We are not so much living in an age of growing complexity as we are confronting the reality that complexity literacy is no longer optional. Across sectors and disciplines, the limits of linear thinking are being exposed. Yet the habit of interpreting complex systems through the lens of simplicity remains deeply ingrained. We still tend to assume that complexity is merely an aggregation of simpler components, an additive logic of parts interacting in increasingly intricate ways. This mode of thought underpins much of what is commonly, and somewhat casually, referred to as “systems thinking.” But perhaps, as outlined in the preceding two thinking pieces, this framework still conceals an older reductionism: the belief that we can understand wholes by understanding parts, and that complex phenomena arise from simpler substrates.

This essay proposes a deeper reconceptualisation of complexity. Drawing from a reworking of Immanuel Kant’s philosophical insights and inspired by contemporary developments in complexity theory and philosophy (notably Deleuze’s concept of multiplicity), I suggest that complexity is not an emergent property of simple things but a primordial condition, a field of processes, not objects. From this vantage point, I introduce the notion of complexity fingerprinting as a diagnostic approach that can help us read the present state of a complex system not by analysing its parts, but by interpreting its active processes.

The long-standing assumption that complexity arises from simplicity is intuitive, but possibly incorrect. Our tendency to see simple components giving rise to complex systems is shaped not by reality itself, but by the limits of our observation. A seed becomes a tree. Molecules form proteins. Words form languages. All of these give the appearance of complexity emerging from simplicity. But this is not necessarily how complexity works.

Instead, I propose that complexity starts with simplicity but does not arise from it. This is a subtle but potentially disruptive shift in perspective. It means that what we call “simplicity” is not the origin of complexity but merely an entry point, an accessible surface that allows us to engage with systems too vast, dynamic, or layered to grasp in totality. The essence of complexity is not in the visible parts but in the invisible relations and processes that make those parts possible.

This insight parallels a shift in modern science. Physics has shown that what once appeared to be “simple” particles are themselves vast, dynamic fields of interaction. Biology has taught us that even the most basic cell is teeming with regulatory complexity. Similarly, what we take to be “parts” in social or ecological systems, individuals, trees, rivers, organisations, are in fact living processes. They are snapshots of a moment in motion, never fixed, never truly discrete.

This invites us to reframe our entire understanding of systems: from collections of parts to convergences of processes.

This shift is informed by a subtle adaptation of Immanuel Kant’s famous claim: “All our knowledge begins with experience, but it does not arise from experience.” Kant’s philosophy of knowledge offered a revolutionary insight. Our perception of reality is shaped not only by what we encounter through the senses, but by the preconditions of understanding itself. Experience begins with the world, but its intelligibility depends on something deeper, something not given in experience alone.

In this spirit, I propose: complexity begins with simplicity but does not arise from it. In other words, the intelligibility of complex systems may start with seemingly simple observations (components, behaviours, patterns), but the actual source of complexity, the condition that makes complex systems possible, lies deeper. It lies in a kind of formative logic that precedes empirical appearance.

Kant’s notion of the “enlarged mentality” also becomes relevant here. In his aesthetic theory, this is the ability to think beyond one’s own limited perspective, to imagine how others might think, to engage in reasoning that is not confined to personal interest. I propose we extend this idea into complexity thinking. An “enlarged mentality” becomes a way of inhabiting the processes of another system, not just imagining how it appears, but how it unfolds, reacts, reorganises. This is not merely empathy or mentalising, but an ongoing attunement to living systems as processes rather than stable objects. It is a disposition essential to complexity work.

This approach also aligns with post-structural insights, particularly Gilles Deleuze’s philosophy of immanence and multiplicity. Deleuze challenges the Western assumption that the One precedes the Many, that unity is primary and multiplicity secondary. Instead, he argues that multiplicity is originary, that the foundational condition of being is not singularity but variation, difference, and proliferation.

What might be called an “originary multiplicity” is a term borrowed from philosophical traditions to indicate not simply a temporal beginning, but a foundational condition from which forms and relations emerge.

This resonates strongly with complexity thinking. What we often describe as a move from simple to complex may actually be the reverse: a process of simplification imposed by perception, by naming, by systematising. Complexity is not what happens after simplicity. It is the field from which simplicity is extracted, temporarily stabilised, and made observable.

From this vantage point, complexity is not a structure, not a fixed architecture of parts, but an event. An unfolding. A living simultaneity of processes. Just as a volcano may appear dormant until it erupts, so too do complex processes fluctuate in intensity, visibility, and influence over time.

This view displaces the classic systems thinking model in which systems are seen as composed of interacting parts with feedback loops. It also moves beyond the overly mechanistic language of inputs, outputs, and causal chains. In complexity-as-event, we no longer ask what the system is in terms of parts, but what the system is doing at this moment in time, and how those processes are layered, amplified, inhibited, or redirected. This leads us to a more powerful form of engagement, not categorisation, but diagnosis.

If complexity is processual and fluctuating, then diagnosis must be about reading those processes at any given moment. This is what I propose with the concept of complexity fingerprinting. Just as a fingerprint captures the unique pattern of ridges at a point in time, complexity fingerprinting captures the pattern of active processes within a complex system at a particular moment. It is not a static map but a snapshot of dynamic tendencies. The key insight is that core processes, such as resilience, self-organisation, emergence, adaptation, equilibrium-seeking, divergence, and more, are always active within a system. However, their strength, visibility, and interaction vary over time.

For example, a system might exhibit strong resilience and weak emergence at one moment, suggesting it is recovering or stabilising. At another time, it might show high emergence and weak self-organisation, indicating creative chaos but low integration. These fingerprints help us read the current behaviour of a system without reducing it to fixed parts.

Importantly, this approach avoids the trap of intervening in systems as if they were problems to be solved. Instead, it supports strategic interventions in processes. If resilience is weak, we may nudge the system by enhancing buffering capacities. If emergence is too strong without structure, we may help support new stabilising forms. These interventions are informed not by assumptions about parts, but by readings of process dynamics. Over time and in collaboration with complex systems strategists, practitioners and analysts this method could evolve into a structured diagnostic toolkit, enabling practitioners to develop fingerprints across time and contexts, social, ecological, organisational, and adapt their strategies accordingly.

This thinking and exploratory piece follows on from the direction set in my earlier pieces, Against Hidden Reductionism and Beyond Systems Thinking. It offers a further provocation: that truly engaging complexity requires not simply new methods, but new philosophical orientations.

By grounding complexity thinking in a Kantian-Deleuzian framework, we move toward a post-reductionist paradigm, one that respects process, multiplicity, and becoming. Complexity fingerprinting offers a first practical application of this view, enabling us to diagnose, interpret, and strategically support living systems in motion.

We do not act on complexity as if it were a machine. We participate in it as fellow processes.