A system can be complicated without being complex. Complicated systems have many parts, but can often be understood by taking those parts apart. Complex systems change through relationships: their parts adapt, influence one another, and produce effects that can be disproportionate, delayed, or surprising.

I have also encountered complexity as an individual whose needs and experiences have at times been disregarded by the systems I have inhabited: social, political, and economic systems that mistreat and oppress. I have sought to understand my own position, the positions of others, and the workings of the systems that produce the status quo: both their designed features and their externalities.

Marginalization is often shaped by more than one factor. Safety, health, recognition, and the possibility of thriving emerge through the interaction of identity, institutions, relationships, material conditions, and sources of agency. Intersectionality points to the fact that social positions and systems of inequality are not simply additive. They interact, shaping distinct forms of constraint, exposure, belonging, and possibility. A complexity-aware lens shifts the question from "What is wrong with this person or group?" to "How do interacting systems shape opportunities, harms, and possibilities?"

More recently, I have worked with complexity as a coach. In my coaching practice, sitting with complexity is a core capability. To hold space for it, for my clients to face the complexity of their challenges, their environment. The task is not to eliminate uncertainty, but to help create enough clarity, steadiness, and confidence for the client to see what matters and choose their next step. One must observe, one must feel, one must exercise patience and courage. Tolerance for uncertainty. To be a coach is, in my practice at least, to accompany someone through that.

"What should I do?" is the question coaching clients ask themselves (and sometimes their coaches). A coach might respond with questions such as: "Who and what are affected by this decision?", "What happens when you respond this way?", "What power relations are operating?", "What narratives are at play?", "Where will the costs of this show up?". The answer to “What should I do?” is rarely a single prescription. More often, it is a clearer set of options, trade-offs, responsibilities, and experiments.

Complexity challenges the idea that understanding always means reducing a system to its smallest components, or that a piece of information about a complex system can be relied on for decision-making in isolation. Reduction can be useful: it lets us isolate, measure, and understand particular parts of a system. But it becomes misleading when a partial view is mistaken for the whole, or when decisions are made as if relationships, feedback, history, and context do not matter. This matters especially in a world where economic, technological, ecological, and social systems are increasingly connected, and where consequences can travel rapidly across boundaries.

"Information that does not take into account the full scope of interrelationality in a system is likely to inspire misguided decision-making, which compounds already wicked problems," says Nora Bateson. She calls this “warm data”: relational, transcontextual information that keeps a “nest of relations” intact rather than treating data points as isolated facts. It does not replace other data; it adds the contextual relationships needed to interpret them well.

Complex, systemic challenges are shaped by the interaction of multiple contexts: the economy, nature, art, culture, technology, and more. All of which have a number of interacting components of various types, hierarchies, and dependencies. To effectively address such challenges, we need understanding of the interdependence of all these things.

We live in overlapping layers of meaning: personal, cultural, emotional, and historical. Much of the data used in decision-making captures only a portion of this complexity, offering facts with limited context. Data can illuminate a system, but no dataset is self-interpreting. When data is detached from relational, cultural, historical, and material context, it can support decisions that are precise yet misguided. The question is not whether to use data, but what relationships and consequences our data practices make visible or obscure.

Responses shaped by awareness of complexity, patterns, and connections are effective. Simplistic responses to complex challenges can create new problems, shift costs elsewhere, or reinforce the patterns they aim to change.

Complexity is the stuff of interdependence, feedback, nonlinearity, adaptation, emergence, and uncertainty. Its effects can be disproportionate, delayed, collective, and surprising. It is the stuff we ought to be willing to sit with. And to become apt at it, to resist reductionism, it is a practice.

Sitting with complexity is not passive. It is the practice of resisting premature certainty while still taking responsible action. It asks us to see relationships as well as parts, consequences as well as intentions, and context as well as data.

These questions can help guide that practice:

What becomes visible if I expand the boundary of this question?

Who defines the problem, the evidence, the options, and the criteria for success?

What is the system currently organized to produce?

We form and clarify our intentions within complex environments. Here, I intend to share what I learn, what I think, what I feel about it, and what might be helpful to other people. People who, like me, exist within a multitude of complex systems. What it comes to exactly we’ll find out along the way.