AI work is often invisible in org planning
Agents and automations change how work gets done, but many planning tools still treat them as side notes instead of contributors in the operating model.
AI operating model
Design the operating model your AI strategy actually needs
Represent people, AI agents, and automated processes as contributors in the same structure so leadership can see how AI changes roles, teams, cost, and capacity.
Why it matters
The planning gap Orgonaut closes
These pages are written for teams that already feel the limits of static org charts, fragmented planning data, and spreadsheet-led change.
Human capacity and agent capacity get separated
When AI usage, cost, and accountability sit outside the org model, leaders struggle to understand the real shape of the team.
Governance needs a model to operate on
AI-assisted planning is safer when agents work through scenario contexts, scoped APIs, and visible change history.
Capabilities
What Orgonaut gives you
The product primitives are deliberately small: structure, actors, positions, placements, scenarios, snapshots, and history.
Actors beyond humans
Model people, AI agents, and automated processes as actors inside the same organisation structure.
Scenario-safe AI work
Use scenarios as a governed working context for proposed AI-assisted changes.
Agent-accessible model
Expose the operating model through API, MCP, and CLI surfaces designed for controlled automation.
Cost and capacity visibility
Bring contributor cost, allocation, and capacity into the same view as structure and roles.
Human review paths
Keep proposed changes reviewable before anything is promoted into the live organisation state.
Shared language for AI change
Give executives, operations teams, and technical leaders a common model for AI-augmented work.
Planning model
AI operating model design needs more than a diagram
Orgonaut gives AI-forward teams a structured way to reason about where agents fit, what they cost, and how proposed changes affect the rest of the organisation.
- Actor types for people, AI agents, and automated processes
- API, MCP, CLI, and assistant surfaces for controlled access
- Scenario workflows that keep proposed changes reviewable
Workflow
A safer path from idea to approved change
Use scenarios as the working layer between the organisation you have and the organisation you are considering.
1
Map contributors
Represent human workers, agents, and automated processes in the same actor model.
2
Place them in structure
Connect contributors to teams, roles, allocations, and costs.
3
Model the next operating shape
Use scenarios to test how AI changes the team design before committing.
4
Review and govern
Keep AI-assisted changes bounded by permissions, history, and promotion workflows.
Ready to model your organisation before you change it?
Start with Orgonaut, or contact us if you want to talk through fit first.