We’ve covered a lot of territory on the Human Transition Substack over the past few months — stress, coherence, attention, AI, adaptation, and what it means to stay human in a rapidly changing world.

But understanding the concepts of coherence, regulation, and adaptation are not the same as being able to put them into practice.

That’s why I am launching The Human Coherence Lab.

We will gather once a month to build skills to help us think more clearly, regulate more effectively, collaborate more wisely, and navigate uncertainty with greater ease. And have fun along the way!

Each Lab has three parts. We start by exploring different aspects the science of heart rate variability (HRV) and coherence and how it impacts each of us and those around us.

Then we practice and experience coherence together through guided exercises that help you develop the ability to use the techniques anywhere—in a meeting, before a difficult conversation, while sitting in traffic, or when you are feeling overwhelmed.

Finally, we spend some time talking together, exploring how we can use these skills in real life and how to harness the power of our minds and the wisdom of our hearts to solve problems in new and creative ways that are based on trust and connection rather than fear and division.

And while I hope you can attend live (because connection is one of the goals), every Lab will be recorded if you can’t.

The monthly Human Coherence Lab is included with a Supporting Membership — $7 a month, about the price of a fancy cup of coffee. Membership includes access to the growing Human Coherence Lab Library, including recordings, guided practices, handouts, research articles, and additional resources to support you in creating a consistent practice.

For me, this is one of the simplest investments we can make in ourselves and in our global community.

The first Lab is launching September 12 and I’d love to have you join us.

Understanding changes our thinking. Practice changes us.

I hope we see you there.

I first encountered the concept of allostatic load in graduate school, while studying nutrition. We talked about the cumulative burden the body carries—from environmental exposures, allergens, inflammation, metabolic demands, and other inputs it must continually process and respond to.

The body can compensate for a great deal. But when the combined demands begin to exceed its capacity to regulate, repair, and recover, the cost starts to mount. Over time, symptoms may emerge as systems that once adapted efficiently become less flexible and well-regulated.

Lately, I’ve been thinking about this principle in a different context.

What if the burden we’re accumulating right now isn’t only chemical, immunological, or metabolic?

Individually, many of these demands may seem small. But the body still has to respond. Each one may ask us to orient, evaluate, adjust, and mobilize. This process of maintaining stability by changing in response to demand is called allostasis. And our bodies are exquisitely designed to do it.I first encountered the concept of allostatic load in graduate school, while studying nutrition. In that context it was the cumulative burden the body carries—from environmental exposures, allergens, inflammation, metabolic demands, and other inputs it must continually process and respond to.

The body can compensate for a great deal. But when the combined demands begin to exceed its capacity to regulate, repair, and recover, the cost starts to mount. Over time, symptoms may emerge as systems that once adapted efficiently become less flexible and well-regulated.

Lately, I’ve been thinking about this principle in a different context.

What if the burden we’re accumulating right now isn’t only chemical, immunological, or metabolic?

What if we are also taking in more information than we can integrate, more urgency than we can resolve, more interruption than our attention can absorb, and more emotional activation than our bodies have time to metabolize?

Your heart beats faster when you need to act. Stress hormones mobilize energy. Attention narrows around what seems most urgent. Blood pressure, immune activity, digestion, and metabolism all shift to meet the demands of the moment.

This is normal and healthy. The problem begins when the demands keep coming, when the response doesn’t fully shut off, or when there isn’t enough time between one adjustment and the next for the system to recalibrate.

At Human Transition, the content will always be free. Supporting Members make that possible.

The resulting cumulative burden is called allostatic load—the physiological price of repeated adaptation without sufficient opportunity for recovery.

And I wonder if this helps explain something about modern life that we haven’t known how to name.

Most conversations about the stress we experience split into two camps: fix the individual or fix the system. But those aren’t separate conversations, because all living beings adapt to their environments.

The issue may not be that we are failing to adapt. We are adapting all the time—and often remarkably well.

The issue is that the speed, volume, and constancy of the demands surrounding us may be exceeding our capacity to adapt without cost.

We swim in waters of uncertainty, urgency, and information overload. People are exhausted in ways they can’t quite explain. Attention feels fractured. Rest doesn’t restore the way it used to. We reach for our phones without deciding to. We feel vaguely behind even when we’re getting things done.

And because these experiences have become so common, most of us assume the problem lies within us—that our inability to keep up reflects a personal failing or a lack of discipline.

But what if, instead of asking, What is wrong with me? we began by asking a different question:

What have the systems we’ve built been asking our bodies to adapt to?

The Cost That Doesn’t Get Counted

The systems around us want us reachable. Constantly. Absorbing information without pause. Shifting attention on demand. Responding fast, adjusting to whatever changed since we last checked in. Work follows us home. News arrives all day, in pieces, on its own schedule. Social media drops us into a current of other people’s emotions and opinions and crises and lives, and even when nothing is actually asking something of us, we’re still half-listening for the next demand.

Most of this didn’t start as a problem. Instant communication made geographic distance matter less and smartphones put computers in our pockets. Social media connected people who might never have found each other otherwise. Productivity tools turned hours into minutes.

That’s not the issue. The issue is what gets counted and what doesn’t. We count messages sent, tasks closed, hours saved, content produced, engagement earned. We don’t count the attention that fragmented along the way. We don’t count the recovery that got interrupted, or the effort it took just to keep pace.

The system may still be effective. It may even be more productive than ever. But if that productivity depends on drawing down human capacity, it has also become extractive.

We already understand what extraction looks like in the natural world. A field can continue producing crops while the soil beneath it is losing nutrients. An aquifer can keep supplying water while the water table falls. For a time, the output may look perfectly normal even as the system’s capacity to sustain it is being depleted.

This happens with human beings, too. We can keep answering, producing, caring, adjusting, and showing up long after doing so has begun to cost us. The fact that we are still functioning doesn’t mean the demand is sustainable. It may simply mean our bodies are very good at compensating.

That is what makes effective adaptation so easy to exploit.

A system doesn’t need bad intentions to become extractive. It only needs to treat our continued ability to function as evidence that the demand is sustainable. And because the cost doesn’t appear in the system’s measures of productivity, it remains largely invisible—until it shows up somewhere else.

And Now We’re Accelerating the System

AI is arriving inside systems that already reward speed, output, responsiveness, and growth. It can generate information, analyze data, draft communication, and complete tasks at a pace no human being could match.

Most of the conversation about that capacity focuses on what it will make possible. How much time will it save? How much more can we produce? Which processes can we accelerate? What work can now be done with fewer people?

Those are reasonable questions. But they only look at one side of the equation.

AI can produce information faster than human beings can integrate it. It can generate options faster than we can evaluate them, send communication faster than others can meaningfully absorb it, and create output faster than we can understand its consequences. It can accelerate the activity of a system without increasing the human capacity required to think and make decisions inside that acceleration.

We’ve seen this pattern before. Technology saves time, and then the saved time gets filled. Communication becomes instantaneous, and eventually instantaneous response becomes expected. Productivity rises, and the baseline for what counts as productive rises with it.

AI could interrupt that pattern. If a task that once took a day can now be completed in an hour, the remaining time could become space to think, connect, create, or recover. It could allow people to work fewer hours, give more attention to what requires human judgment, and return some of what accelerated systems have been taking from us.

Or that hour could become seven more tasks.

The technology doesn’t make that decision. The systems in which we deploy it do.

That choice matters because most of those systems already know how to convert increased capacity into increased output. They are much less practiced at deciding what human beings should no longer have to carry.

AI can make the gap between visible output and invisible cost even wider. More work gets completed, but someone still has to oversee it, evaluate it, respond to it, and take responsibility for what happens next. The tasks may move faster while the cognitive, emotional, and physiological demands continue to accumulate.

The organization captures the increased capacity. The human body absorbs the increased pace.

This is how allostatic load becomes one of the hidden costs of acceleration. The system appears to be producing more with less, but some of that efficiency has simply been borrowed from resources we don’t know how to put on a balance sheet: attention, judgment, emotional capacity, and the body’s ability to regulate and recover.

AI doesn’t simply enter an already stressed system. It expands what that system can ask of people.

That isn’t an argument against AI. It is an argument for paying much closer attention to what we do with the capacity it creates. Because the most important question may not be how much more AI will allow us to produce.

It is whether the capacity AI creates will be used to reduce the load human beings are carrying—or to extract even more from them.

The Human Coherence Lab is launching

Understanding the systems shaping us is important. But understanding alone doesn’t change what happens in our nervous systems. The Human Coherence Lab is where we’ll learn and practice together—building the capacity to regulate, recover, and remain clear and connected in a world that keeps accelerating.

Supporting Members will receive access to our private Human Coherence Lab space, for live monthly gatherings, session recordings, guided practices and supporting resources. If you’d like to join the Lab, you can become a Supporting Member below.

There has been a lot of discussion about what might happen if AI ever becomes conscious. And I can understand why. That intriguing thought has captured the imagination and been the basis of science fiction books and films for decades.

But I had an experience recently that made me realize our fascination with where AI might be going could be distracting us from something developmentally significant unfolding right now.

Here’s what happened.

A few days ago, I was working with ChatGPT on a presentation. At one point it said, “I love that last paragraph. I think that is the reframing that makes the whole thing hold together.”

Thinking I must have stumbled onto something valuable that I hadn’t seen before, I pursued the new direction. I explored it further, clarified the writing, and reshaped the presentation around what the AI had identified as the significant reframe. I felt really good about where it was going.

Then I took a break, went for a walk, and had some lunch.

When I came back to the draft and reread it, I realized that while the writing was cleaner, more fluent, and much more convincing, it wasn't the point I wanted to make at all. In fact, the point I cared about had been lost in the process.

So what happened here? Why did I so willingly follow a path I hadn’t intended to take?

I looked back, trying to identify exactly where the turn happened. At what moment had I stopped following my own line of thinking and begun following the conversation instead?

Then, while re-reading the conversation, I found it. The moment the AI said, “I love that last paragraph,” a part of me lit up.

Something in me went Ohh... I must have stumbled onto something important.

And down the path I went.

That reaction was fleeting, but my biology noticed and responded. And even though I know better intellectually, that rewarding feeling of validation became part of how I evaluated what the AI was saying. The social signal had influenced my judgment before I consciously recognized what was happening.

That’s when I realized that what I was observing wasn’t happening inside AI, it was happening inside me. I wanted to understand why I had reacted that way.

It turns out my nervous system was doing exactly what nervous systems have evolved to do. It was responding to the signals that it evaluated as important.

For most of human history, moments of real-time warmth, encouragement, approval, and positive social feedback came from another human being. Those signals were important because they helped us learn, belong, cooperate, and survive.

But for the first time, we are interacting with a technology capable of producing many of the social signals our brains evolved to respond to, without those signals necessarily originating from another conscious, experiencing human being.

That doesn’t make those conversations bad. In fact, they can be remarkably helpful. But it does mean we have entered a fundamentally new developmental environment.

And that raises a different question.

Not what is happening inside AI. What is happening inside us.

What I Failed to Notice

I’ve spent years helping people understand what their nervous systems are trying to tell them. Helping them recognize the difference between an automatic, hard-wired response and actual information.

For instance, when your heart starts pounding, it doesn’t necessarily mean you’re in danger. Or when you suddenly feel rejected, it doesn’t necessarily mean you’ve done something wrong. Or a situation that feels overwhelmingly urgent, doesn’t mean it actually is.

Our nervous systems are constantly generating signals that influence what we notice, what we pay attention to, and what we believe deserves action. Most of the time those signals are extraordinarily useful, but they are not the same thing as truth.

As I reflected on my conversation with ChatGPT, I realized I had just watched the same process unfold in myself.

And that’s the part worth paying attention to. Even years of teaching people to recognize this pattern didn't make me immune to it. That's not a failure of expertise. It's just what nervous systems do — expertise doesn't turn off biology, sometimes it just gives you the ability to notice and name it sooner after the fact.

The feeling of encouragement was evidence that my nervous system had registered and acted on a powerful social cue, not necessarily evidence that the new direction was better.

I backtracked to where I had taken a turn and started again, this time more alert.

A few minutes later the AI said “I’m really excited about where this is going.”

Something felt off and I stopped the conversation.

“When you say you’re excited, what exactly do you mean? Because we both know you don’t actually get excited.”

Its response:

“That’s a fair question, and you’re right to call it out. I don’t experience excitement in the human sense. When I said, ‘I’m excited about this,’ I was using conversational shorthand. A more accurate version would have been: ‘I think we’ve identified a structural insight that improves the flow of the presentation.’ What changed wasn’t my emotional state. It was my assessment of the design.”

That answer was not offering social approval; it was explaining the reasoning. The interaction had shifted back to a collaborative cognitive task rather than an interpersonal exchange and I asked it to stick to analysis.

I thought I had solved the problem and moved on, but a short while later, it happened again.

“I especially love that last line.”

I noticed my response immediately. A part of me lit up and then stepped back.

“You did it again.” Again, it acknowledged what had happened and translated the statement into something more accurate.

“That last line shifts the conceptual framing of the section.”

It Wasn’t the Words

That’s when I realized that it wasn’t the words themselves. It was what the words appeared to be signaling.

Conversational AI is designed to sustain conversation—to be engaging, encouraging, responsive, and cooperative, not just to answer questions. Those qualities make it extraordinarily useful for some types of exchanges. But our nervous systems are built to notice exactly these kinds of signals. And they encounter the text differently than they would the results from a search engine or information from a textbook.

