Agent layer
Generate reasoning
Models, agents, and tools generate candidate reasoning and workflow artifacts.
Category explainer
Control Plane for AI agents
The model can remain probabilistic. The boundary before action should be explicit, reproducible, and validator-checkable.
Organetic uses the Control Plane frame to separate generated reasoning from trusted workflow decisions. Stage 1 makes that practical through Tobi Validator: a released CLI and GitHub workflow gate for reasoning artifacts.
Where Organetic fits
Between agent output and irreversible workflow effects
Use the validator gate where a generated artifact would otherwise become a merge, deployment, tool call, release step, or expensive scientific computation.
Control Plane
Validate artifacts
Tobi checks canonical ASCII, _h, deterministic diagnostics, and golden/conformance behavior.
Action layer
Gate decisions
The workflow decides whether to pass, fail, investigate, or preserve the artifact as evidence.
Stage 1
What is shipped now
- validator-first CLI
- GitHub Action / workflow path
- canonical ASCII and
_h - deterministic diagnostics
- golden / conformance execution
- controlled evaluation access
Stage 2 direction
Future, not shipped
Stage 2 is the Agent Consensus Engine direction: validating agreement between agents over validated artifacts. It is not a public CLI, not an API, not an MCP product, and not a shipped consensus protocol.
Practical path
Start with a narrow gate, not a broad platform claim
Add Tobi Validator where reasoning artifacts need deterministic validation before action.