Today TIME published an Op-Ed I wrote titled You Can’t Predict the Future. But Can You Rehearse It?. The piece explores a simple but important idea: the future is not something we can reliably predict, but it is something we can rehearse.

The Op-Ed focuses on why prediction is becoming less useful in a world where pressures across science, technology, geopolitics, economics, society, philosophy, and the environment are arriving at the same time. But the article only briefly touches on something that has shaped my thinking over the past year: how the idea of possibility chains actually emerged. It started with a familiar problem.

I was preparing for a board-level discussion about the future and thinking carefully about how to frame the forces reshaping the system. The goal was not to speculate about distant possibilities, but to help leaders understand where pressures were building and how those pressures might begin to interact in the years ahead. But something about the exercise kept bothering me.

For years I had been presenting a framework that examines how forces across seven domains—science, technology, society, geopolitics, economics, philosophy, and the environment—interact to shape the future. The conversations were often eye-opening for leaders, revealing how much change was building across systems at the same time. Yet the reaction was surprisingly consistent. After the discussion, attention quickly returned to the immediate horizon. As one leader put it bluntly, “This is fascinating, but right now we just need to focus on the next 18 months.”

Those conversations forced me to confront a deeper problem. The approach I used helped leaders see how much change was unfolding across the system. But they did not always make clear when pressure was building, where decisions would matter, or why leaders should act sooner rather than later. That realization pushed me to rethink how we approach the future.

Much of traditional foresight begins by imagining outcomes. We picture what the world might look like ten years from now and then work backward to explain how we might get there. But real systemic change rarely unfolds in that orderly way. Major transitions typically occur when pressures that originate in different domains begin to interact.

• A technological breakthrough reshapes economic incentives.
• Economic changes alter how people work and define security.
• Social responses provoke political action.
• Environmental constraints accelerate innovation or redirect it.

Each of these developments can be understood individually. The real transitions occur when they begin to reinforce one another over time. That insight became the starting point for what I now call possibility chains. Rather than trying to predict a single outcome, possibility chains trace how observable developments interact across domains and across time. They follow how pressures build, how systems attempt to adapt, and how accumulated strain eventually forces structural change.

Most systems adapt successfully for long periods. Organizations adjust processes, markets absorb shocks, and institutions revise rules as conditions evolve. But adaptation has limits. As pressures accumulate, flexibility begins to erode. Decisions become harder to reverse, options narrow, and incremental adjustments stop being enough. When that happens, systems move from adaptation toward reconfiguration.

Over the past several years we have seen this pattern repeatedly. Supply chains optimized for efficiency fractured under stress and were rebuilt around resilience. Work structures that once revolved around centralized offices became more fluid and distributed. Institutions designed for slower change struggled when events moved faster than their processes could accommodate. These shifts were not isolated disruptions. They were signals of pressure accumulating across interconnected systems.

Possibility chains are designed to make those pressures visible. By tracing how developments across domains interact, leaders can walk through plausible futures in advance and explore the tradeoffs each path presents. Every emerging development carries both upside and downside. A new capability can unlock productivity and creativity, or deepen inequality and fragility depending on how it is adopted and governed. Institutional reform can restore trust or entrench exclusion. Environmental constraints can accelerate innovation or trigger instability depending on timing and response.

Seeing those tradeoffs before pressure forces a decision creates a decision space. This idea of rehearsal is common in other high-stakes environments. Pilots rehearse responses to plausible sequences of failure so they are not improvising in the air. Cities rehearse coordination for disasters so response does not depend on perfect foresight. Complex systems are navigated through preparation rather than prediction.

The same principle can apply to how we think about the future. Over the past year I have been refining the possibility chain approach and developing an AI-supported prompt architecture that allows these chains to be constructed and explored systematically. The goal is to move beyond abstract conversations about the future and toward approaches that help leaders see where pressures are building and where decisions can still shape outcomes.

Prediction will always have limits. The future is too complex, and too many forces interact at once. But if we can better understand how pressures accumulate and interact, we can rehearse our responses before systems move from adaptation to structural change. That is the idea behind possibility chains. And it is why I believe the future is not something we predict. It is something we rehearse.

The ideas in the TIME article are part of a broader conversation I have been having with leaders about how pressures across science, technology, society, geopolitics, economics, philosophy, and the environment increasingly interact to shape the systems we operate within.

If you happen to be in Austin for SXSW, I will be exploring these ideas further during a fireside conversation on Monday, March 16. We will discuss why prediction has never been enough and how leaders can better rehearse the future by examining where pressures are building across these seven domains and how systems begin to change when those pressures start to converge.

The goal of the session is not to speculate about distant possibilities, but to think more clearly about how complex systems evolve, where constraints are beginning to form, and where decisions still have the power to shape outcomes.

If you are attending SXSW, I hope you will join us.