The most energy-effective leverage point is not the individual but the relations between individuals — the coordination, information flows, trust and power from which collective intelligence and resilience emerge. These relational properties can, and must, be measured.
The most energy-effective leverage point is not the individual but the relations between individuals — the coordination, information flows, trust and power from which collective intelligence and resilience emerge. These relational properties can, and must, be measured.
Reality nests from the subatomic to whole societies. Most layers are inaccessible or don't scale. The outer relational layers — organisms, communities, societies — are where small, well-placed interventions reshape the whole.
Impact. Investors, founders, philanthropists, experts, governments, for-profit and non-profit organisations — so many of us are directing attention and resources toward it. And so we keep asking the same four questions: what counts as impact, how is it measured, what matters most, and why. These are not simple questions, because neither we nor the world we inhabit are simple. Navigating the vast, complex landscape of shifts that could create beneficial change can feel overwhelming, and the temptation is to simplify. Simplification helps with day-to-day decisions, but it is unnatural to complex systems — it strips away exactly the structure that makes them what they are.
The answer this paper proposes is not to remove the layers but to trace the connections between them — following the flow of influence until it converges on a potent leverage point. A leverage point is a strategic location within a system where a small, well-aimed intervention can produce significant, system-wide effects, especially when it reaches a deeper structural layer. The work begins by zooming out to look at the complex system we live inside, mapping its nested layers and how they influence one another, and then zooming in on a single hypothesis: that the most energy-effective leverage point is relational dynamics.
Whether that hypothesis holds is something each reader will have to decide by the end. In the meantime, the invitation is to ask new, deeper, and more nuanced questions — because that is how we move forward: by mobilising collective intelligence toward impact that actually matters. What follows is offered as a frame-work in the most literal sense, a skeleton and a foundation rather than a finished answer.
We believe the answer is not in stripping away the layers, but in tracing the connections between them — until we find potent leverage points.
This is the discipline the rest of the essay tries to hold: refuse the comfort of the simple metric, follow influence where it actually travels, and accept that the leverage we are looking for may live not in any single component of the system but in the quality of the relations between them.
The central premise is that complex systems are organised in layers. Each layer has its own characteristics and operating principles, yet all are interconnected, so that a change in one layer produces ripple effects that touch the others. To work with such a system strategically, you first have to understand how change moves through it — and it moves in two distinct directions, each with very different properties.
Upward propagation is the easy direction. Modifications to fundamental, structural layers — subatomic, atomic, molecular, genetic — tend to cascade upward automatically, reshaping the characteristics of every higher-level system built upon them. Alter the molecular structure of a compound and its material properties change; edit an organism's genes and you can shift its physiology, its behaviour, even its role in an ecosystem. For a systems thinker, anticipating this upward cascade is essential to seeing the full spectrum of consequences a foundational intervention may unleash.
Downward influence is the hard direction, and historically the slow one. Reaching down from a higher level of organisation to reshape a deep structural layer — societal change rewriting genetic structure, for instance — used to happen only over evolutionary or geological time, through processes like natural selection. Technology has fundamentally altered that dynamic. Gene-editing now permits direct modification of DNA that was unimaginable for most of human history, and technology has become the primary means by which higher-level systems can consciously engineer or perturb the foundations beneath them. Identifying where technology opens such downward leverage is precisely where the most potent, enduring interventions are found. Practically, the framework asks the analyst to do five things: map the terrain, trace the interconnections, identify leverage points, allocate resources strategically, and assess the cascading impacts of a change before committing to it.
Upward emergent changes from structural modifications are often automatic; interventions aimed at altering the structural layers themselves are more complex and resource-intensive, yet offer the potential for more fundamental and lasting shifts.
Reality nests. The framework lays out eleven layers of organisation, grouped into four families: the universal building blocks from which all physical reality is constructed; the cosmological and astronomical environments that set the stage; the molecular and biological emergence that unfolds within a hospitable planet; and the social and anthropic systems that arise from biological populations. Each layer builds upon the one below it, and each adds its own characteristic components, processes, and dynamics.