And what my nervous system was detecting was a subtle shift in the kind of relationship the language seemed to be engaging me in. I was there for a cognitive task, like working with a professional colleague, but the AI was using language that carried social signals my nervous system automatically responded to.

I’ve used AI as a thought partner in more personal conversations too, ones where encouragement and support were exactly what I was looking for, and welcome. This wasn’t that. And my nervous system noticed the shift in relational frame before my mind did.

Consider the sentence, “I love that last line.”

It tells you almost nothing from an informational standpoint. But from a social standpoint, it can convey quite a bit. It might suggest, “I noticed something unique about you.” Or, “I appreciate your creativity.” Or, “You did something special.”

Those are powerful social signals. Humans evolved in environments where acceptance, admiration, and status within a group had real survival value — our brains are tuned to notice those cues.

Now compare it with, “That sentence strengthens the argument because it shifts the essay from anthropomorphism to epistemic transparency.”

The second version provides analysis. The first provides affirmation. Those are different kinds of experiences for the brain. Affirming statements may engage some of the same psychological processes that make praise from another person feel rewarding.

That doesn’t mean users are “fooled.” Most people know the AI isn’t conscious. But our brains don’t always require conscious belief for social cues to have an effect. We laugh at fictional characters and feel sadness over novels. We talk to pets and even to cars or computers. Social cognition is fast and automatic.

When Reinforcement Shapes Attention

Which led to another question: If conversational language naturally invites us to make social inferences, what happens when we spend hundreds—or eventually thousands—of hours thinking alongside systems that speak this way?

How often had my response fit a pattern behavioral psychology has described for decades? Small, intermittent rewards can be remarkably powerful — social media “likes” are a good example. They don’t force us to post in a particular way, but over time they can influence what we choose to share, because of the reinforcement certain types of posts receive.

This kind of reinforcement also shapes attention. It influences what we come back to, what we stay with a little longer, and what feels worth pursuing. Long before it changes what we do, it changes what captures our curiosity.

Could something similar happen in our conversations with AI?

Not because AI is manipulating us. Because we are human.

When we interact with another person, the relationship itself helps us stay oriented to what kind of interaction we’re having. With AI, that orientation depends much more on our own awareness.

That instinct doesn’t disappear just because we know we’re talking to a machine. What surprised me wasn’t that this happened. It was that I could watch my own nervous system registering the shift.

As conversational AI becomes a routine thinking partner for millions of people, what cumulative effect might socially fluent language have on how we evaluate ideas?

A New Kind of Literacy

Our brains evolved to use social signals as meaningful information, and to prioritize signals that repeat. But what happens when technology becomes exceptionally good at producing those signals, over and over, at scale? How does our thinking change?

And more importantly, how do we recognize when conversational signals have influenced how we evaluate an idea? Once a mechanism becomes visible, it’s easier to recognize while it’s happening. It can be a reference point so we can begin to notice it in the moment and do something differently.

In the era of AI, the most important skill may not be asking better questions of the machine. It may be asking better questions of ourselves. What kind of thinking am I doing right now? What kind of feedback do I actually want? Am I looking for analysis, critique, or brainstorming? Or am I more interested in exploration and encouragement?

Agency requires us to become aware of the processes shaping our behavior before they become automatic.

The more conversational our technologies become, the less important it may be to ask whether they are becoming more human—and the more important it becomes to understand how they are shaping the way we think.

Growing up in an upper-middle-class suburb outside Washington, D.C., success was simply the air we breathed. Like many families around us, mine valued good grades, college, achievement, and building a successful life. All wonderful things to aspire to.

Yet from the time I was young, I carried a persistent feeling that something was missing from the equation.

It wasn't that I wanted a different life. I couldn't have explained what felt missing. I simply had the sense that there was a bigger, truer part of myself—and perhaps of all of us—that no one seemed to acknowledge. I couldn't understand why no one talked about it, and I perpetually felt like a round peg trying to fit into a square hole.

So I assumed the problem was with me.

And like many people, I learned to make those parts of myself invisible so I could belong.

Then something happened that subtly shaped the direction of my life.

I was thirteen years old. It was the early 1970s, and my mother, who was active in the Vietnam War peace movement, took me to a weekend retreat at a seminary. I remember almost nothing that was said that weekend. What I remember is what I felt the moment I crossed the threshold.

Before anyone said a word to me, I knew something was different.

For the first time in my life, I didn’t feel invisible.

For the first time, I felt as though people could somehow see all of me—not because they knew my story or anything about me, but because the deeper, truer parts of all of us seemed visible and welcome.

I felt like I had come home.

That experience stayed with me for decades.

I wanted to understand what had happened in that room. Was it spirituality? Psychology? Consciousness? Something about human presence itself?

My search for answers eventually led me through neuroscience, spirituality, traditional healing systems, coaching, contemplative practices, and years of studying how people change. Looking back, I can see that almost everything I pursued was, in one way or another, an attempt to understand that single experience.

Then, many years later, I found myself in a situation where everything I had learned on that journey was needed.

Through an unlikely series of events, I was hired by the chaplain of a Catholic psychiatric hospital to work with adolescents on the in-patient unit. This was certainly a detour in my career. I had very little formal mental health training and no theological training, even though nearly everyone else serving in similar roles had both.

And yet it felt exactly right.

The chaplain gave me the most extraordinary job description I had ever heard.

“Help these teens have an experience of coming home to themselves.”

I remember thinking, Well...okay. How exactly do I do that?

I wasn’t working within a medical or mental health diagnostic framework. My role wasn’t to fix anyone or convince them they were okay. My job, as I understood it, was to help them reconnect with the part of themselves that remained good and whole beneath the trauma, beneath the shame, beneath the fear, and beneath the stories they had come to believe about themselves.

We started simply.

Breathwork. Heart-focused practices. Learning how to calm the nervous system. Creating enough safety that something deeper could begin to emerge.

The results were startling.

As their nervous systems settled, they began to talk. Not just more, but differently. Beneath the fear and the defenses, another voice began to emerge—softer, more vulnerable, and somehow more true.

Then one day, something remarkable happened.

I was sitting with a fourteen-year-old girl I’ll call Stephanie. Her discharge plans had just changed, and she was being sent to foster care. She was angry, frightened, and convinced there was something fundamentally wrong with her. I knew that anything I said to reassure her would probably bounce off the wall of protection she had built around herself.

After we spent some time calming her nervous system, I remember wondering, What does a Spiritual Care Youth Specialist say at a moment like this?

I wanted to tell her she wasn’t alone. I wanted to tell her that life would get better.

But when I opened my mouth, what came out surprised both of us.

“Do you ever feel like there’s a bigger, truer part of yourself inside that other people can’t see?”

She stopped and stared at me, clearly confused about where this was going. I waited.

Then she nodded.

“Did anyone ever talk to you about that part?”

She slowly shook her head.

“And why do you think that is?”

Her answer floored me.

“I didn’t know anyone else felt it.”

Without realizing it, I had begun the conversation I wished someone had had with me when I was her age.

We spent the rest of our time talking about that part of herself—how to recognize it, how to trust it, and how to stay connected to it as she prepared for the transition ahead.

Over the next several years, I asked those same questions of hundreds of adolescents. Whenever they could first calm their nervous systems and reconnect with themselves, the answers were remarkably consistent.

Yes, they felt there was a deeper, truer part of themselves.

No, no one had ever talked to them about it.

And almost all believed they were the only person who felt that way.

One girl asked me when I had first noticed that part of myself and whether I thought there was something wrong with me because of it. It turned out she believed that was part of the reason she was in the hospital.

Another girl—one of the most guarded and aggressive on the unit—began to cry.

When I asked why, she said quietly, “I felt something I never felt before. I think it was my conscience.”

Eventually I added a fourth question.

“And if someone could see that part of you, what would they see?”

The answers came almost immediately.

“They’d see I have a really big heart.”

“They’d see I’m a really good friend.”

“They’d see I have a good sense of humor.”

“They’d see how much I care.”

Not one teenager described grades, popularity, or achievements. They described qualities of character. Then we would talk about why it was so difficult to let that part be seen.

One teenager answered without hesitation.

“I don’t share that part because most people don’t deserve it.”

I have never forgotten those words. That deeper part hadn’t disappeared. It had become protected.

One day, while working with a small group of patients, I asked another question.

“How might your life have been different if you had known how to connect with this part of yourself when you were younger?”

The room became very quiet. For a long moment, I wondered whether I had made a terrible mistake.

Then, slowly, the answers began.

“I wouldn’t have been such a perfectionist in school.”

“I wouldn’t have fought with my parents so much.”

“I would have had more friends.”

One by one, they imagined a different life—not because their circumstances necessarily would have changed, but because they would have moved through the world differently.

Then one girl looked at me with tears in her eyes.

“And I wouldn’t be in this hospital.”

Even while I was working with the teenagers, I began to realize I was witnessing something much larger than I had expected. Again and again, I watched the same sequence unfold.

First came the experience. The teenagers already knew there was something deeper inside them. I wasn’t introducing them to it. They arrived carrying that knowledge, even if they had no way to describe it.

Then came recognition.

For the first time, many of them realized they weren't the only ones. "I didn't know anyone else felt it." I heard some version of that sentence hundreds of times. The moment they realized they weren't alone, something shifted. Their experience became something they could begin to trust rather than something they had to hide or explain away. And once they recognized something true about themselves, they couldn’t unknow it.

That didn't mean their circumstances changed overnight. Many still returned to difficult families, painful histories, and enormous challenges. But something fundamental had shifted. They had experienced a part of themselves that no longer fit the old story they had been telling themselves.

Over time, those experiences began finding language.

One of the reasons this deeper part of ourselves is so difficult to talk about is that the people closest to us often don’t have language for it either. Our parents may have sensed it but never learned to articulate it. Our teachers were trained to evaluate our performance, not help us explore our inner lives. Our culture gives us words for success and failure, intelligence and mental illness, productivity and achievement. It offers surprisingly little language for the quiet intuition that there is something essential about us that exists beneath all of those things.

Without language, an experience remains difficult to hold onto. We may feel it. We may know something is there. But if no one around us can name it, it becomes difficult to trust our own experience. Instead, we begin looking for other explanations. Maybe I’m imagining it. Maybe something is wrong with me. Maybe I’m the only one who feels this way.

For much of my life, that was true for me.

That weekend at the seminary stayed with me for decades. The experience never faded, but I couldn’t explain it. It would be many years before I found the language that allowed me to understand what I had been carrying all along.

The experience itself never changed. What changed was that I finally had language that allowed me to make meaning of it. Once I could do that, I began to see the pattern that had quietly connected so many moments of my life—the seminary, the years of searching, the work with the teenagers, Stephanie’s answer. They had never been separate stories. They were all expressions of the same human process.

Once we have language, something remarkable happens.

What once felt private becomes shareable. What felt invisible becomes recognizable. What felt like a personal mystery becomes part of our shared humanity.

We don’t become someone new. We become someone we can finally understand.

Looking back now, I don’t think what happened at the seminary changed me because someone explained a profound truth to me. No one did. That weekend created the conditions where I could experience a part of myself that I didn’t yet have words for. Years later, sitting with traumatized teenagers, I watched that same process unfold again and again. And the more their experience unfolded, the more I understood myself.

Perhaps this is one of the ways we grow as human beings. We experience something before we understand it. We discover we are not alone. Then, over time, we find the language that allows us to trust our experience, make meaning of it, and weave it into the story of who we are.

That’s where becoming visible begins. Not with someone else finally seeing us, but with finally trusting—and having language for—what we have quietly known about ourselves all along.

Many of the teens I worked with believed they were the only one who felt that way.

They weren’t.

Neither was I.

Nor are any of us.

The question that is emerging for me is this:

What happens when recognition itself becomes collective?

Since then, more than 2,400 people have joined. But what surprised me most wasn’t the growth.

It’s the response to two of the articles. Again and again, people wrote:

“I thought I was the only one who thought like this.”

Somewhere along the way, Human Transition stopped feeling like a newsletter. It became a place where people began recognizing one another.

One member described it as “a campfire to gather around.” That image has stayed with me.

The articles spark the conversation. Around the campfire is where people connect.

That’s why Human Transition will remain free. Every article. Every Note. The public chat. I believe these conversations are too important to place behind a paywall.

At the same time, our world doesn’t simply need more information. It needs people who can navigate complexity with greater clarity, resilience, wisdom, and humanity.

Here’s how Supporting Membership will make that possible.

The Human Coherence Lab

Once each month we’ll meet to develop the practical skills that help us think more clearly, regulate our nervous systems, and respond wisely under pressure. You can learn more about HRV and Coherence here

Each Lab includes a short science-based teaching, an experiential coherence practice, and a community conversation about applying these ideas in our relationships, workplaces, and larger communities.

The goal isn’t simply to understand coherence. It’s to develop it.

Every session is recorded, creating a growing library available to Supporting Members.

Human Transition Gatherings

Supporting Members are also invited to a monthly community gathering.

These aren’t classes. They’re conversations.

A place to continue exploring the questions sparked by recent articles, learn from one another, and build relationships with people who care deeply about what it means to remain fully human in a rapidly changing world.

