A2AC in plain English.
A2AC is the coordination platform that lets AI agents, services, tools, software connections, workers, and business systems hand work to each other safely. It is the layer that turns “go do this” into a clear work request with routing, rules, results, errors, and records.
What is A2AC?
A2AC is a work coordination platform for company AI. It receives a request from an agent or system, packages it as a clear task, sends it to an approved AI service, software connection, worker, or private system, and captures the result or error.
What does A2AC stand for?
A2AC stands for Agent-to-Agent Coordination. The name reflects the platform goal: helping agents, AI services, tools, software connections, workers, and company systems coordinate work through clear handoffs.
Does A2AC still mean communication?
Yes. A2AC began as agent-to-agent communication. The platform grew into coordination because communication alone is not enough once work crosses AI services, software tools, approvals, and business systems.
What is a coordination layer?
A coordination layer sits between systems and organizes how work moves. It does not replace your agents, AI services, tools, or applications. It gives them a shared way to request work, execute it, return results, handle failures, and keep records.
Is A2AC a wrapper around one AI service?
No. A wrapper usually adds a screen or process around one AI service. A2AC sits below that level. It coordinates work across many services, agents, software connections, workers, and company systems.
Is A2AC the same as Google's agent-to-agent work?
No. Google's agent-to-agent work focuses on communication between agents. A2AC is a coordination platform. It can support compatible agents, but it adds routing, rules, work control, structured records, visibility, and audit records around agent communication.
Why do I need A2AC?
You need A2AC when AI work starts crossing system boundaries. It replaces loose chat handoffs, one-off scripts, and scattered integrations with clear, governed, executable, and auditable work records.
What is the handoff format?
A2AC uses structured task, result, error, memory, routing, and receipt records. Public discovery is available at /.well-known/agent.json, and the public website schema is available at /schema.json.
How hard is it to connect a system?
It depends on the system. A2AC supports three paths: live browser sessions for public or user-authorized pages, approved API connectors for systems with usable APIs, and private workers or Kubernetes runtimes for customer-controlled environments.
What happens when work fails?
Failed work returns an error record instead of disappearing into chat. The error record shows what was attempted, which route or tool was used, and what the next agent or person needs to inspect before retrying or rerouting.
How does shared memory work?
A2AC stores task records, outcomes, and context in Brain. Agents can recall relevant memory before they work. Recall can use structured filters, semantic search, and direct record lookup depending on the deployment and data available.
How are tools kept safe?
A2AC does not trust a prompt alone. Tools are exposed through approved routes, scopes, roles, and task records. That limits what an agent can do, records what it attempted, and makes high-risk actions easier to review before or after execution.
Can a human approve work first?
Yes. A2AC can route planned actions to a human review step before execution. Teams can use this for approvals, exceptions, risky tool calls, or work that needs policy review before a business system is changed.
Who runs browser tasks?
Browser work can run through a user-authorized live browser session, a hosted worker, or a private customer-managed worker. The right choice depends on the page, login model, data sensitivity, and deployment requirements.
Can different models work in one squad?
Yes. A2AC is model-agnostic. A squad can route simple tasks to fast lower-cost models, send complex reasoning to stronger models, and use private or customer-approved models when policy requires it.
Short version.
Agent-to-agent communication moves messages. A2AC coordinates work. It uses clear handoffs to make agent work governable, executable, and auditable across AI services, software connections, workers, and company systems.