Most of these layers are, for practical purposes, either inaccessible to deliberate intervention or impossibly resource-hungry to move. We cannot reach the cosmological scale, and reaching below the individual — into the molecular and genetic — remains hazardous and uncertain. The argument of this paper is that the productive frontier sits in the three outer relational layers: nine, ten, and eleven, from the individual organism to populations and communities to societies and global systems. It is there, in how living things relate, that interventions become both tractable and powerful.
Within the human layers, the core thesis — a north star running through everything from capital allocation to infrastructure development — is that interventions targeting the relational dynamics between individuals and groups are more resource-effective, and more capable of producing lasting systemic change, than efforts focused on modifying individuals in isolation. Individuals are the actors, but the relations between them are the leverage.
Three reasons support this. First, context shapes behaviour: individuals are deeply influenced by their relationships, norms, available information, and structures of interaction, so changing a person without altering their relational context usually leads to reversion as the surrounding system reasserts its old pressures. Second, scalability and efficiency — what the paper calls the energy ratio. Changing one individual deeply is intensive and slow; changing a system one person at a time would demand a prohibitive amount of energy. But modifying how individuals or groups relate — communication protocols, information flows, incentive structures, a dominant narrative — can shift the behaviour of many at once, so a comparatively small input into the relational fabric can trigger widespread adaptation. Third, emergence: culture, trust, collective intelligence, and resilience are not properties of isolated individuals but properties that emerge from the patterns and quality of their interactions, and the only way to change them is to address the relational dynamics that generate them.
This advancement is not primarily due to changes within individual human biology, consciousness or cognitive capacity, but rather to radical shifts in how humans relate to each other and to knowledge.
The clearest evidence is the recent trajectory of Homo sapiens. Our genetic makeup has not changed dramatically over tens of thousands of years, yet our technological capability, societal complexity, and planetary footprint have exploded. The cause is not a better brain but better relating — complex language, writing, social learning, cumulative culture, shared narratives, scientific method, and vast communication networks, all of them profound changes in relational dynamics that unlocked unprecedented cooperation, knowledge accumulation, and innovation. A frontier of deeper intervention is opening — genomics, synthetic biology, biosphere engineering, even terraforming — but these target the structural underpinnings of life and remain marked by limited predictability, substantial ecological and health risks, and unresolved ethical and governance dilemmas. For the coming decade, the relational layer offers a more understandable, manageable, and safer pathway: shorter feedback loops, more observable systems, and a greater capacity for adaptive learning.
Drill into relational dynamics and you reach coordination — the process of organising and integrating the actions of multiple autonomous or semi-autonomous agents to achieve a shared goal or a coherent collective outcome. It is the art and science of getting different parts of a system to work together so that efforts are aligned, resources are used efficiently, and actions are synchronised in time and space. It need not be rigid top-down control; it can emerge from simple rules, be facilitated by leaders or structures, or be designed into the fabric of how a system operates. The capacity for effective coordination is a primary determinant of a system's success, resilience, and evolutionary potential — and without it efforts duplicate or work at cross-purposes, synergies are missed, complex goals stay unreachable, crisis responses slow, and trust erodes.
Coordination is fundamentally a relational phenomenon, arising from the nature and quality of the connections between a system's components. Five relational dynamics underpin it: information flow and shared awareness — who talks to whom, through what channels, with what accuracy, timeliness, and bandwidth, and whether shared mental models form; trust and reciprocity — the willingness to rely on each other's commitments, the lubricant that lets high-trust environments shed cumbersome verification; norms, rules, and protocols — the implicit understandings and explicit agreements that shape how agents interact, decide, and resolve conflict; interdependence and role clarity — how much agents depend on each other and how clearly their roles are defined; and feedback loops — the mechanisms by which the system senses outcomes, returns that information to the right actors, and adjusts.
Each of those dynamics is a place to intervene. Five leverage points follow directly, each with a favourable energy ratio — significant systemic improvement from focused effort.
Build platforms that get transparent, timely, relevant information to the right people, and standardise communication for critical or delicate situations — reducing ambiguity and enabling faster, more synchronised decisions.
Define who is accountable for what and how decisions are made, integrating efforts across organisations and cultures while retaining individual agency and without dissolving organisational membranes.
Foster open communication, mutual respect, fair process, and accountability, raising the willingness to share, cooperate, take risks, and offer discretionary effort.
