during Multi-Agent Reasoning. A2A’s weight lies in the interoperability layer, which ensures that agents can safely detect each other and cooperation when models are ready to exchange data or coordinate tasks. This combination of context sharing (MCP) and Inter-agent communication (A2A) can form a more comprehensive foundation for multi-agent applications.
An example of a real-world application for A2A is hiring process. An agent screener possibly candidates based on specific criteria another could plan interviews, while a third possibly administering background check. These specialized agents can communicate through a unified interface, synchronize the status of each step and ensure that relevant information is transferred securely.
Google has Open Sourced A2A to encourage community involvement and standardization across the AI ​​industry. Key consultant and technology companies – including BCG, Deloitte, Cognizant and Wipro – contribute to its development with the goal of refining interoperability and security functions. By taking this method of collaboration, Google aims to lay the basis for a more flexible and effective multi -agent ecosystem.
In general, A2A offers a structured way for organizations to integrate specialized AI agents so that they can exchange data safely, manage tasks more efficiently and support a wide range of business requirements. As AI continues to expand to different facets of business operations, protocols such as A2A can help combine different systems, promoting more dynamic and reliable scale workflows.
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