We used to think of visualisations for teams as boxes and lines. Org charts. People reported to people, and that was about that.
I've never felt like this was enough. Reporting is one lens on how work happens, but what about influence? Communication lines? Collaboration? Process? Where are the bottlenecks? Who is underutilised, either in terms of workload, skills, or simply raw potential?
But now, as AI systems of every flavour are taking on responsilibities, those old diagrams are next to useless. They don't even necessarily approximate the relative cost centers, or come anywhere close to showing how the work gets done.
The question isn’t who reports to whom anymore.
It’s: "who is doing the work, how, and why?"
From Org Charts to Workforce Operating Systems
The static org chart was built for a different era. An era where change was occasional and roles were slow to evolve. But today’s organisations need to adapt weekly, sometimes daily. Especially when people work cross-functionally, and crucial parts of the team never sleep.
In this new world, we need something more dynamic. A live, evolving map of responsibilities, flows, and feedback loops.
Not just who someone is and who they report to, but what they’re doing — what are the loops they're a part of, where are the opportunities, gaps, bottlenecks and risks?
We need visibility.
This is the premise of ORTO.team, which represents a way of breaking down and visualising work that I've been rendering in my mind for, well, years now. Someday it may become tool to build a Workforce Operating System, reflecting how hybrid human–AI teams actually get things done.
Not who sits where.
But who does what, and how that work aligns with what an organisation stands for. Values. Growth. And All That.
Mapping the Invisible Work
Most of the critical work we do these days isn't represented on an org chart.
It lives in Slack threads, Figma files, various automations, and LLM outputs we copy and paste.
- Who’s owning the customer experience loop?
- Where is automation quietly propping up an entire department?
- Which AI agents are doing things no one’s reviewing?
These aren’t edge cases. They’re the new normal. And they’re invisible unless we start mapping work, not titles.
Modularity, Not Monoliths
Core to the ORTO.team concept is the idea of modular roles. Because roles evolve as capabilities change. Roles evolve because people grow.
As AI improves, responsibilities shift.
As strategies evolve, roles reconfigure.
As teams learn, the system must adapt.
Roles shouldn’t be static. They should be strategic.
Humans and agentic AI are alike in this way.
Modularity lets us:
- Reassign responsibilities across humans and systems
- Align daily work with values and objectives
- Track real contribution — not just presence or position
- Design teams that flex, not fracture
It’s not automation. It’s coordination. Choreography, perhaps.
Accountability in the Age of Agents
When AI contributes to decision-making, we can’t afford vague boundaries.
Accountability matters more than ever. Visibility is the key.
Because trust scales when visibility does.
This Is More Than a Tool
Like Automation Transformation, this isn’t just a new stack.
It’s a new skill.
A new way of seeing teams and leading them.
This is necessary because in a hybrid team, where humans and AI work side by side, I can’t find a way to answer the simple question:
"How does the work get through?"
The shape of work is changing. The shape of our teams is changing too.
And with it — the shape of leadership.