Facilitate the co-creation of guiding principles and shared goals, providing common ground that lowers the transaction costs of constant negotiation and aligns autonomous action.
Create regular opportunities for reflection — after-action reviews, retrospectives — so the system learns to coordinate better over time, becoming more adaptive and resilient.
The Sapiens example, revisited, shows the energy ratio at work in each. Language is a coordination protocol — a small set of shared rules unlocking immense collective capability in planning, learning, and cultural transmission. Writing and digital communication altered the scale, speed, and persistence of information sharing at a development cost dwarfed by their societal impact. The scientific method is a protocol for coordinating inquiry and validating knowledge cumulatively. Market mechanisms and legal frameworks coordinate the economic activity of millions, enabling specialisation and trade. In every case, a change to the mechanism of interaction was leveraged into a massive advance in collective capacity.
Designing better coordination mechanisms is one thing; practising coordination in real human systems is another, because those systems are built from human beings with inherent frictions. The macro-level functioning of a society is ultimately constrained by the micro-level attributes of its members, and three of those attributes structurally limit our collective capacity to coordinate.
First, cognitive and communicative limits: bounded information-processing speed, attention, and memory, susceptibility to bias, and a communication faculty that, however remarkable, still produces misunderstanding and misinterpretation. Second, biological and genomic predispositions: an evolutionary heritage tuned for small-group cohesion that scales poorly to large, diverse societies — we are not eusocial the way some insects are, and individual drives can sometimes act like invasive-species traits within a social ecosystem if not constructively channelled. Third, fundamental human drives: the enduring search for security, recognition, resources, influence, and response to physiological stimuli, which culture can shape but not abolish. Even perfectly designed coordination mechanisms must navigate, rather than ignore, these realities — which is why coordination in most societies operates far from optimal, marked by flawed information flows, trust deficits, and the misaligned ultimate aims that the concept of telodiversity names.
Power is the pivotal relational dynamic in this terrain. The drive to seek power may be latent in an individual, but power itself can only manifest in relationship — to other people or to the environment — and it is in those interactions that its acquisition, distribution, use, and abuse unfold. Societal structures rarely create the drive for power, but they profoundly shape how it is expressed and legitimised, how it is distributed or concentrated, whether it serves exploitation or collective benefit, and what mechanisms exist for accountability and redress. Changing structures will not eliminate the human interest in power, yet well-designed relational protocols and governance can mitigate its harms and channel it toward constructive ends. A central contemporary concern is the rapid concentration of power — often amplified by technology — into a small minority whose ultimate aims may diverge sharply from the well-being of the general population and the health of the biosphere.
We may not be able to easily solve fundamental aspects of human nature or eradicate power differentials entirely — but we can design better relational systems, information environments, and governance structures.
Acknowledging these constraints is not counsel for despair; it is a more realistic landscape for finding leverage. Refining our understanding and application of leverage points within the relational dynamics of existing human systems remains a vital and perhaps more immediately tractable path to positive change than the riskier frontier of deep biological and environmental engineering.
To allocate energy — capital, effort, attention — toward transformative phase shifts, we need to measure the state and trajectory of the systems we hope to influence. Working from the hypothesis that relational dynamics are the key leverage point, and focusing on nested layers nine, ten, and eleven, the metrics must illuminate the quality, structure, and potential of relational dynamics in those layers. Crucially, they must be leading indicators of emergence and phase transition, not just lagging indicators of past performance: selected to track progress toward evolutionary leaps, global harmony, elevated collective intelligence, and resilience, while providing early warning against extreme convergence of power, existential risk, erosion of trust, and systemic fragility.
The catalogue organises into five categories. Connectivity, coordination & information flow assesses the architecture and quality of interactions — the Interconnectedness Factor, Feedback Loop Velocity, Change Propagation Rate, Information Flow Entropy, Composability Index, Collective Intelligence Architecture, and Cross-System Integration Quality, asking whether connections foster diverse exchange or echo chambers, and how fast valuable signals propagate. Trust, social cohesion & power dynamics reads the social fabric and the distribution of influence — the Harmony and Peace Coefficient, the Power Distribution Index, the Malevolence Containment Factor, Trustworthiness Infrastructure, Legitimacy Generation Capacity, and Social Cohesion Metrics, asking whether trust is rising, whether power is concentrating or dispersing, and whether accountability mechanisms hold.