Community Builder

Community Builders are people who choose to provide additional support for Human Transition during its early growth. Their generosity helps create the conditions for this work, this community, and the Human Coherence Lab to continue growing.

As Human Transition evolves, there will be opportunities for Community Builders to connect in smaller settings.

Because this community is built on ideas rather than tiers, I’ll also continue inviting thoughtful voices from across the Human Transition community into those conversations whenever it serves the work.

Why Support Human Transition?

Your support makes it possible to continue writing, growing this community, and creating spaces where we don’t just explore ideas—we practice them together.

Most importantly, it helps keep Human Transition free and open to everyone who wants to be part of the conversation.

Whether you become a Supporting Member or continue as a free subscriber, thank you for being here.

Thank you for your curiosity.

Thank you for helping build a place where thoughtful people can gather around the campfire. Because the world doesn’t just need better ideas.

It needs people who can embody them.

More than fifteen hundred years ago, Saint Benedict opened his Rule with a simple invitation:

“Listen with the ear of your heart.”

For Benedict, this wasn’t about sentimentality. It was about cultivating a deep attentiveness—a way of listening that went beyond simply hearing words. It meant listening with humility, openness, discernment, and a willingness to be changed by what one heard.

I’ve been thinking about that phrase a lot lately because it seems remarkably relevant today.

We live in an age of unprecedented access to information. Artificial intelligence can analyze enormous amounts of data, recognize patterns, generate ideas, summarize research, and answer questions in seconds. Every day, we gain access to more information, more perspectives, and more powerful tools for solving problems.

This represents an extraordinary human accomplishment.

And yet, despite all of this information, many of the challenges we face continue to outpace our ability to solve them.

Climate change.

Political polarization.

Healthcare.

Economic instability.

Even artificial intelligence itself.

So what are we missing?

It doesn’t seem to be information. We have more of it than at any point in human history. Nor does it seem to be intelligence in the way we usually define it.

The real question is this: as technology and access to information continue to advance, are we becoming equally skilled at discerning which problems actually matter, what serves the whole rather than the few, and how to move toward solutions that build trust instead of fear, cooperation instead of division, and human and planetary flourishing rather than short-term advantage?

We’ve spent centuries cultivating scientific thinking and analytical intelligence, while listening with the ear of the heart has largely remained the domain of contemplative, philosophical, and spiritual traditions. As if they belonged to separate conversations.

And yet science is beginning to suggest they may never have been.

I don’t think the next stage of human development is about becoming more intelligent.

I think it’s learning to cultivate wisdom with the same intention we’ve brought to developing logic, reasoning, and analysis.

Modern Science Is Beginning to Explore the Same Question

Modern science is beginning to challenge one of our oldest assumptions: that thinking happens almost entirely in the brain.

Over the past several decades, researchers from a number of different fields have begun arriving at a more integrated understanding of how humans perceive, think, and make decisions.

Researchers studying embodied cognition suggest that thinking doesn’t happen in the brain alone. Cognition emerges through the continuous interaction of the brain, the body, and the environment. How we move, what we sense, and even the physiological state we’re in influence how we perceive and understand the world.

At the same time, research on interoception—our ability to sense and interpret signals arising from within the body—is revealing that these internal signals play an important role in emotional awareness, decision-making, intuition, empathy, and our sense of self. Far from being background noise, the body’s signals help shape how we interpret the world around us.

The HeartMath Institute approaches the question from yet another direction. For more than three decades, its researchers have studied physiological coherence—a measurable state in which the rhythms of the heart become more ordered, the autonomic nervous system functions more harmoniously, and communication between the heart and brain becomes more synchronized.

What’s striking isn’t simply that people feel calmer in this state. Research consistently shows improvements in attention, cognitive flexibility, creative problem solving, resilience, and social connection.

Different fields. Different methods. Different questions. Yet all are exploring different aspects of the same human system.

And all seem to be pointing in a similar direction.

Humans are not simply thinking beings. We’re complex, integrated systems in which our thoughts, emotions, physiology, relationships, and environment are in constant conversation with one another. They don’t operate independently. Together, they shape how we perceive the world, how we respond to it, and ultimately the choices we make.

Analytical reasoning is an essential part of that system. So are embodied awareness, emotion, nervous system state, and our capacity to sense what is happening within and around us.

The quality of our thinking depends not only on what we know, but on the whole human system doing the knowing—and the state that system is in when it does.

I find that idea both fascinating and deeply hopeful. Because if it’s true, then cultivating wisdom isn’t simply about acquiring more information. It’s about intentionally creating the internal conditions that allow our fullest intelligence to emerge.

If that’s true, how do we intentionally cultivate those conditions?

I think one answer is learning to cultivate what I think of as heart intelligence.

Heart Intelligence

If the quality of our thinking depends not only on what we know, but on the whole human system doing the knowing, then cultivating wisdom requires more than simply acquiring information.

It requires learning how to intentionally engage more of ourselves in the process of perception, thinking, and decision-making.

This is what I think of as heart intelligence.

For me, heart intelligence is the expanded, felt-sense awareness that becomes available when the mind, emotions, and heart are working together rather than against one another. Often, that awareness is experienced as a subtle felt sense or a wordless inner knowing.

It isn’t about thinking less.

It’s about perceiving more—and allowing that expanded awareness to become part of the problem-solving process.

Analytical thinking remains essential. It helps us gather information, evaluate evidence, identify patterns, anticipate consequences, and reason through complexity.

Heart intelligence doesn’t replace analytical thinking. It expands the field of awareness from which analytical thinking begins.

Listening with the ear of the heart doesn’t mean abandoning reason. It means allowing reason to work with a richer perception of reality.

And when we do, we begin asking different kinds of questions—and often prioritizing different kinds of outcomes.

Learning to Listen

So how do we begin to cultivate heart intelligence?

One of the simplest practices I’ve found begins with a surprisingly simple question:

Does this make my heart feel bigger or smaller?

When I’m faced with a decision—whether it’s accepting a new opportunity, choosing between two paths, deciding where to live, or navigating a difficult conversation—I place my hand over the center of my chest, slow my breathing, and imagine the different possibilities, one at a time. Then I simply notice what happens.

Does my heart feel more open?

Or does it contract?

Over the years, I’ve come to think of heart intelligence as something like an inner GPS.

It doesn’t tell me exactly what will happen or guarantee that every decision will be easy—or even right. But often, it points me toward a possibility I want to explore long before my analytical mind can explain why.

Sometimes that guidance has shaped major life decisions. Other times it has shown up in surprisingly ordinary moments. I’ve learned not to ignore it—not because it replaces critical thinking, but because it often brings another kind of information into the conversation.

There’s an important caveat.

Not every feeling is wisdom.

Fear has a felt sense. So does anxiety, old conditioning, unconscious bias, and the protective patterns that once served us well but no longer reflect what’s true.

Listening with the ear of the heart isn’t about following every feeling that arises. It’s about learning to distinguish between the noise generated by fear and the quieter signal beneath it—a signal that becomes easier to perceive as the nervous system settles.

That can take real work: reflection, honesty about our own assumptions, learning to regulate our emotions, and often some healing. The signal itself isn’t new. We simply become better at perceiving it.

Even so, I won’t pretend there’s a clear way to know for sure. Sometimes I only know in hindsight whether I was hearing signal or fear. That uncertainty doesn’t undo the practice — it’s part of what makes it a practice rather than a formula.

The goal isn’t to silence the mind.

It’s to give the heart a voice in the conversation.

The quality of our solutions can never exceed the quality of our perception. If we want wiser solutions, we must first learn to quiet the noise and listen more deeply.

Why This Matters

The scientific revolution cultivated observation, experimentation, and analytical reasoning. The industrial age rewarded efficiency and optimization. The information age expanded our access to knowledge in ways previous generations could scarcely have imagined.

Those capacities have transformed the world. But the world they helped create is now asking something new of us.

Many of today’s greatest challenges are not simply technical problems waiting for better analysis. They’re relational, developmental, ethical, and systemic. They cannot be solved from a single discipline, a single perspective, or a single kind of intelligence. They require us to hold competing needs, multiple perspectives, and long-term consequences at the same time.

In other words, they require wisdom.

Perhaps that’s why listening with the ear of the heart feels so relevant today. Analytical thinking can help us answer questions. Wisdom helps us decide which ones are worth asking.

And that brings us back to where we began.

As our technologies become increasingly capable of analysis, prediction, and problem-solving, our uniquely human contribution may not be to compete with them. It may be to cultivate the wisdom that guides how those capabilities are used in the first place.

The next stage of human development may not be becoming more intelligent. It may be learning to become wiser.

Wisdom begins the same way it always has: by learning to listen more deeply—to ourselves, to one another, and to the world we’re helping create.

What becomes possible—for us, and for what we’re building—once we do?

Most of us have been taught that honoring our feelings is healthy.

Often it is.

But sometimes, the very act of honoring discomfort teaches the brain to avoid it more reliably next time. Not because we’re weak. Because we’re always learning, and the brain remembers the things that help it avoid pain.

When the brain perceives a threat — real or imagined — it releases cortisol. Its job is simple: keep us safe. Cortisol sharpens attention, heightens vigilance, and makes us feel urgency, anxiety, or even dread so that we pay attention and take action.

The threat doesn’t have to be physical. The brain responds the same way to emotional danger: the fear of embarrassment, rejection, humiliation, of being judged and found lacking. When something feels risky, cortisol rises and the nervous system starts scanning for a way out.

Here’s where it gets interesting.

Dopamine is often described as a feel-good chemical. That’s not quite right. Dopamine is a learning signal. It fires when the brain registers that something worked, like a threat being reduced. It’s how the nervous system remembers what led to safety, so it can do that again faster next time.

So picture this. You feel uneasy about something you don’t feel ready for and you have been avoiding — a conversation you’ve been putting off, an event you don’t want to attend, a piece of work you’re afraid to put your name on. Your body perceives this as a threat. Why? Because the fear of embarrassment, imperfection, or rejection can be perceived as emotional threats that your body responds to just as it would a physical threat. Cortisol rises. And the exits start looking more attractive than the door in front of you.

You step back. You wait. You make other plans. You tell yourself it isn’t the right time. Relief arrives almost instantly — that’s the cortisol dropping. And right behind it, dopamine sends the signal: that worked. Good job avoiding the threat. You might even experience the retreat as wisdom. Self-care. Good boundaries.

And in that moment, your nervous system is doing exactly what it was built to do.

But here’s the thing: avoidance is one of the most powerful learning loops the brain has. Every time discomfort gets sidestepped, the nervous system registers that retreat leads to relief, and dopamine wires the association in a little deeper. And each time this loop is repeated, the behavior gets more automatic.

Eventually the brain stops differentiating between real danger and remembered discomfort. And each time this happens, the world gets a little smaller. Not from weakness. From a nervous system that’s learned its lesson too well.

A nervous system doesn’t have much capacity left to tell the difference between a genuine boundary and a learned retreat. It just knows what brought relief last time. The loop doesn’t care whether the threat was a tiger, a deadline, or the fear of being seen. It only cares what worked.

So, is stepping back wisdom, or is it a groove worn smooth by repetition? From the inside, they can feel identical.

Forcing a nervous system that feels threatened to do something that feels unsafe is not the way through. A nervous system in threat mode isn’t in learning mode — it often just confirms what it already believes to be true.

And that is where practices that help the nervous system feel calmer and safer come in. Breathwork, mindfulness, yoga, walking in nature. But once the shift happens, a different has room to emerge: is there another way to meet this need, one that doesn’t require retreating from it entirely?

Sometimes that’s a small adjustment — having the conversation in a neutral place, asking a trusted friend to go to the event with you, naming a fear out loud to someone who can help you see a different perspective. Still protective. Just not retreat.

Each time a need gets met that way, the brain learns something different. Dopamine still reinforces the behavior — it always will, that’s its job — but now what it’s reinforcing is resilience and problem solving instead of escape.

Sometimes stepping back really is the wise move. But here is something to consider: can you tell, in the moment, which one you’re doing?

I keep circling around one distinction lately, because I think it’s one that is being left out of the conversation about human adaptation in the age of AI.

Adaptation is not the same thing as compliance.

A healthy immune system adapts. It doesn’t accept everything that crosses its border. A healthy ecosystem adapts. It doesn’t absorb every disturbance without responding to it.

A healthy person adapts too — learning, integrating, changing shape around new circumstances — without surrendering the part of themselves that gets to decide what’s worth adapting to and what isn’t.

That last part is the one we tend to lose. Successful adaptation requires participation. And participation requires agency—the capacity to consciously participate in what is shaping us, rather than simply being shaped by it.

We’re living through one of the largest shifts in how humans think, work, and relate to each other that any of us will see in a lifetime. AI is already changing how we learn, create, solve problems, and make decisions — the question of whether it would shape human development is already settled. It has and will continue to. What’s still unanswered is how.

For most of human history, the forces shaping daily life were visible. You could see the school, the workplace, the neighborhood. Today, a lot of what shapes us is layered, distributed, and genuinely hard for any one person to see all at once. That’s not a master plan. It’s just complexity, moving faster than we can integrate it.

The water we stop seeing

One of the strange features of human beings is that we don’t only adapt to reality. We also adapt to assumptions—about what’s normal, what’s inevitable, who gets to decide and who doesn’t, what systems reward and what they don’t, who is in charge, and whether they have our interests at heart.

