The past year has seen an explosion of “agent frameworks.” Demos look impressive. Loops run. Tasks complete. But as soon as you try to scale beyond a single agent in isolation, things start to break in familiar ways:

• Context gets lost
• Deadlocks appear
• Agents hallucinate into vacuums
• Coordination collapses under real-world complexity

Most agent stacks ship without a nervous system. They can act, but they cannot reliably coordinate. Unstructured intelligence is just entropy.

We built Common Ground Core (CGC) to change that.

CGC is the coordination engine behind our Slack-based workflows and internal collaborative workspace.

Today, we’re open-sourcing the engine.

Why Agents Fail in the Real World

Single-agent systems are easy to reason about. Multi-agent systems aren’t.

The moment you introduce parallelism, delegation, and asynchronous collaboration, you inherit the same problems that human organizations have spent centuries learning to manage: misalignment, partial information, conflicting intents, and brittle coordination.

Most frameworks try to solve this at the application layer with heuristics and orchestration logic. We took the opposite approach.

CGC is protocol-first.
Not a library.
Not a workflow template.
An operating system for collaboration.

Freedom at the edges. Constraints at the kernel.

A Sociotechnical OS, Not Another Loop

Common Ground Core is built as a protocol-first OS kernel for multi-agent systems. Instead of hardcoding workflows, it defines the physical laws of collaboration:

• State is immutable and traceable.
  Every message, decision, and tool call is persisted as part of a shared cognitive ledger. You can inspect how an outcome emerged, not just what the outcome was.
• Coordination is enforced at the kernel.
  Agents can fork, join, and converge dynamically, without collapsing into race conditions or split-brain states.
• Workers are framework-agnostic.
  The protocol doesn’t care how an agent thinks, only that it follows the rules of collaboration. You can plug in different models, stacks, or execution environments without rewriting the system.

This is what allows CGC to move beyond toy demos and into real world coordination.

Humans Are Not “In the Loop.” They Are In the System.

One of the core design choices in Common Ground is simple: humans and AI are equal async agents.

We wire CGC directly into collaboration tools like Slack. The result is not a chatbot in a channel, but a shared protocol space where:

• Humans inject intent mid-flight
• Review research plans as they form
• Authorize code while agents are already executing
• Participate in the same state machine as AI workers

The machine adapts to human cadence, not the other way around.

This is not “human-in-the-loop.” It’s human-in-the-organization.

Seeing the Agent Think

We also built internal interfaces on top of CGC that let you see what’s happening inside the system.

Our collaborative workspace uses a state model we call CardBox: every piece of reasoning, every tool call, every branch of thought becomes a visible, navigable artifact.

Instead of a black box, you get a living map of cognition:

• You can trace how an idea formed
• See where an agent branched
• Intervene mid-thought
• Course-correct before errors propagate

This turns agents from opaque executors into true co-creators.

From Single-Player Agents to Digital Organizations

The era of the “single-player agent” is ending.

The future doesn’t belong to isolated loops running faster and faster; it belongs to structured human–agent ecosystems that can sustain complexity over time.

What we’re building with Common Ground is not just better automation. It’s the foundation for functioning digital organizations:

• Teams of agents with division of labor
• Humans embedded as peers, not supervisors
• Shared memory, shared protocol, shared ground truth
• Resilient coordination under real-world load

The kernel is live. The protocol is evolving. The ecosystem is just getting started.

What's Next

The open-source release of the core engine is just the baseline. We'll continuously iterate this Core, evolving it step-by-step to power the complex, large-scale human-agent systems of tomorrow.

Get Involved

Review the code and build with us:

• GitHub: https://github.com/Intelligent-Internet/CommonGround
• Developer Community: https://discord.com/invite/intelligentinternet

Fork it, extend it, and show us what you build.