Your organization is filled with capable people.
People care about their work.
New technologies promise greater efficiency.
Artificial intelligence is opening possibilities that didn’t exist a year ago.
And yet, it feels increasingly difficult to see the whole picture.
Knowledge lives across documents, meetings, inboxes, and people’s memories.
Different teams develop different ways of solving similar problems.
Communication requires more effort than it used to.
Leadership senses that something isn’t working as well as it could, even if the underlying causes remain unclear.
Organizations rarely suffer from a lack of solutions.
They suffer from a lack of shared understanding.
Most organizations don’t lack talented people.
They don’t lack information.
They don’t lack technology.
More often, they struggle to develop a shared understanding of how all of those pieces fit together.
As organizations grow, knowledge becomes distributed across people, teams, documents, meetings, and increasingly, AI.
Communication becomes more difficult.
Different teams develop different ways of solving similar problems.
Leaders make decisions without always seeing the whole system.
We naturally experience these as separate problems.
I tend to see them differently.
More often, they’re different expressions of the same underlying reality:
the organization has become more complex than the systems supporting it.
When organizations reach this point, the natural response is to look for better solutions.
A new platform.
A new process.
A new framework.
A new AI tool.
Sometimes those changes help.
But before deciding what should change, I believe it’s important to understand why the current system is producing the results it is.
That’s where I begin.
I listen.
I ask questions.
I work to understand how the organization functions today — not just on paper, but in practice.
Where does knowledge flow naturally?
Where does it become trapped?
Which teams have quietly developed effective ways of working?
Which assumptions are no longer serving the organization?
Only then do we begin identifying thoughtful experiments that move the organization toward its desired future.
My goal isn’t to introduce someone else’s system.
It’s to help your organization better understand its own.
My perspective didn’t come from studying a single discipline.
It emerged from working across several of them.
Over the past three decades, I’ve worked as a composer, educator, designer, software engineer, startup founder, and, more recently, alongside organizations exploring the practical use of AI.
I lived and studied across Europe for over a decade before earning my Ph.D. in Music Composition at the University of California, Berkeley.
Although those experiences may seem unrelated, they’ve all taught me the same lesson:
Complex systems can’t be understood by looking at individual parts in isolation.
As a software engineer, I became increasingly interested in software architecture and the relationships between systems rather than individual pieces of code.
As the founder of Troo, I spent more than four years building and leading a volunteer team around the vision of an ethical social media platform. We designed a complete product, developed organizational processes from the ground up, and came close to raising $2 million before running out of funding.
Following that experience, I spent the next several years exploring a different kind of complexity: how people come to understand themselves more clearly. That work ultimately led me back to organizations with a new realization.
Organizations, like people, benefit from understanding themselves before deciding what should change.
Today, I help organizations better understand themselves before deciding what should change.
Every organization is different.
Rather than describing my work in the abstract, I’ve written a few short explorations of common organizational situations.
They aren’t case studies or templates.
They’re examples of how I approach complexity.
Michael Nicholas