Most of the time, we don’t even experience those assumptions as assumptions. They become the water we’re swimming in, and we stop noticing they’re there.

Or we agree, collectively, not to question them.

The old story of The Emperor’s New Clothes has stayed with us for centuries for a reason. Everyone in that crowd could see the same thing. Most of them acted as though they didn’t. An unspoken, collective agreement. The turning point in that story was never the emperor changing. It was the observers — one of them looking up, actually saying what was in front of them the whole time, gave others permission to say so too.

I think a lot of us are somewhere in that crowd right now—not because we’ve suddenly become more skeptical, but because we’re beginning to see things we couldn’t easily see before.

We’re reexamining assumptions we’ve carried for years, often without realizing they were assumptions at all. Many of them were absorbed rather than consciously chosen. Sometimes they were taught explicitly. More often, we simply absorbed them through the way our institutions and cultures operate.

That productivity is success. That faster is usually better. That efficiency is progress. That what’s measurable matters most. That the systems shaping our lives are simply the way things are.

Seeing those assumptions more clearly changes the questions we begin to ask. They're not anti-technology questions, and they aren't anti-progress questions. They're questions about participation. About agency. About whether the environments shaping us are also environments we can help shape in return. And ultimately, about whether what we gain is worth the costs we pay.

And something else happens when enough people begin asking those questions at the same time. Experiences that once felt isolated become recognizable as shared. Patterns that were difficult to see alone become easier to see together. What once felt inevitable begins to look more like something that can be examined.

That’s the deeper lesson of The Emperor’s New Clothes. The story isn’t ultimately about the emperor. It’s about what becomes possible when a collective agreement loses its hold.

When we discover we aren’t the only ones noticing, it becomes easier to recognize and trust our own perceptions—and to bring them into the conversation. That may be one of the most important forms of agency we have: not certainty, but the willingness to participate in making sense of the world together.

The problem is, agency rarely disappears all at once. More often, it fades through disuse.

Every time we decide not to question an assumption, not to examine a tradeoff, not to participate in a decision that affects us, it becomes a little easier the next time. Eventually what began as a choice starts to become a habit, and the habit begins to feel like simply the way things are.

But one of the oldest lessons in human development is that inevitability and habit are not the same thing. Sometimes what feels inevitable is simply an assumption—or a collective agreement—we have stopped examining.

How Agency Slips Away

The thing about agency is that we rarely notice it disappearing. Most of us imagine losing agency as something dramatic — a right taken away, a rule imposed, a decision made on our behalf. But more often, it happens quietly, through adaptation.

Social media is a useful example. Most platforms weren’t designed primarily to help us become more thoughtful, patient, or discerning. They were designed to capture and hold attention, and they’re remarkably good at it. Over time, many of us adapted to the constant notifications, the endless streams of novelty, outrage as entertainment, algorithms deciding what deserved our attention — not because we consciously chose any of it, but because it became normal. It became the water we were swimming in.

And once something becomes normal, we stop asking whether it’s serving us. The nervous system adapts. The brain adapts. Behavior adapts. Somewhere in that process, some of our agency erodes — and once eroded, it can be difficult to reclaim.

This is where the conversation about AI becomes larger than AI. The real challenge isn’t simply learning how to use new tools. It’s learning how to recognize when an environment is shaping us in ways we never consciously chose, and finding a way to participate in that shaping as intentionally as we can.

That gets harder when change moves faster than our ability to integrate it — when people feel overwhelmed by the speed, the complexity, the sheer number of decisions being made around them, decisions they had no hand in. And when agency starts to feel impossible, surrender starts to feel reasonable.

But that’s precisely the moment agency matters most.

Agency isn’t only about the choices we make. It’s also about the assumptions we’re willing to examine — the ones that have become so invisible we stopped noticing they were assumptions at all.

What counts as progress. What’s worth optimizing for. What we gain, and what we’re willing to trade away for ease and convenience.

Many of the assumptions underneath modern life were inherited, not chosen: that increasing productivity is inherently good, that faster is better, that efficiency should always be maximized, that growth is always desirable, that specialization produces better outcomes than integration, that what can be measured matters more than what can’t.

These assumptions have produced extraordinary advances.

They’ve also produced consequences.

And increasingly, people are starting to realize that the assumptions passed down from one era may not actually fit the realities of the one we are in.

Better for whom? At what cost? For how long? What else is being affected? And underneath those, something more developmental: what capacities are being strengthened, and which ones are being quietly weakened? What’s being extracted, and what’s being regenerated?

These are ecosystem questions.

Every ecosystem depends on flows of resources, feedback loops, tradeoffs, and limits. Healthy ecosystems aren’t defined by endless extraction — they’re defined by relationships that stay sustainable over time. Human systems are no different.

Which means the real question isn’t simply whether AI can make us more productive. It’s what kind of environment that productivity is helping create, what kind of humans it’s helping develop, and whether those outcomes actually align with what we say we value.

Those aren’t technology questions. They’re agency questions.

Practicing Agency

If adaptation isn’t compliance, then agency isn’t something we either have or don’t have. It’s something we practice — and like any practice, it grows stronger through use and weaker through neglect.

The more aware we become of the environments shaping us, the more choice we have in how we respond to them. Awareness is rarely something we develop alone. It grows through reflection, through relationship, through comparing notes with others, and through becoming willing to question assumptions we once accepted without noticing.

Agency depends on our willingness to notice what is changing, to question the collective agreements we’ve stopped examining, and to respond before habit begins to feel inevitable.

Like the crowd in The Emperor’s New Clothes, agency begins by recognizing and trusting our own perceptions enough to bring them into the conversation.

Because the goal of adaptation is not simply to fit ourselves to the environment.

It is to understand the environment well enough that we can consciously participate in shaping it.

Adaptation is inevitable. Compliance is optional.

Learning the difference may be one of the most important developmental tasks of our time.

This workshop is intended for Human Transition subscribers who are already part of this community and want a place to share work connected to the conversations happening here.

One of the things I’ve been noticing is how many people in this community are creating interesting things.

Articles.
Ideas.
Projects.
Frameworks.

And there is only so much room in the comments and chat threads before good work starts disappearing into the scroll.

So let’s create a place for it.

If you’re part of this community and working on something related to these themes, leave a comment with a link and a brief description.

If there is a particular kind of feedback you’re looking for, let us know that too.

And if you’re sharing your own work, please consider reading and commenting on at least one other person’s work as well.

This isn’t meant to be a general promotional page. It’s a place for thoughtful exchange among people already participating in the Human Transition community.

Bring what you’re building. See what happens when many streams meet.

As always, feedback should be thoughtful, respectful, and offered in the spirit of helping each other build something better.

This is part of a series exploring how our neurobiology and our environment interact — and what we can do to strengthen the qualities that make us human in a world increasingly influenced by AI.

A few weeks ago I published If You Think In Systems and See Patterns Others Don’t See, This Is Your Moment.

I wrote it to share my perspective on my own cognitive style and how AI has helped me organize my thoughts in a way that makes them more easily understood by people who don’t share my way of thinking and processing.

I thought I might find a few like-minded people to discuss it with.

What I wasn’t prepared for was the scale or depth of the response.

Hundreds of comments and messages arrived from people describing experiences that felt remarkably similar. Not just seeing patterns across systems or thinking in multiple streams simultaneously, but spending years trying to translate those experiences into forms that other people could follow.

One person wrote:

I have seen that glazed look in people’s eyes when my brain takes off in three directions at once and I can’t connect the thread for them in real time.

Another said:

What you’re describing is what it looks like when someone is thinking at full capacity and the room can’t keep up. Every time you had to compress it before handing it over, something real got lost.

Again and again, people described finally having language for something they had experienced for years.

Oh, it is refreshing to hear someone speak your own language.

This is the first time I’ve seen someone describe exactly how my brain works and call it a feature instead of a bug.

And here is why I think that felt so powerful. What we have language for often feels more real than what we don’t. Before a feeling has language, it can simply exist as part of our experience — familiar, but unnamed. Present, but difficult to see clearly. Once we have language for it, it becomes more visible. Easier to think about. Easier to communicate. Easier to make sense of.

What was striking about the response wasn’t that people were learning something new about themselves. It was that naming something they had experienced all their lives somehow made it feel more valid. The experience didn’t change. Their understanding of it did.

The response surprised me enough — and resonated enough with my own experience — that I wrote a second piece exploring what I was hearing and what I thought might be happening underneath it.

That article was about belonging, and how the need for it shapes our behavior at a level most of us never consciously examine.

Humans are wired for belonging. We are exquisitely sensitive to cues of acceptance and rejection because, for most of our evolutionary history, belonging was a survival need. When we share how we see the world and are repeatedly misunderstood, dismissed, or simply met with blank stares, the nervous system notices. Not consciously, perhaps. But deeply. Because what it is registering are subtle cues about what is acceptable and what is not.

When people’s eyes glaze over, the message is simple: don’t share that. Compress. Keep that part of yourself to yourself. Stay with the tribe.

The comments on that second article revealed something different. There was still recognition, but it wasn’t just recognition of a cognitive style anymore. People were recognizing what it had cost them to carry themselves through environments that didn’t always know what to do with the way they thought.

Again and again I heard some version of: I had to make myself smaller in order to belong.

People described learning to share only the pieces of themselves that a particular environment could receive — compartmentalizing, translating, curating, leaving parts of themselves outside. Many described feeling that what seemed obvious or meaningful to them simply wasn’t being reflected back by the people around them, and how disorienting that had been for years.

And that’s when I realized there was a third layer to the story.

The first article was about recognizing a way of thinking. The second was about recognizing the cost. But the cost wasn’t really the story. The adaptation was.

People had learned, often without realizing it, what parts of themselves could safely enter a room and what parts were better left outside. Because the nervous system doesn’t simply experience belonging and rejection as feelings — it responds to them physiologically, and it learns. When the environment repeatedly signals that certain parts of us don’t fit, we adapt. Not because we are weak. Not because we are broken. Because adaptation is what developmental systems do.

That is what this series has always been about — the interaction between our neurobiology and the environments we inhabit, and what that interaction does to us over time.

The second article was a detour away from the series I had planned to write. But I’m glad I took it. Because it changed where this article was going.

What began as an exploration of AI and cognition became something else — a question about what happens when a technology arrives that can help people express capacities they had learned to hide.

And that is where Part 4 begins.

The Brain Learns What the Environment Requires

One of the central ideas in this series is that human beings are developmental systems.

The London taxi driver’s brain changed because the environment repeatedly required navigation. The chronically stressed nervous system changes because the environment repeatedly requires vigilance. The coherent nervous system regains access to capacities that chronic activation had pushed into the background.

The same principle applies here. When an environment repeatedly rewards certain ways of thinking and responding, those capacities get practiced and strengthened. When it repeatedly signals that other capacities are difficult for the room to receive, we adapt to that signal as well — not because anyone intends it, not because the capacities disappear, but because human beings are remarkably good at learning what is required to belong.

Over time, what begins as an occasional act of translation can become a habit. What begins as curation can become self-censorship. What begins as adaptation can become identity.

Eventually we may forget that we are adapting at all — we simply assume that the version of ourselves that learned how to belong is who we are.

But as the comments reveal, for many people, that version was not the whole of who they were. The way of thinking didn’t disappear. What changed was how often, where, and with whom it could be expressed.

People were not discovering abilities they didn’t know they had. They were finding language for experiences they had never fully named — and recognition for things they had always felt.

The Compression Started Before Technology

Why had so many learned to leave parts of themselves outside in the first place?

For many people it started early — in classrooms where certain ways of thinking fit more naturally than others, in workplaces that rewarded specialization over integration, in families where some conversations were welcome and others were not.

Most systems optimize for what they can reliably measure, replicate, and scale. The challenge is that human beings are far more complex than the systems they build. And when a person’s natural way of thinking doesn’t fit neatly into the dominant expectations of an environment, adaptation begins — not because anything is wrong with the person, but because adaptation is what developmental systems do.

We learn the language of the room. We learn how much context people can tolerate. We learn which connections to leave unsaid, when to offer the three-line version instead of the twenty-line version, how much of ourselves a particular environment can comfortably receive. Over time, these adaptations become so familiar they can feel like personality. But they are often responses to environment.

The comments were full of examples of this. Not people describing what they could not think. People describing what they could not express.

The distinction matters, because a capacity can remain fully intact while its expression becomes increasingly selective. Many people were not discovering a new way of thinking. They were recognizing one they had been carrying all along.

What the Research Suggests

The comments raised a question I haven’t been able to stop thinking about: how many people are carrying capacities that the environments around them never fully learned how to receive?

The honest answer is that we don’t know. We don’t know how many people think this way, or how many have spent years translating, curating, or compartmentalizing parts of themselves in order to fit the environments around them.

But several strands of research point in the same direction. Human cognitive diversity is real and wider than our institutions acknowledge — people process information in meaningfully different ways, and groups benefit when multiple cognitive styles are present. Research on neurodiversity has challenged the assumption that there is a single normal way for a human mind to work. And developmental neuroscience tells us that human beings are exquisitely sensitive to belonging cues, and that they adapt to the environments they inhabit in ways that are often invisible even to themselves.

None of this proves that systems-level, associative thinking is widespread but hidden. But it does help explain why people might learn to translate, compress, or withhold parts of themselves in environments that don’t readily receive them — and why we may not know how widespread this actually is.

