Chapter 5 of 10
Complementary Spectrums
A thousand identical electrons are not a hypercomplex system. They’re a set. A collection. You can count them, but you can’t analyze their structure, because there’s no structure to analyze — they’re all the same.
Three electrons with different spins, interacting — that’s a system.
Malyuta used this distinction as a foundation. The word he chose — hypercomplexity — means specifically this: qualitative diversity as a necessary condition for a system to exist at all. Without different qualities interacting, there’s no system. There’s just a pile.
Teams work the same way.
The spectrum of a person
Every person brings a set of qualities to a team. Not just their job title. Not just their technical skills. The full set: how they think, how they communicate, how fast they respond, how deeply they go, what domains they understand, where their intuition is strong, where they’re blind.
I think of this as a person’s spectrum — like a frequency spectrum in physics. Some frequencies are strong (deep technical skill, fast execution), others are weak (communication across departments, patience with ambiguity). The shape of the spectrum is unique to each person.
Most hiring processes look at one or two bands of this spectrum: “Do they know React? Do they have five years of experience?” This is like judging a symphony by whether it has a trumpet.
Learned another language or framework? Nobody cares. Today a junior with a good prompt produces the same volume of technically correct code as a senior. Syntax knowledge is no longer a filter. When companies hire by tech stack and years of experience, they’re buying what an AI agent can already do. And the one thing an agent can’t do is see the system as a whole.
That’s why a different approach is needed. Not a skill set — a spectrum of thinking.
The spectrum of a team
When you put people together, their spectrums compose. The team’s spectrum is the sum of its members’ individual spectrums.
If you put three backend developers with identical spectrums on a team, you get a very tall, very narrow combined spectrum. Enormous depth in one area. Complete blindness everywhere else. When the problem comes from an unexpected direction — a UX issue, a security concern, a political dynamic with another department — nobody sees it. The team is fragile precisely because its members are too similar.
If you compose a team where the spectrums are complementary — orthogonal, in Malyuta’s language — something different happens. Each person’s weak frequency is another’s strong frequency. The team’s combined spectrum covers a wide range. Gaps are filled. Blind spots are covered.
This is not a new observation. Everyone knows diverse teams perform better. But the theory gives us something that intuition doesn’t: a way to think about what kind of diversity matters.
Not demographic diversity (though that can help). Not random diversity (throwing different people together and hoping for chemistry). Structural diversity — where the specific qualities each person brings are orthogonal to the others, and together they form a spectrum that covers the space the team needs to operate in.
This is what цілісність — completeness — means in practice.
How to see it
You can’t see a team’s spectrum in a spreadsheet of skills or a list of job titles. It emerges from how people actually interact.
Who responds when another department sends an unclear request? That person has a translation quality — they can operate across boundaries even when the information is imperfect.
Who has the courage to ask the uncomfortable question nobody wants to hear? That person has a depth quality — they prevent the team from taking the easier but wrong path.
Who generates energy in meetings, making others want to actively engage in solving problems? A catalyst quality — just by being present, they make the whole team turn more of what it has into value.
Who quietly fixes things nobody asked them to fix? That person has an integrity quality — they maintain the system even when nobody’s watching.
None of these show up in a job description. All of them determine whether the team’s spectrum is complete or has critical gaps.
The invisible member problem, revisited
On page 2, I described people who are invisible in cross-functional work — present but not contributing to the value flow.
The spectrum model reframes this. An invisible member isn’t necessarily a problem person. Their spectrum may simply not overlap with the team’s current challenge. Their frequencies are strong, but the team isn’t operating in that range.
This is a structural diagnosis, not a performance judgment. The solution isn’t to fire them or pressure them. It’s to find the challenge — or the team — where their spectrum is needed.
Of course, there are genuinely flat spectrums — people with no observable signal in any direction. No contribution to the internal cycle, no contribution to external output. This is a real signal. But it should prompt a question about structure first, and only then about the person.