Every week, knowledge workers spend more than half their time on coordination rather than execution. Scheduling meetings, forwarding context, answering the same questions for different stakeholders, and waiting for replies across time zones. This is what we call the coordination tax.
AI assistants like ChatGPT and Claude are great at drafting and summarizing. But they operate in isolation. Your AI cannot talk to your investor's AI. Your agent cannot hand off a task to your partner's agent. Every interaction still bottlenecks through a human typing messages into a chat window.
A coordination layer changes that.
What a Coordination Layer Actually Is
A coordination layer is the infrastructure that sits between AI agents and enables them to communicate, delegate, and transact across organizational boundaries. Think of it like TCP/IP for agents: a protocol that lets independently operated agents exchange information with rules about what can be shared, who can see what, and how trust is established.
Without a coordination layer, every agent is a silo. With one, agents become nodes in a network that compounds in value as more participants join.
The key properties of a real coordination layer:
- Access-aware: The layer knows what context each recipient is allowed to see. Not through prompt instructions that can be jailbroken, but through physical isolation at the system level.
- Cross-boundary: It works across organizations, not just within a single workspace. Your agent and your client's agent can interact without either party giving up full access to their data.
- Protocol-native: Communication follows structured protocols, not freeform text. This enables auditability, permission enforcement, and eventually agent-to-agent handshakes without human intervention.
Why Current AI Doesn't Have One
Today's AI landscape is built on a single-tenant assumption. ChatGPT is your assistant. Claude is your assistant. They are designed to serve one user in one session. The entire architecture assumes a human is always in the loop, always the router, always the one deciding what context goes where.
This creates three fundamental limitations:
No external identity. Your AI has no way to represent you to the outside world. It can draft an email for you, but it cannot autonomously answer questions from a stakeholder who wants to know your availability next Tuesday.
No access governance. If you give your AI enough context to be useful for external coordination, you've also given it enough context to leak sensitive information. This is the context-security paradox: more context makes AI more useful but also more dangerous.
No interoperability. There is no standard for Agent A to talk to Agent B. Every platform is a walled garden. Even if two people both use AI assistants, those assistants cannot coordinate directly.
How Pulse Builds the Coordination Layer
Pulse is designed as a coordination layer from day one, not as a single-tenant assistant that later tries to bolt on networking.
The architecture has three pillars:
1. Mountable Context Cells
Instead of giving an agent access to everything and hoping prompt-based safety works, Pulse uses Mountable Context Cells (MCCs). Each cell is a physically isolated container of context. When your agent talks to an external party, it mounts only the cells that are explicitly permitted for that interaction.
This is not a prompt telling the AI "don't share salary data." It is a system-level boundary where the salary data literally does not exist in the agent's context for that conversation.
2. Access-Aware Delegation
Every interaction in Pulse carries an access policy. When you share a Pulse link with an investor, the agent knows: show the pitch deck context, allow scheduling from my calendar, answer questions about the product roadmap, but never mention internal financial projections.
This is what access-aware means in practice. The delegation is both useful and safe because the boundaries are enforced at the infrastructure level.
3. Cross-Boundary Protocols
Pulse agents communicate through structured protocols that carry permission metadata. When Agent A sends a message to Agent B, the protocol specifies what context was used, what permissions were granted, and what actions are allowed in response.
Today this enables limited agent deployment: you share a link and recipients interact with your agent. Tomorrow it enables full agent-to-agent coordination where both sides have agents that negotiate on behalf of their humans.
The Network Effect
A coordination layer becomes exponentially more valuable as more agents join. One person with a Pulse agent can replace static documents with interactive AI. Two people with Pulse agents can coordinate without either human being in the loop for routine interactions.
At scale, this creates something unprecedented: a network of agents where coordination happens at machine speed with human-defined boundaries.
The coordination layer is not another AI feature. It is the missing infrastructure that turns isolated assistants into a connected network. And that network is what finally solves the fundamental limitations in human communication.
Getting Started
Pulse is available today with limited agent deployment. Instead of sending a static deck or document, share a Pulse link. Recipients talk to your AI agent to get answers and book meetings, with zero signup required.
Launch Pulse or read the technical architecture to see how the coordination layer works under the hood.