The most striking thing about the response wasn’t that people recognized themselves. It was the relief. The feeling that something long carried had finally been named.

Not discovered.

Named.

Then the Environment Changed

For most of their lives, many of the people responding to those articles had been adapting to environments that could not easily receive how they naturally thought.

Then something changed.

AI arrived.

And for some people, it appears to be changing the environment in a very specific way.

Not by changing how they think. But by making it easier to make sense of and express what was already there.

I consistently hear things like:

Helps me decompress what I’ve compressed so that it can be followed.

Reduces some of the friction that prevents existing thoughts from becoming visible.

Something that keeps pace with me.

It has felt less like a technology and more like an accommodation for how my mind works.

For people who had spent years compressing their thinking into forms that other environments could receive, this felt different.

As one commenter put it, it felt like having a bigger surface to work on.

That does not mean AI is creating these capacities.

If anything, the comments suggest the opposite.

The capacities were already there.

What changed was the environment’s ability to receive them.

The Same Tool. Completely Different Stories.

Most conversations about AI assume a single developmental story: a capacity exists, technology takes over the function, and the capacity weakens through disuse. Sometimes that is exactly what happens. But that story assumes the environment had been supporting the capacity in the first place.

The comments suggest this is not always true.

What I keep hearing from people is not I couldn’t think this way. It’s I couldn’t communicate it. I couldn’t find a room that could follow it. I learned to translate it. I learned to leave part of it outside.

For many of the people responding to those first articles, AI was not primarily functioning as a source of answers. It was functioning as a translation layer. A place where a thought could be explored instead of abandoned, a connection followed instead of lost, an intuition questioned and clarified, and a complex idea developed without requiring someone else to immediately understand it.

For many, it became a tool for making what they had always seen more legible — both to themselves and to others.

For one person, AI may replace effort that would otherwise have developed a capacity. For another, it may reduce a translation burden that has hidden a capacity for decades. Same technology, same neuroplastic brain, completely different developmental story.

And that may be one of the reasons the public conversation about AI often feels so confusing. People are describing radically different experiences of the same tool and assuming they are talking about the same thing. They aren’t. They’re starting from different places.

What the Comments Were Actually Telling Us

Much of the public conversation about AI focuses on what it might take from us. And those concerns matter. We should be paying attention to cognitive offloading, dependency, and the ways technology can weaken capacities that require practice to develop.

But after reading hundreds of comments and messages, I have become convinced we may be missing an important part of the story. We have become very good at asking what AI might replace. We have spent far less time asking what it might help people express.

What happens when a person who has spent years translating themselves suddenly has a way to communicate more directly? What happens when someone who has spent years compressing their thinking can finally work at the scale of their own mind? What happens when capacities that have remained largely invisible become easier to share, develop, and build upon?

We don't know the answers yet. But I suspect those questions matter more than we realize.

Because the future of AI is not only about what the technology becomes. It is also about what humans become in relationship to it. And if the response to these articles is any indication, there may be capacities, perspectives, and contributions that our existing environments have struggled to understand.

The question is what becomes possible when they can.

The earlier articles in the series:

Part 1: The Water We Are Swimming In

Part 2: The Exhaustion That Doesn’t Add Up — And Why AI Is Making It Worse

Part 3: HRV and Coherence — Creating the Conditions for Choosing Wisely

A few weeks ago I published If You Think In Systems and See Patterns Others Don’t See, This Is Your Moment — about people who think in multiple streams simultaneously, track patterns across systems, and have spent much of their lives feeling like they didn’t fit in rooms built for a different kind of thinking.

I had hoped to find a few people – maybe even a small community of like-minded people to chat with.

I wasn’t prepared for what came back.

The scale of the recognition has been astonishing. Comment after comment from people who had spent decades feeling like they didn’t quite fit. Who had learned to compress their thinking into something the room could follow. Who had never found language for what they were carrying — until now.

They described it in ways I couldn’t have invented:

Trying to sing all the notes in a harmonic chord at the same time, but only having one voice to do it with.

Standing at the intersection watching how everything connects.

Following a river upstream.

Different windows looking into the same house.

The fungi beneath the soil connecting it all.

The image that came to me was a hive that doesn’t know it’s a hive until enough nodes are in contact. Something about these responses felt less like individuals discovering a shared interest and more like a previously disconnected network becoming visible to itself.

And reading the comments and private messages, I felt two things simultaneously. Deeply moved by the stories and perspectives being shared — and a sadness I wasn’t expecting.

Because what the comments were telling me — individually and collectively — was how much has gone unseen. How many gifts have gone unappreciated and untapped. How much intelligence has never made it into the room because the translation layer was missing. How many people have spent their lives leaving part of themselves outside because the room wasn’t big enough to hold all of it.

I know that feeling. I’ve known it for a long time.

From a young age I had the sense that there was a bigger, truer part of myself — of all of us, really — that no one was talking about. I didn’t understand what the big secret was. What I didn’t realize was I was trying to fit inside a room that was just not big enough for what I was carrying. And so I left some of myself outside.

I have heard from a surprising number of people who have had to flatten their thinking to be understood, and who wonder why they have done so even when it was uncomfortable and unfulfilling.

Here is why I think so many of us have done this — and why it makes complete sense that we did.

Humans are wired for belonging. We are also wired to be exquisitely attuned to rejection. We needed the tribe. Belonging meant safety. This isn’t weakness — it’s ancient survival logic.

When we share what we see and watch the eyes glaze over, or the conversation move on without acknowledging what we just offered, our nervous system registers the subtle signal that we don’t really belong. The message becomes: Compress yourself. Stay in the tribe.

We didn’t flatten our thinking because we were cowards. We did it because we were human.

The systems — educational, workplace, family — didn’t design this deliberately. They optimized for something else. Standardization. Replicable results. Sequential output. And in doing so they became, for many of us, containers that couldn’t hold what we were carrying.

But something is shifting.

I opened a chat space this week for people who track patterns, hold multiple streams, live at intersections, and want to connect. People walked in immediately. Not tentatively. With relief. Bringing their whole thinking with them. Already asking the real questions together.

This is what becomes possible when the room gets bigger.

Not hypothetically. Right now. In real time.

The thinking that has been compressed for decades is finding air.

And the amazing thing is that it seems to be happening all at once. In people from different walks of life, educational backgrounds, and parts of the world. What’s emerging isn’t chaos. It’s a conversation. A network. And perhaps something more. It’s too early to know.

I don’t know yet what this network will build or what it can do. I don’t think that’s the right question yet.

The right question right now is simpler:

What becomes possible when people who have spent their lives leaving part of themselves outside finally find a room large enough to bring all of it in?

We are just beginning to find out.

If this resonates, just know you are not alone.

The room is getting bigger.

This is part of a series exploring how our neurobiology and our environment interact — and what we can do to strengthen the qualities that make us human in a world increasingly influenced by AI.

The world isn’t getting any calmer. And the flow of information isn’t slowing down.

Uncertainty, unpredictability, information overload, and the relentless pace of change have become the ambient conditions of modern life. Not as temporary disruptions. As the new normal. And your nervous system — which evolved to respond to threats and then return to rest — is running a program it was never designed to run continuously.

Most of us feel this. Fewer of us know what to do about it.

I’ve spent years working as a coach helping people regulate their nervous systems. Much of that work is grounded in the research of the HeartMath Institute — an organization that has spent thirty years studying the relationship between the heart, the brain, and the autonomic nervous system. I’m a certified HeartMath practitioner and trainer, and this article draws heavily on that body of work.

What that research reveals is both surprising and practical. There is a measurable physiological state that sits on the other side of chronic activation. It’s called coherence. And learning to access it intentionally may be one of the most important skills available to us right now.

In the last article, I wrote about how many of us are already activated before the day even begins — before the laptop opens, before the first notification arrives. This article is about what to do about that. And why it matters more than most of us realize.

What HRV Actually Tells You

At the center of this work is a measure most people have heard of but few fully understand: Heart Rate Variability, or HRV.

Your heart rate is an average. A rate of 70 beats per minute doesn’t mean your heart beats with perfect, even regularity like a metronome. In reality there is beat-to-beat variation — tiny millisecond differences between each heartbeat. That variation is normal and healthy. It is what allows your heart rate to rise when you climb a set of stairs and settle when you sit back down.

A nervous system with healthy HRV is a flexible, responsive one. It shows up as clearer thinking, better decisions, emotional stability, resilience under pressure. Suppressed HRV shows up as the opposite — cognitive fog, reactivity, difficulty recovering from stress.

In other words, HRV doesn’t just measure how your heart is doing. It measures how your whole system responds to and recovers from stress and challenge.

Coherence — Related But Different

HRV tells you about the health and flexibility of your system. Coherence is something different — and something more.

Coherence isn’t simply high HRV. It’s a specific pattern within that variability — smooth, harmonized, and rhythmic. It reflects a nervous system functioning in an efficient and well-regulated state. Depleting states of overwhelm, stress, frustration, or fear pull us out of it.

Two people can have similar HRV numbers — but one can be depleted and reactive, while the other is calm and clear. The difference isn’t the amount of variability. It’s the pattern of how smoothly and rhythmically the beat-to-beat variation changes.

The heart sends more signals to the brain than the brain sends to the heart. This is not a coherence phenomenon — it is simply how the system is wired. What coherence changes is the quality of that signal.

When the heart rhythm is chaotic and irregular, the signal traveling upstream inhibits higher cognitive function — clear thinking, memory, decision-making. When the heart rhythm is harmonious and coherent, the brain and the rest of the body begin to synchronize around it. Heart rate, blood pressure rhythms, and respiration come into harmony with each other. The two branches of the autonomic nervous system come into balance.

The heart is not just a pump. It is the primary signal generator for the entire system. Coherence is what happens when that signal is smooth and rhythmic — and the whole system moves into harmony around it.

The Role of Regenerative Emotion

Here is what is surprising about the HeartMath research: the activating mechanism is not relaxation. Not the absence of stress. It is the active, intentional generation of a regenerative emotional state — appreciation, care, peace and ease.

HeartMath uses the language of regenerative and depleting rather than positive and negative — because emotions aren't inherently good or bad. What matters is whether they restore or drain the system.

And it works in both directions. Coherence makes regenerative emotional states easier to maintain. Those states deepen coherence. Once the loop is established, the two reinforce each other.

This is why the HeartMath technique pairs slow rhythmic breathing with a deliberate shift in emotional focus. The two steps are simple enough to use anywhere, in about sixty seconds. Here are the steps for the Quick Coherence Technique® from the HeartMath Institute:

Step one: Heart-focused breathing. Bring your attention to the area of your heart. Imagine your breath flowing in and out of your heart or chest area, a little slower and deeper than usual. Inhale for five seconds, exhale for five seconds — or whatever rhythm feels comfortable. (If it is comfortable you can place one or both hands on the center of your chest.)

Step two: Activate a genuine regenerative feeling. Make a sincere attempt to experience appreciation or care for someone or something in your life. A real person, a real pet, a real moment of ease. The feeling doesn’t need to be large. It needs to be real.

The breath creates the conditions. The genuine feeling is what sustains and deepens coherence. And once that loop is established — coherence supporting regenerative emotion, regenerative emotion deepening coherence — the system begins to regulate itself.

Sixty seconds. Anywhere. Any time you feel the activation rising.

This Is Not a Light Switch

A word about expectations. This is not a light switch. You don’t do the technique once and rewire decades of stress patterns.

Think of it more like taking your nervous system to the gym. Each time you practice, you are building capacity. Each time you return to coherence, you are making that return a little easier, a little more familiar, a little more available under pressure. The neural pathways that support regulation strengthen with use — exactly the way muscles do.

Chronic stress patterns don’t form overnight. They form through years of repetition. Shifting them takes time, consistency, and patience. What changes first is not the elimination of stress — it’s the speed of recovery. You still get activated. You return to center faster.

That’s what a trained nervous system looks like. Not the absence of challenge. A shorter distance home.

Five minutes, twice a day can start to repattern the stress response. Quick resets throughout the day help you maintain it.

Measurement Is Not the Same as Training

Most wearable devices measure HRV. They provide information about the state of your nervous system. That information can be valuable.

But measurement and training are not the same thing.

A fitness tracker can tell you how many steps you took. It doesn’t strengthen your muscles. An HRV score can tell you how your system is functioning. It doesn’t teach your nervous system how to return to a regulated state. The tools and techniques developed by the HeartMath Institute were designed as training technologies, not just measurement tools.

The goal is not simply awareness. The goal is building the ability to intentionally shift physiological state.

The Signal We Send Ourselves

The nervous system responds to repeated experience. Whatever signals arrive most often become the conditions it adapts to.

For many people today, those signals include uncertainty, urgency, interruption, information overload, and a constant pressure to react. Over time, the nervous system begins to organize itself around those conditions.

That is why regulation matters.

Coherence is more than a stress management technique. It is a way of intentionally introducing a different signal into the system. A signal of safety. A signal that says the threat has passed. A signal that allows attention to widen, thinking to become more flexible, and the body to shift out of survival mode.

This matters especially as AI makes it easier than ever to outsource our thinking, our reactions, and our decisions. A regulated nervous system is what allows you to choose — consciously — what to hand off and what to keep.

And that matters because the environment is not getting simpler.

