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COWORK Protocol

An Open Standard for Human-Agent Collaborative Software

MCP solved how agents connect to tools. COWORK solves how agents and humans coordinate through those tools.


The Problem

Every B2B SaaS product is adding AI agents. None of them agree on how those agents should collaborate with humans.

The result: every company reinvents trust models, handoff protocols, permission systems, and feedback loops from scratch. Each implementation is incompatible. The experience is inconsistent. The industry is solving the same problems independently and poorly.

The Bet

Within 3 years, every B2B SaaS product will need human-agent collaboration. An open protocol that defines the shared primitives — the way OAuth defined authorization or HTTP defined web communication — will become foundational infrastructure.

The Framework: Three Interaction Zones

Traditional software design assumed one interaction model: HCI (Human-Computer Interaction).

Two new zones are emerging:

Zone What it covers Example
HCI Human-Computer Interaction How a human uses a CRM dashboard
ACI Agent-Computer Interaction How an AI agent navigates APIs, schemas, and tool interfaces
HAI Human-Agent Interaction How a human and an AI agent collaborate — trust, handoffs, feedback

COWORK defines the primitives, patterns, and specifications for all three zones.

Primitives (Draft v0.1)

We've identified 18 primitives across 6 categories. Each is a draft meant to be challenged and refined.

Category Primitives Core Question
Trust Trust Score, Trust Threshold, Trust Evidence How does an agent earn and lose autonomy?
Authority Action Scope, Delegation Contract, Escalation Trigger What can an agent do, and under what conditions?
Handoff Context Packet, Handoff Mode, Continuity State How do humans and agents transfer work seamlessly?
Feedback Override Signal, Approval Signal, Collaboration Quality Score How does the system learn from human corrections?
Communication Confidence Signal, Reasoning Trace, Intent Declaration How does an agent express uncertainty and intent?
Observability Action Attribution, Collaboration Timeline, Intervention Map How do you see what happened and who did what?

📄 Full primitives specification →

How This Fits the Ecosystem

COWORK is complementary, not competitive:

┌─────────────────────────────────────────────┐
│           Human-Agent Collaboration          │
│                  COWORK                       │  ← Trust, handoffs, feedback,
│                                               │     authority, communication
├─────────────────────────────────────────────┤
│           Agent-Agent Communication          │
│                   A2A                         │  ← Agent discovery, negotiation,
│                                               │     message passing
├─────────────────────────────────────────────┤
│            Agent-Tool Connectivity           │
│                   MCP                         │  ← Tool schemas, data access,
│                                               │     action execution
├─────────────────────────────────────────────┤
│           Human Authorization                │
│                OAuth / RBAC                   │  ← User roles, permissions,
│                                               │     access control
└─────────────────────────────────────────────┘

MCP handles plumbing. A2A handles agent-to-agent. OAuth handles human auth. COWORK handles the collaboration layer where humans and agents actually work together.

Real-World Evidence

These aren't theoretical problems. They're happening in production right now:

Current Phase: Primitives Discovery

We're in Phase 1 — validating the primitive taxonomy through structured workshops.

Phase Goal Timeline Status
1. Primitives Discovery Validate primitive taxonomy 8-10 weeks 🟢 Active
2. Pattern Definition Reusable interaction patterns per zone 10-12 weeks ⬜ Next
3. Specification Draft Formal versioned spec 8 weeks ⬜ Planned
4. Reference Implementation Working examples 12 weeks ⬜ Planned
5. Adoption & Ecosystem Real-world pilots Ongoing ⬜ Future

Contributing

Quick Start

  1. Read the primitives spec
  2. Challenge — open an issue for what's missing, wrong, or redundant
  3. Share — add your real-world examples to the examples folder
  4. Join — attend a workshop (sign up here)

Who We Need

Role What you'd do
Designers Validate that primitives can be rendered into natural experiences
Product Managers Validate that real product teams would adopt this
Engineers Validate that primitives are implementable without unreasonable overhead
AI/ML Practitioners Validate compatibility with how agents actually work
Domain Experts Validate that primitives are universal, not biased to one vertical

How to Contribute

See CONTRIBUTING.md for guidelines.

Background Reading

License

  • Specification: Apache 2.0
  • Reference implementations: MIT

This protocol is a living draft. Everything in it is meant to be challenged. If you're reading this, you're invited to shape it.

Created by Kamesh · Twitter · Substack

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