We Sit At a Precipice Between Systems

AI can augment how you learn, create, make, and grow. But only if you take responsibility for developing your creative process, sharpening your discernment, and evolving your working methods.

We are living through a transformation today with AI that makes telecom deregulation in the 1990s look quaint. But for those of us who worked in it and lived through it, it was a big deal, and I found myself in 1996 at the “Systems Thinking is Action” conference in San Francisco with ten colleagues—all of us working on mainframe telecom billing systems.

Going into the conference, I knew nothing about “systems thinking”, but by the end, it had become a lens, a worldview, that would shape the next 30 years of my life.

It was like that story of the goldfish, which David Foster Wallace told in a commencement speech in 2006: “There are these two young fish swimming along and they happen to meet an older fish swimming the other way, who nods at them and says ‘Morning, boys. How’s the water?’ And the two young fish swim on for a bit, and then eventually one of them looks over at the other and goes ‘What the hell is water?’

All of a sudden, I could see the water and the implications of the water as a system for all who swam in it.

Being able to observe, describe, and model the impacts of systems instilled in me a responsibility to build better systems and apply systems thinking to redesign and nudge existing ones.

Applying a systems thinking approach has done more to shape my entrepreneurial career in technology than almost anything else. And in the age of AI, it’s a lens that’s never been more relevant or clairvoyant.

The core ideas of the 1996 conference on systems change remain as timely as ever today. Renowned thinkers like Peter Senge and Meg Wheatley made it clear: there’s a fundamental difference between systems thinking that optimizes an existing paradigm and systems thinking that explores, experiments, and engages with a new system.

Today, something rare is happening. We sit at a precipice between systems: an old system in which human intelligence commands instrumental technology, and a new system defined by the interaction between human intelligence and superintelligent technology.

It is at this threshold that systems thinking doesn’t ask us to make incremental tweaks to the existing system, but rather to leap into the new one. In the old system, we adjust the variables of a known game. In the new system, we discover new, unknown games. In the old system, we accept and work within the established rules. In the new system, we help shape the future rules.

In new systems, the difference between those who thrive and those who flounder is one thing: the ability to take responsibility.

AI can augment how you learn, create, make, and grow. But only if you take responsibility for developing your creative process, sharpening your discernment, and evolving your working methods. We call this the Generative Way—using your agency to guide yourself toward the world you want to create.

An old system of hierarchical expert-led teaching will transition into a new system of flattened and distributed learning.

An old system of lecture-based education hemmed in by semesters and quarters and grade-years, will transition into continuous, personalized, on-demand learning.

An old system of certifications and degrees will transition into a new system of curiosity-based learning and creativity, where anyone can use curiosity, discernment, reflection, and creativity to unlock new opportunities.

In this new AI paradigm, the pace of your learning is directly proportional to the depth of your responsibility. Anything is possible for those with a posture of personal responsibility and agency. We call this the Generative Way—using your agency to guide yourself toward the world you want to create.

Your job is to build your method, clarify your purpose, and envision your impact. When you control your world and let creativity flow through you, the external noise quiets. The signal comes from within.

This is what responsibility looks like when systems leap: not waiting for the new paradigm to arrive fully formed, but actively shaping it as it emerges. The age of AI demands this from all of us.

For more on the Responsibility process, see the Responsibility Process. There are just three keys and a shift in mindset.