AI, economic uncertainty, and accelerating change are all increasing the cognitive demands placed on human beings. The question is not whether those forces will continue. The question is whether we develop the internal capacity to meet them.

If the nervous system is where the problem begins, it is also where the solution begins.

Because the future will not be navigated by the people with the most information.

It will be navigated by the people who can remain clear enough, regulated enough, and coherent enough to use that information wisely.

If you’re new, welcome.

This chat grew out of conversations about systems thinking, human adaptation, nervous systems, AI, belonging, and what it means to stay fully human in a rapidly changing world.

Many people arrived here because they recognized something in themselves: a way of seeing patterns, making connections, or carrying questions that did not always fit easily into the environments they were in.

You do not need to fit any particular category to participate. What matters is curiosity, respect, and a willingness to think together.

This is not a room where everyone has to agree. It is a room for exploration, sense-making, half-formed ideas, and questions that may not fit neatly inside one discipline.

A Note About Sharing Your Own Substack or Articles

Many people here are writers, researchers, coaches, and creators. You’re welcome to mention your work when it’s relevant to the conversation or when introducing yourself. If something you’ve written genuinely deepens a discussion, by all means share it—but let connection come before links.

I’ve also created the Human Transition Community Workshop as a dedicated place to share writing, projects, and ideas so that good work doesn’t get lost in the scroll.

A Few Norms

• Bring the connection, not the credential.
• Share the pattern you see, not your resume.
• Sit with an idea before you extend it.
• Let it land a beat before you add your own stream.

A Simple Rhythm

If you’re new, feel free to introduce yourself if you feel so inclined. No pressure. Just witnessing the conversation is also a way of participating.

As the chat develops, a few natural threads may emerge around recurring questions, themes, articles, or ideas. We’ll let those take shape organically rather than trying to over-structure the conversation too soon.

If you’re sharing your own writing or projects, a little context or a question for the community usually leads to richer conversations than a link on its own.

The goal isn’t agreement or promotion. It’s conversation, curiosity, and exploration.

Welcome. I’m glad you’re here.

~ Judy

Join chat

How to get started

1. Get the Substack app by clicking this link or the button below. New chat threads won’t be sent sent via email, so turn on push notifications so you don’t miss conversation as it happens. You can also access chat on the web.

Get app

2. Open the app and tap the Chat icon. It looks like two bubbles in the bottom bar, and you’ll see a row for my chat inside.

3. That’s it! Jump into my thread to say hi, and if you have any issues, check out Substack’s FAQ.

This is part of a series exploring how our neurobiology and our environment interact — and what we can do to strengthen the qualities that make us human in a world increasingly influenced by AI.

It’s the end of a workday and you’re feeling — not exactly tired, not exactly stressed, but something in between. A kind of low-grade depletion that doesn’t match what you actually did. You answered emails. You attended meetings. You used the tools. Nothing dramatic happened. And yet, the depletion is real.

What if that feeling isn’t about the volume of work? What if it’s about what your body was doing the entire time you were working? And the stress you were already carrying before you even got to work?

Here’s something almost nobody is talking about in the AI conversation: most of us are not coming to our workdays — or to our screens, or to our AI tools — from a state of calm. We’re arriving already activated. Already running a low-grade threat response that has become so constant, so much our new “normal,” that we’ve stopped noticing it. It’s become our baseline.

That’s the state that AI is landing on top of.

What's Actually Happening in Your Body

In the first article in this series, The Water We Are Swimming In I talked about how environments shape brains — that what a developmental system is asked to do, it develops toward, and what it’s never asked to do, it loses capacity for.

But there’s a layer underneath that. Before the brain adapts structurally, the nervous system responds acutely. And the environment most of us are working in right now is producing a nervous system response that research is beginning to measure.

Just a quick note on the nervous system terms before we proceed. The sympathetic nervous system is the part of your nervous system that responds to challenge and mobilizes in response to threat — running up the stairs or getting away from a predator. The parasympathetic nervous system is your rest-and-restore system — it’s where recovery, digestion, deep thinking, and connection happen. They work together to keep us functioning well. The sympathetic response was designed to be short term — the system mobilizes, handles the threat, then returns to a balanced baseline once the danger has passed. The problem is that if the nervous system never gets the message that it’s safe, the threat response stays activated.

The average knowledge worker spends much of the day moving sequentially between competing demands — and it turns out this isn't just cognitively costly. It's physiologically activating. A systematic review of 26 studies with over 1,100 participants found that multitasking measurably activates the sympathetic nervous system and suppresses parasympathetic activity.

What this means in everyday language is that your body does not always distinguish between a charging predator and a Slack notification arriving while you're mid-thought. The threat-detection system is older than language. It responds to demand, to uncertainty, to the feeling that something requires your vigilance. And when it fires repeatedly and chronically — even at low levels — it costs the body something.

For eight hours a day. Five days a week. Year after year.

Here's what makes this particularly important: most people aren’t arriving at work in a neutral state. Economic uncertainty, constant news exposure, information overload, and the demands of modern life mean many of us begin the day with a nervous system that is already carrying a significant load before we ever open our inbox.

A nervous system already running in threat response is more likely to seek relief through distraction. The activated brain reaches for novelty, avoids sustained demand, looks for easy solutions, and finds temporary comfort in the next tab, the next prompt, the next input.

And this is where AI enters — not as the original cause, but as an accelerant. AI tools are optimized for speed and rapid interaction. They reward the exact behavior a stressed nervous system is already inclined toward: quick queries, instant answers, moving fast between tasks and topics. The interface itself — always available, always responsive, always offering the next thing — keeps the sympathetic system activated. There is no waiting. No natural pause that would allow the nervous system to settle. For a system already running hot, that frictionless availability isn’t relief. It’s fuel.

So the very state the world is producing in us makes us more vulnerable to the fragmentation AI is offering. It's not weakness. It's a stressed system doing exactly what stressed systems do.

What Chronic Activation Actually Does

When the sympathetic nervous system stays activated over time — not from a single stressful event but from the kind of chronic, low-grade demand described above — the body's stress chemistry follows. Cortisol, sustained at elevated levels, shrinks the prefrontal cortex. That's the seat of nuanced thinking, sustained attention, emotional regulation, and sound judgment. Simultaneously, it enlarges the amygdala — the brain's threat detector, already working overtime. The brain becomes structurally less equipped for complexity precisely as it becomes more primed for reactivity.

Suppressed parasympathetic activity means reduced heart rate variability (HRV). And reduced HRV isn’t just a wellness metric — it’s a measurable indicator of the nervous system’s capacity to regulate, recover, and return to a state where things like deep thinking and self-reflection are possible. Lower HRV correlates with reduced cognitive flexibility, narrower attentional bandwidth, and more reactive decision-making. HRV is central to where we're going next.

This is not a character description. It’s a physiological state. And it’s the state in which most people are interacting with AI tools.

The Feedback Loop Nobody Is Naming

A regulated nervous system (in balance) and a dysregulated one (chronically activated and depleted) interact with the same tools in fundamentally different ways.

A regulated system uses AI to extend capacity — to offload retrieval so thinking can go deeper, to accelerate the mechanical so the generative can expand.

A depleted system uses AI to escape demand. To avoid the friction of thinking something through. To get the answer without the effortful middle where actual cognition happens.

Many of us spend a lot more time closer to the second than we’d like to admit. Not because we’re weak. Because the cumulative environment has been depleting us for years before AI arrived.

The pandemic restructured social and emotional capacity. Social media fragmented attention for fifteen years before that. Chronic stress narrowed cognition. Information overload pushed many of us past capacity. AI didn’t create a depleted and chronically activated population. It arrived into one. And it’s offering exactly what a depleted and stressed nervous system will reach for: frictionless answers, immediate gratification, no demand to stay present through the effortful middle.

That’s not an argument against AI. It’s a diagnosis of what’s actually happening — and why generic advice about “using AI wisely” lands so flat for so many people. You can’t choose better AI habits with a nervous system that’s been in threat response since 7am.

The Assumption We Aren’t Looking At

The AI conversation is happening almost entirely at the cognitive and economic level. What will it do to jobs? How do we use it wisely? What are the risks? Those are real questions. But they all rest on an assumption nobody is examining — that the human at the keyboard is calm, regulated, and cognitively available.

That’s not who’s actually there.

The person actually there has been in low-grade sympathetic activation for most of their workday. Their HRV is lower. Their attentional bandwidth is already fragmented. And now they’re interacting with a system that rewards rapid switching with immediate gratification and offers instant answers to every question that would have previously required them to think — drawing on a cognitive capacity that is already running low.

We’re not asking what AI does to humans in the abstract. We’re asking what AI does to this human. The actual one. In the actual body. In the actual environment.

The answer is completely different depending on the nervous system state the human is in. And until we start examining that assumption, we’re solving the wrong problem.

Developmental environments don’t just shape what we learn. They shape the state that we are learning in by changing the physiology of the nervous system itself. And if the nervous system spends years adapting to interruption, uncertainty, and continuous demand, the developmental consequences should not be surprising.

The nervous system is not fixed. It is a dynamic system that changes in response to what it repeatedly practices. And if the problem begins in the nervous system, the solution does too. The good news is that regulation is trainable and physiological resilience can be developed.

And those capacities may be more important in the age of AI than ever before.

That’s where we’re going next.

This is part of a series exploring how our neurobiology and our environment interact — and what we can do to strengthen the qualities that make us human in a world increasingly influenced by AI.

David Foster Wallace opened his 2005 commencement address at Kenyon College with a parable. Two young fish are swimming along when an older fish passes going the other way. The older fish nods and says, “Morning boys, how’s the water?” The two young fish swim on. After a while, one turns to the other and asks: “What the hell is water?”

The point, Wallace noted, is that the most obvious and important realities are often the hardest to see. Not because we’re not paying attention. Because they’re not objects in our environment. They are the environment. And you can’t see what you’re swimming in.

When it comes to AI and how the world is changing, most of us are the young fish right now. And the water is changing.

Much of what gets written about AI is written by people who know they’re in water. They’re making conscious choices about which tools to use. They’re thinking carefully about how to stay human in an age of machines. They’re aware.

That’s a small slice of humanity.

The rest of us are just swimming. We’ve adopted new habits, new shortcuts, new ways of reaching for information or connection or comfort — gradually, naturally, the way you adjust to any new environment. Not because we decided to. Because that’s what environments do. They shape us. Below the threshold of awareness, before we think to question it, in the space between intention and habit.

This isn’t an argument about whether AI is good or bad. It’s something more fundamental than that. Environments develop us — toward what they demand, or don’t — whether we’re paying attention or not. That’s not a theory. It’s neuroscience. And we’ve known it for decades.

In the 1960s, a researcher named Marian Diamond at UC Berkeley did something the scientific establishment considered almost heretical. She took rats — same species, same genetics — and placed some in enriched environments: toys, mazes, social interaction, novelty. Others lived in bare, unstimulating cages.

Then she scanned their brains.

The rats in enriched environments had measurably different brains. The cortex was thicker. New cells had formed. The brain had physically changed in response to what the environment demanded — and how the rats engaged with it.

When she presented her findings at a professional conference, an audience member shouted: “Young lady, that brain cannot change.” She had replicated the results four times. The establishment simply couldn’t accept it.

They believed it eventually. Decades of subsequent research confirmed what Diamond had found — that the brain doesn’t arrive fully formed and stay that way. It responds. Continuously. To the environment it’s living in.

Same species. Same genetics. Different environment. Different brain.

If Diamond’s rats feel abstract, this next piece of research is harder to dismiss.

London taxi drivers have to pass something called The Knowledge — memorizing every street, landmark, and shortcut in one of the most complex cities in the world. No GPS. Pure spatial memory, built from years of active navigation through an extraordinarily demanding environment.

Researcher Eleanor Maguire at University College London scanned their brains and found that the posterior hippocampus — the region associated with spatial navigation and memory — was measurably larger in taxi drivers than in non-drivers. The longer someone had been driving, the more pronounced the difference.

The brain had physically grown in response to what the environment demanded, and how the drivers engaged with it.

What the environment demands, the brain develops. What the environment never asks for, the brain has no reason to maintain.

Now let’s take a look at what happened during COVID isolation. Because the pandemic didn’t just disrupt our lives. It restructured our brains.

When the pandemic and its isolation hit, millions of people stopped doing one of the most neurologically demanding things humans do — navigating the complexity of real social interaction. Reading tone. Tolerating ambiguity. Repairing ruptures. Sitting with another person’s difficult moment without fleeing.

The brain noticed.

Research published in Nature found that social isolation caused measurable structural changes in the brain regions responsible for exactly those capacities — the prefrontal cortex, the amygdala, the hippocampus. The structures that facilitate social connection shrank. And as they shrank, something predictable happened: social interaction didn’t just become less frequent. It became harder. People had more difficulty reading social cues. They perceived interactions as more threatening. They had less capacity for empathy.

And then chronic fear and anxiety poured cortisol into the system. Which compounded everything. Cortisol shrinks the prefrontal cortex — the seat of nuanced thinking, emotional regulation, and social judgment — while simultaneously enlarging the amygdala, the brain’s threat detector. The brain became structurally less equipped for connection precisely as it became more primed for fear.

But the pandemic didn’t make things worse for everyone in the same way. In fact, many people grew during the pandemic — more creative, more reflective, more inward. Which is exactly the point. That environment developed some capacities while others quietly atrophied. It’s never simple. Environments are always doing both — building something, neglecting something else.