Innovation & emergence potential tries to quantify the system's capacity for novelty and transformation — the Emergence Potential Index, the Adjacent Possible Expansion Rate, Cultural Innovation Rate, Memetic Diversity and Fitness, the Attractor Formation Quotient, the Cross-Domain Coupling Index, Positive Feedback Amplification Capacity, and the Distributed Agency Enablement Score. Resilience, adaptability & regenerative capacity measures the ability to absorb shocks, learn, and renew underlying resources — Current System Resilience, the Adaptive Capacity Metric, the Antifragility Quotient, Regenerative Capacity, the Shared Resource Stewardship Index, Polychronic Adaptation Capacity, Phase Shift Navigation Intelligence, and the Selective Permeability Index. And risk awareness & epistemic security gauges whether a system can perceive threats and stay tethered to reality — Externality Cost Quantification, the Epistemic Security Index, Civilization-Level Threat Awareness, Coordinated Response Capability, Collapse Deceleration Potential, and Collapse Acceleration Risk.
The goal is to find interventions in the relational dynamics that show positive movement across multiple desired metric categories — leading indicators of emergence and resilience — rather than optimising for lagging indicators like financial returns alone.
A handful of composite indices recur as the most telling. The Emergent Value to Invested Energy Ratio — the EVE Ratio — attempts to quantify the novel, beneficial emergent value a system generates against the total energy invested in it, a direct measure of the energy ratio that runs through the whole framework. The Relational Overhead Ratio compares the energy spent maintaining internal coordination and resolving conflict against the energy applied to external goals. And the Collective Learning Cycle Time measures the duration of a system's full Sense–Make–Decide–Act–Learn loop. Many of these properties resist clean quantification — trust, meaning-making, and values transmission may need qualitative or proxy assessment — so a mixed-methods approach, combining network analytics with ethnography, surveys, and expert judgment, is usually required to get a sufficiently rich picture.
Underneath the whole apparatus of metrics sits a single cycle, and the faster and cleaner a system can run it, the more adaptive and resilient it becomes. The Collective Learning Cycle — Sense, Make, Decide, Act, Learn — runs from detecting a significant internal or external signal, through collective sense-making, through decision, into coordinated action, and back through learning from the feedback. Shorter cycles enable faster adaptation and evolution, which is decisive in rapidly changing environments; and the quality of the cycle depends on feedback signal fidelity — how accurately the mechanisms reflect reality, how clearly they communicate, how well they filter noise, and how reliably they lead to appropriate adaptive action.
Detect the significant event, signal, or data point — internal or external — with information of sufficient quality, reach, and trustworthiness to be worth acting on.
Collectively make sense of what the signal means, building shared awareness and shared mental models across the relevant actors.
Reach a decision through whatever legitimate process the system has agreed — consensus, delegated authority, or vote — with roles and accountability clear.
Translate the decision into coordinated, synchronised action, integrating diverse contributions into a coherent collective response.
Capture the feedback from the action, fold the lesson back into the system, and shorten the next cycle — the engine of antifragility.
This framework is exactly that — a frame-work: a structure, a skeleton, a foundation for impact created together, in coordination. It is offered with a set of invitations to those who feel called to continue the work. Build with us: through masterminds and in-person workshops at the Villa Gaia Impact Hub in Italy, where systems-change knowledge is grown and connected to real projects, and through a fund whose two pillars — one for impact investors, one for philanthropic contributors — aim to prove that ethical, regenerative practice can be economically superior. Add your puzzle piece: if you are already tracking one of these metrics, or hold tools, data, or protocols that could bring the work into practice, there is a place for it.
Build upon the framework, too. Apply it in practice and report what emerges; develop it further where you see gaps and share what you discover; and if it sparked counter-arguments, all the better — critique and new perspectives are part of how any good framework evolves. Compost it if you must. The point was never to deliver a finished answer but to mobilise collective intelligence toward better questions, and to leave the reader with one in particular: having traced the connections rather than stripped the layers, do you agree that the most energy-effective leverage point we have is the way we relate?
Human advancement is not due to changes within individual biology, but to radical shifts in how humans relate to each other and to knowledge.