Most leaders can name their “messy” client relationships—the ones full of surprises, shifting scopes, and long, meandering conversations (yes, including disputes and arguments) that somehow still move the work forward. They’re never as tidy as the contract or org chart suggests. Yet these are often the partnerships that last the longest and deliver the greatest value.
In reality, messiness isn’t a symptom of failure...it’s the texture of real learning.
Where the Mess Comes From
Messiness appears the moment real collaboration begins. It’s what happens when two systems, two organizations, or even two people, start learning each other’s rhythms. Context changes, priorities drift, language collides. Not all people are easy to work with, and that isn’t necessarily a negative; it’s often what keeps the relationship alive.
Human difference generates friction, and friction is where learning happens. From Chris Argyris’s work on double-loop learning to Donald Schön’s reflective practitioner and David Kolb’s experiential learning cycle, research has long shown that growth doesn’t come from smooth performance—it comes from the tension between expectation and surprise.
I wrote about this dynamic in UNMANAGED, and it’s also a core part of the Context-Based Briefing technique I teach. The process depends on what I call micro-collisions—small, rapid exchanges where assumptions meet, sometimes clash, and then real understanding starts to form. These micro-collisions are not interruptions nor are they conflict; they’re learning events. They build shared mental models and accelerate comprehension across disciplines and roles.
In both teams and buyer–seller relationships, these collisions create a loop of sense-making: each misunderstanding becomes a data point, and each repair strengthens trust.
Being Good at the Mess
The ability to work inside complexity—without needing it to resolve too quickly—is a modern organizational superpower. The best leaders don’t smooth over uncertainty; they learn to hold it. They recognize that beneath confusion there’s often unarticulated knowledge trying to surface.
This is the heart of unmanaging: creating space for difference, emergence, and human rhythm. Csikszentmihalyi’s research on Flow, Schein’s work on culture, and Nonaka’s studies of knowledge creation all point in the same direction—adaptive performance depends on a system’s capacity to learn from friction, not avoid it.
Organizations that master this develop structural competence in ambiguity. They don’t just endure complexity—they metabolize it. These are the relationships that resist disintermediation. They’re not merely about delivery; they’re about co-evolution. Each side learns the other’s context so deeply that the line between buyer and seller begins to dissolve.
AI and the Clean-World Problem
AI, by contrast, needs cleanliness—structured inputs, clear rules, and predictable mappings. Wherever a relationship can be reduced to data, AI will do it faster and cheaper. But the messy world—the one full of tacit meaning, emotion, and judgment—remains stubbornly human. The danger is that organizations obsessed with efficiency will strip away the very complexity that makes them resilient. They’ll optimize for clarity and lose their ability to learn.
A New Kind of Mastery
The next strategic advantage belongs to those who practice messiness well—who can interpret nuance, navigate disagreement, and find coherence in disorder. This isn’t soft-skill territory; it’s systems competence.
AI eliminates friction. But friction is where adaptation, learning, and trust are made.
The companies that thrive won’t be the cleanest or most automated. They’ll be the ones that can live—and learn—inside the mess.