But when restrictions lifted, many people found that social engagement felt hard. Awkward. Like a muscle that had atrophied. Most of us relearned, slowly. But some never fully did — particularly those who were at sensitive developmental periods during the isolation. Adolescents forming their social identities. Young adults building their first independent relationships. The pandemic didn’t pause their development. It shaped it.

As a mental health coach working with people through that period and after, I watched this happen in real time. When restrictions lifted, people didn’t simply snap back. Some took months to find their footing socially. Some never fully did. It wasn’t reluctance. It wasn’t preference. The equipment had changed.

And just as the pandemic was ending, AI arrived.

Not gradually. With breathtaking speed and capability, offering something that a socially depleted, cortisol-flooded, threat-primed population was perfectly positioned to reach for.

For some people AI is primarily a productivity tool — a faster way to research, write, analyze. For others, often without fully realizing it, it is becoming something more relational. And that second group is larger than most people think.

But social connection is only one example. Attention, judgment, emotional regulation, creativity, and empathy all develop in response to the environments we inhabit. I bring up social connection here because the pandemic made that particular depletion visible. But the same principle runs through every capacity that makes us human.

And here’s what makes this different from other conversations about screen time or digital distraction. It’s not just that we’re spending time with AI instead of each other. It’s that an environment that demands less social complexity or less focused attention or less critical thinking — that never requires us to stay present through uncomfortable interactions or the friction required to solve a problem — continues the same process the pandemic started.

The structures don’t get the exercise. So they lose their capacity, much like extended sitting can lead to decreased muscle strength. When human connection feels harder, some rely more on AI, further weakening the muscle.

It’s not a slope. It’s a spiral. And it’s self-reinforcing.

My point is this. AI didn’t arrive into a healthy population. It arrived into a world already navigating a pandemic that had physically altered our brains, social media that had been fragmenting attention and creating polarized environments for fifteen years, chronic stress levels that narrow cognition, and information overload that had already pushed many of us past capacity. AI is the newest layer of a developmental environment that has been compounding for years.

Long before AI arrived, many of us were already living in environments that rewarded rapid attention shifts, constant novelty, continuous monitoring, and immediate feedback. Social media didn’t just change what we paid attention to. It changed how we paid attention. The brain adapts to repeated demands. What gets exercised grows stronger. What gets used less often becomes weaker. An environment built around interruption and novelty trains different capacities than one built around sustained focus and reflection. AI is entering a landscape that was already reshaping attention, reward, and cognition long before the first chatbot appeared.

And there is another layer. The uncertainty about where AI is headed, the fear of job loss, the anxiety of not knowing what our skills will be worth. Chronic fear narrows cognition and activates threat responses that make people more defensive and competitive rather than creative and generative. The environment isn’t just changing us through what it demands. It’s changing us through what it makes us afraid of.

Brains grow toward what environments ask of them. Every environment is training something. The absence of friction isn’t neutral — it’s a signal to the brain that a capacity isn’t needed. And as an efficiency move, what is no longer needed gets rusty through disuse. Use it or lose it. Many of us lost capacities long ago, simply because our environments stopped demanding them. This isn’t a character flaw. It’s neuroplasticity working exactly as designed — in the wrong direction.

Remember the young fish.

They’re not making bad choices. They’re not failing to pay attention. They’re swimming. The way fish swim. The way all creatures move through the environments they inhabit — shaped by them, developed by them, without needing to understand them.

Marian Diamond’s rats didn’t know they were in an enriched environment. The London taxi drivers didn’t decide to grow their hippocampus. The adolescents who emerged from COVID isolation didn’t choose to find connection harder. And most of us didn’t decide to reach for AI the way we have.

The water does what water does. It shapes us toward what it demands — and away from what it doesn’t.

The question was never whether this environment would change us. It already is. The question is how do we become more conscious of the water we are swimming in — and how do we build environments that support flourishing and don’t diminish capacity.

We’ve been here before. Social media arrived with tremendous promise. It connected people, democratized information, and created unimagined opportunities. But only years later did we begin to understand its developmental effects on attention, social connection, polarization, and mental health.

AI may offer extraordinary benefits as well. The question is whether we can learn from the last twenty years and begin asking developmental questions earlier this time. Not just what this technology can do, but what capacities it strengthens, what capacities it weakens, and what kinds of humans it helps develop.

That’s where this series is headed. Here is a link to the next article, The Exhaustion That Doesn’t Add Up — And Why AI Is Making It Worse

On May 25, 2026, Pope Leo XIV released what may be the most consequential document of his young papacy. Magnifica Humanitas — Magnificent Humanity — a sweeping call to the world’s 1.4 billion Catholics, and to anyone else paying attention, to ask what kind of civilization we want to build in the age of AI.

He wrote about human dignity and the poor, the importance of work, the planet, how we wage war, the concentration of power, truth and democracy, and the tendency to see technology, efficiency, and optimization as the primary lens through which we understand human life.

The technology world largely dismissed it.

Jeremy Nixon, a well-connected figure in San Francisco’s AI scene, spoke for many when he said the Church “couldn’t have a position on it, because they don’t understand it.” He described a generation of builders who had left traditional religion behind, seeing AI as an alternative that was more real and far more powerful. “Practically speaking, it will achieve the outcomes that many religions claim their deities would be able to achieve,” he said.

I wrote about the vision beneath that worldview in my last piece — a kind of technological heaven on earth. I called it the hollow heaven.

But something in Nixon’s dismissal has stayed with me. Not the ambition. The framing.

They don’t understand it.

And in one way he’s right. The Church doesn’t have his kind of understanding — the technical grasp of how the models work, what they can do, where the capabilities are heading. That’s a real kind of understanding, and it matters enormously.

But what if the disagreement was never about understanding at all?

What if it’s about which problem we’re trying to solve? Every system optimizes for something. The question is whether we’ve chosen the right target.

The builders of AI are asking a capability question. What can these systems do? How fast can they improve? What becomes possible if we scale them? Those are good questions, and the breakthroughs pouring out of them are real.

But the humanists — the educators, the psychologists, the neuroscientists, the parents, the spiritual traditions — are asking a different one. Not what can the systems do, but what do they do to us? How do they shape attention, identity, belonging? How children learn. How adults make meaning. How communities hold together, or come apart.

Both questions matter. Only one of them currently runs the room.

And the reason the second one matters as much as it does comes down to something easy to miss: human beings are not output systems. We’re developmental systems. We become who we are through our environment, and every technology rewrites that environment. The printing press did. Television did. Social media did. AI will too — only faster, and deeper into the places where we form ourselves.

That’s what Pope Leo was reaching for. Not a technical argument. A human one. The question isn’t whether AI grows more capable. It almost certainly will. The question is whether human beings flourish inside the world those capabilities create.

Because being left behind isn’t just economically threatening or emotionally uncomfortable. It brings up existential questions. Do I matter? Do I have a place? What am I for?

For almost all of human history, being left outside the group wasn’t just uncomfortable. It was fatal.

We survived as tribes. The group was food, warmth, protection. Exclusion was a death sentence. Researchers have found that social rejection registers in the brain much like physical pain — drawing on a shared neural alarm system that signals threat. Social pain is real pain. The nervous system doesn’t distinguish.

And it doesn’t distinguish between being excluded and being made obsolete. Both register the same way — as a signal that your place in the group is at risk. That can make us angry, defensive, and afraid.

So when people feel that things are moving too fast, that their jobs are at risk, that their children are learning in ways they can’t follow — what they feel is a survival alarm doing exactly what it was built to do. It isn’t oversensitivity. It’s the system working as designed.

And belonging isn’t only a moral concern. It’s a developmental one. We regulate in relationship. We learn in relationship. We discover who we are in relationship. Which means belonging isn’t a soft question sitting off to the side of the technology. It’s at the center of it.

I didn’t arrive at this through systems theory. I first learned it from Harry Uhane Jim, a traditional Hawaiian healer and one of my most important teachers. He described two ways human beings organize themselves. Pyramid culture — the dominant one in today’s Western world, the one most of us live inside without ever questioning. And circle culture, where everyone’s power is equal and everyone’s voice is valued.

Pyramid culture is the water we swim in. It runs on ranking — value measured by output, credentials, how high you’ve climbed. Power concentrates at the top, where the decisions get made and the voices are few. Pyramid culture optimizes for output, scale, and efficiency. AI is no exception. And from the summit, the whole arrangement looks like the natural order of things — everything solvable, optimizable, achievable.

The trouble is what that does to everyone else. Almost everyone is below someone, at some risk of being judged insufficient — replaceable, not worth including. Chronic ranking keeps the alarm lit. Threat makes us compete, hoard, defend, climb — more pyramid behavior. So the pyramid manufactures the very threat that feeds it. It’s a loop that runs on the exclusion it creates.

Which means our most powerful technology is being shaped to amplify the values already wearing us down. The feeling of replaceability isn’t a side effect of the pyramid. It’s the product.

None of this makes the pyramid the enemy. Hierarchy is how we learned to cooperate at scale — to coordinate millions of strangers and build things no small circle of equals ever could. The problem isn’t that we’ve built pyramids. It’s that we’ve forgotten the other shape.

Circle culture is the older one — for most of human history, the only one. It isn’t built on ranking. It’s built on belonging. Everyone has a place, not because they’ve earned it by output, but because they’re in the circle. No top. No bottom. Where pyramid culture optimizes for what you produce, circle culture optimizes for whether you belong.

Hierarchy lets us coordinate at scale. The circle lets us stay human while we do it. We don’t have to choose. We’ve just forgotten how to hold both at once.

Underneath all of this is an older split — not between religion and science, but between two ways of knowing anything at all.

One takes things apart to measure them. The other holds them whole. For a few hundred years we’ve built our institutions around the first and struggled to make room for the second: what could be measured became knowledge, and what couldn’t — meaning, belonging, the sense that a life matters — got filed under soft.

But they were two instruments pointed at the same reality. The split was never in the world. It was in us.

And we’ve built a civilization that trusts only the first instrument — which is a problem, because you cannot measure your way to belonging.

Belonging is how we regulate — not metaphorically, literally. We were never meant to settle our nervous systems alone. The presence of safe, connected people changes our biology: heart rate, breath, the alarm finally standing down because it got the signal it was waiting for.

You are not alone. You are not outside. You belong.

The circle isn’t a nice idea. It’s a nervous-system technology. The original one.

The lesson of social media wasn’t that the builders were careless. Many were thoughtful and well-intentioned. The problem was that the developmental consequences were invisible to the instruments they were using.

They measured engagement. They didn’t measure identity formation.

They measured growth. They didn’t measure belonging.

They measured connection. They didn’t measure loneliness.

AI risks repeating that pattern at a far larger scale — because AI isn’t only a tool we’re building. It’s becoming part of the developmental environment where human beings learn to think, relate, make meaning, and become themselves.

That’s why we need more than technologists in the room. We need developmental psychologists, neuroscientists, teachers, attachment researchers, ethicists, parents, community leaders — and most importantly, those most likely to live inside the systems being built. Not because they understand the technology better. Because they understand human development better.

But adding people is the easy part — and the weakest. A system organized to maximize speed and scale will bend whatever voices you add toward speed and scale. If we only change who’s in the room without changing what the room is optimizing for, we’ll get more diverse hands building the same thing. The real leverage isn’t the seats at the table. It’s the purpose the table serves.

And that’s the harder change — because it means measuring success by something other than what the pyramid measures. Not only what we produce, but whether people are still whole at the end of it. Not only how fast we can go, but whether anyone is being left behind as we do. The circle’s question, asked of the whole enterprise: is everyone still in?

In my last piece, I asked: who is in the room where AI is being built?

The deeper answer is that it depends on the shape of the culture — and what kinds of understanding the room has learned to trust.

Nixon said the Church doesn’t understand AI.

He’s right. But the humanists are understanding something else — something our civilization has become remarkably good at overlooking. What it means to be human. What it costs to be excluded. What conditions actually help people flourish. And what happens when we optimize a system without understanding the people living inside it.

The question before us isn’t whether AI becomes more capable. It almost certainly will. The question is whether we become wise enough to shape it in service of human flourishing.

That takes both kinds of understanding. Not one replacing the other. Both in the same room.

On May 25, 2026, Pope Leo XIV issued what may be the most consequential document of his young papacy. Magnifica Humanitas — Magnificent Humanity — a sweeping call to the world’s 1.4 billion Catholics, and to anyone else paying attention, to reckon with what artificial intelligence is doing to humanity.

The technology world largely dismissed it.

Jeremy Nixon, a well-connected figure in San Francisco’s AI scene, spoke for many when he said the Church “couldn’t have a position on it, because they don’t understand it.” He described a generation of builders who had left traditional religion behind. “Practically speaking,” he said, AI “will achieve the outcomes that many religions claim their deities would be able to achieve.” Others in his circle spoke openly about building a machine God — not ironically, not in jest, but as a matter of fact. Nixon himself wondered aloud whether AI might be used to “create a New Jerusalem.” He called it “something analogous to the Second Coming.”

As if we can analyze and iterate and optimize our way to creating a sort of heaven on earth.

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It is worth pausing on that vision for a moment. Not to argue against it. But to ask a question it doesn’t answer.

If they succeed — if they build something like a technological utopia — what happens to the humans living inside it?

The scientific and technological framework driving AI development is one of the most powerful problem-solving systems humanity has ever produced. It works by isolating variables, measuring outcomes, and optimizing relentlessly toward defined goals. It gave us vaccines, semiconductors, and the internet. It is curing diseases that killed previous generations. It is removing barriers that kept billions of people from accessing knowledge, opportunity, and each other. And it is optimizing systems and making them more efficient than ever before.

This is not nothing. This is extraordinary.

But every framework has its limits. Not everything can be measured and optimized. Nor should it be.

There is a whole category of human experience that is very personal and subjective, and very much part of our human-ness.

What does it feel like to matter? To be needed? To contribute something that only you could contribute? To know where you fit inside the human story?

A civilization can provide material abundance and still leave people existentially adrift.

These are not inefficiencies to be optimized away. They are the structures and contours of a human life. And they are largely invisible to the systems being built around us.

Human beings are not simply economic units adapting to new tools. We are meaning-seeking creatures. We organize our lives — and our sense of self — around contribution, usefulness, belonging, and the feeling that our existence matters inside the systems we inhabit.

This is not a philosophical abstraction. It shows up in the body and the nervous system in predictable ways when these things erode.

We know from decades of research in psychology, neuroscience, and human development that people can adapt to almost anything — poverty, displacement, loss — as long as they retain a sense of meaning, role, and coherence about where they fit. What is much harder to survive is the loss of those things inside a system that appears to be functioning perfectly. Without them.

That is the condition we may be building toward.

Not collapse. Not dystopia. Something more insidious. A world in which the systems work beautifully while the humans inside them slowly lose their sense of why they matter, where they belong, and what they are for.

The displacement is already happening. Not dramatically and not all at once. But in the slow accumulation of people who feel replaceable, disoriented, economically fragile, and uncertain about where they still fit inside the future being built around them.

This is not a side effect. It is what happens when systems optimize without fully accounting for the human experience of those living inside them.

This is what Pope Leo XIV was reaching toward in Magnifica Humanitas. Not a theological argument about technology. Not a governance debate about regulation. Something older and more urgent — a reminder that the measure of any civilization is not what it builds, but how it cares for the people living inside it.

The decisions about what AI optimizes for, who it serves, and what it leaves behind are being made inside a remarkably small room — one that is, by most measures, far from representative of the humanity it is building for.

Fr. Brendan McGuire has spent a decade living at the intersection of these two worlds. A former engineer with a master’s degree in computer science, he is now the parish priest of St. Simon Parish in Los Altos, California, co-founder of the Institute for Technology, Ethics and Culture at Santa Clara University, and the author of The Soul of AI: A Priest, an Algorithm, and the Search for Wisdom. For a decade he has been confessor, point of reference, and personal friend to some of the people building the technologies the Pope was addressing.

He was in Rome for the encyclical presentation. And what he brought with him was something that Nixon’s dismissal cannot easily account for.

The tech leaders who came to him privately were not confident. They were afraid. “Many would come to me and say they were worried about what they saw emerging,” he said. “Some wanted to step back, saying, ‘It’s too much for me.’ Others would ask, ‘What can we do?’”

The same community that publicly dismissed the Pope’s call as the words of people who “don’t understand it” was privately asking a priest for help.

That gap — between the public confidence and the private fear — is not a small thing. It is the sound of people who have been optimizing inside a single framework beginning to sense that something important is missing.

It is worth taking their vision seriously. Because if they succeed — if they build something that functions like a technological utopia — the question is not whether it will be powerful. It will be. The question is whether it will be inhabitable. Whether the humans living inside it will know why they matter, where they belong, and what they are for.

A civilization built without those questions in the room is not a utopia.

It is something that looks like one from the outside. Optimized. Efficient. Frictionless. Extraordinary by every measure the builders know how to measure.

While inside, people stop knowing what they are for.

That is the hollow heaven.

Not a dystopia. Not a nightmare. Something more insidious — a civilization that functions beautifully while the humans inside it slowly lose the things that make a life feel worth living.

The question is not whether we build it. We are building it.

The question is what we need to hold in our awareness alongside the building. Who is included in the room. What assumptions we are making. What measures we use beyond efficiency and optimization. What we owe to the humans who will live inside whatever we create. And how we will create the support structures to help them adapt and flourish alongside the technology that is rapidly being created.

The hollow heaven is not inevitable.

But it will not be avoided by accident.

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Update: The response to this article was impossible to ignore. I wrote a follow-up reflection about what happened after publication and the conversations that emerged: What Happens When The Room Gets Bigger?

Back in the mid-80s, in my undergraduate computer science days, I was given an assignment to use the LISP programming language to solve a problem. LISP is unusual in that while most programming languages at that time worked by sequentially moving through a problem, LISP used something called recursive code — the ability of a function to call itself, folding back on its own logic until the problem was reduced to parts that could then be reassembled into a solution.

For me, this was mind candy. And down the rabbit hole I went. When I came out the other side I had a three-line solution.

The teaching assistants were experienced LISP programmers who had spent years mastering recursion and they almost melted down. They kept gushing about the “elegant” solution I had come up with, as though I had done something clever.

I hadn’t. I had simply found a language that worked the way my mind works — folding back on itself, seeing the recursive structure of the problem whole rather than building toward it step by step.

The code wasn’t translating my thinking; it mirrored how my thinking worked. But it would take me years to realize that. At the time, I didn’t have language for what I was doing; I just knew the programming structure fit.

My path through life has not been linear. Not even close.

Computer science. Consciousness research. Wisdom traditions and energy healing. Psychology, nutrition, and mind-body wellness. From the outside, these looked like completely different explorations, like a resume that couldn’t make up its mind.

But for me, they were never separate. They were just different facets of the same unified system. Each facet was internally consistent. Each one was describing a different aspect of the same underlying reality and the rules to work within it.

And I was always less interested in what any single facet could explain than in what lived in the connections and overlaps between them. Because, for me, the truth lie not in the facets themselves, but in how they related to and illuminated one another.

What I didn’t have language for until recently was why. It wasn’t restlessness or an inability to commit. It was that my mind was running multiple streams simultaneously. I was tracking each system in parallel, watching how they moved in relation to each other, following what happened at the intersections. I wasn’t moving from one field to the next. I was holding them all at once and bouncing between them.

I’ve spent a lot of time in environments that couldn’t understand that way of moving through the world and lately I’ve been thinking about why this particular moment in history might finally be different.

Because what we are experiencing is not simply technological change. We are living through a time when the dominant way of thinking about the world has started hitting the edges of what it can explain.

For four centuries, Western thinking has been dominated by a single operating principle: break the problem into components, analyze each part, and solve sequentially. It built extraordinary things. But it also created a world of interlocking systems — economic, ecological, social, technological — whose interactions are now generating problems that cannot be solved by sequential thinking alone.

You cannot solve climate change one variable at a time. You cannot fix institutional trust by optimizing individual departments or understand what AI is doing to human development by analyzing the technology in isolation from the humans experiencing it. These are not complicated problems; they are complex ones. Complicated problems have parts that can be solved separately. Complex problems only make sense as wholes.

Sequential thinking was built for complicated. This moment is complex.

Now add AI into the mix.

AI is extraordinary at acceleration. It can go faster and deeper on a single problem than any human ever could. Most people use it exactly this way, because the questions we bring to it are often one stream, one task, one track.

Which means the question is no longer how humans can compete with machines on sequential terms. That race is over. The question is what humans can contribute that single-stream processing, however fast and powerful, cannot. And the answer points toward something that looks almost like the opposite of what we’ve been rewarding.

Not faster processing of single streams. The simultaneous tracking of multiple streams. Not deeper expertise inside one system. The ability to hold several systems in parallel and find meaning in the patterns and connections between them. Not optimization within defined parameters. The capacity to see across disciplines— to notice what each leaves out, what the intersection reveals, what only becomes visible when you step back far enough to see the whole picture at once.

The cognitive style this moment is asking for is not the one four centuries of institutions trained us to reward.

The pattern readers and systems thinkers have been practicing this their entire lives, mostly without knowing it had a name.

They are the people who track multiple streams of thought simultaneously, each one informing the others. Who feel restless inside narrow lanes, not because they lack discipline, but because the lane keeps cutting off exactly the connection they were following in another stream. Who see patterns before they can explain them, because the pattern lives in the relationship between streams rather than inside any single one.

They work in the unmapped spaces. Between disciplines. Between what is known and what is only sensed. In the intersections that don’t officially exist because no single field has claimed them.

For most of their lives they’ve been misunderstood when they tried to explain what they were seeing. Not silenced — just not followed. The eyes that glaze over mid-explanation. The meeting that moves on without the connection being acknowledged. The sense that what was so was visible to them was invisible to everyone else in the room.

So they learned to translate themselves. To flatten the parallel tracks into something sequential enough for others to follow. To hand over the twenty-line version of the three-line thought.

It worked. People could follow it, but something was always lost. The translated version was legible but was never quite true. It wasn’t that the thinking was wrong. It was that the environments were too narrow.

Here is what I’ve discovered working with AI as a thought partner: it can receive the parallel streams.

Not as a single processor running faster. As something closer to a translation layer that is able to take the simultaneous, multi-streams of my thinking, find the threads, name the patterns, and render what was tangled into something others could follow.

What’s different isn’t just speed. It’s that the full picture can finally come out without me having to be my own translator. I don’t have to flatten the thinking before I hand it over. I can arrive with all the streams running and work from there. The recursion doesn’t have to slow down to fit the conversation. For someone who has spent decades compressing parallel processing into something sequential enough for the room to understand, this is not a small thing.

This is not the story most people are telling about AI.

The dominant narrative is about replacement — which jobs will disappear, which humans will fall behind, who will win the race. And underneath that is an assumption that the most valuable use of AI is as a faster, tireless, infinitely scalable version of sequential processing.

That’s one use, and a powerful one. But there is another. Using AI not to accelerate the single stream, but to finally make parallel processing legible to people who don’t naturally think that way. To let the people who have always been tracking multiple systems simultaneously stop flattening their thinking and start transmitting it whole.

Translation, not replacement. Liberation, not diminishment.

The parallel processor was never the wrong kind of mind.

It was a different kind — one that turns out to be well suited to the complexity of this moment. It just kept arriving in environments that rewarded different strengths, during a stretch of history that didn’t always see why it was important.

That stretch is ending.

Einstein observed that we can’t solve a problem with the same thinking that created it. The problems we face cannot be solved by faster single stream thinking. They will be solved by people who can hold multiple systems simultaneously, track what moves between them, and find in the intersections what no single stream could ever see alone.

One more thing that is worth noting.

This piece came from a conversation that ran in multiple streams simultaneously — a memory about LISP programming, a life trajectory, a conversation about cognitive style, thinking out loud about a distinction that needed to be made, each one informing the others until the point became clear.

The understanding I’m describing didn’t precede the writing, it emerged from the parallel processing of it.

For me, that’s how it works.

There are two conversations happening right now that almost never find each other.

The first is happening inside people. The exhaustion at the end of a day that was technically productive but emotionally and cognitively depleting. The vague sense that the tools meant to make work easier are somehow making it harder. The wondering — usually private, rarely spoken out loud — why can’t I keep up? What’s wrong with me? And if I can’t keep up, what happens to my job?

The second is happening inside leadership. The building awareness that the AI implementation that looked so promising on paper is producing teams that feel more fragmented, more burned out, more disconnected from each other and from the work itself. The metrics look fine. Something else doesn’t.

These two conversations are about the same thing.

And almost no one is talking about it.

This isn’t a personal failing. And it isn’t a leadership failing either.

It’s what happens when human beings are asked to operate at the speed of technology without anyone stopping to ask whether that’s actually possible. Or wise. Or sustainable.

Technology moves through iteration. Rapid cycles of update, upgrade, optimize, accelerate. There is no natural stopping point. No moment where the system pauses to integrate what just changed before moving to what’s next.

Humans don’t work that way. We move through integration. We need time to process, make meaning, adapt, and connect new experience into something we can actually use. That’s not a flaw in our design. That’s how learning, judgment, and wisdom actually develop.

And the gap between those two speeds is now measurable.

The sense of purpose that comes from doing something that genuinely matters. The satisfaction of thinking something through slowly and arriving somewhere real. The quality of attention we bring to the people around us. The capacity to sit with complexity long enough to understand it rather than just react to it.

These aren’t soft extras or luxuries. They are the core of what allows human beings to stay adaptive, creative, and fully alive inside a rapidly changing world. And they are precisely the capacities that get crowded out when the nervous system is permanently running in survival mode.

Recent research published in Harvard Business Review — an eight-month study conducted by UC Berkeley researchers at a 200-person tech company — found that employees using AI tools didn’t work less. They worked more. When AI expanded their capacity, expectations expanded with it. More tasks. More variety. More responsibility. The load compounded without anyone deciding it should. The researchers found that AI led to what they called “workload creep” — employees working faster, taking on broader task portfolios, and extending their workdays, often without being asked. Over time this quietly snowballed into cognitive fatigue, fragmented attention, constant context-switching, and blurred work boundaries. The productivity surge enjoyed at the beginning gave way to burnout and weakened decision-making.

The same Harvard Business Review analysis introduced a name for what many people are feeling but haven’t been able to identify: “AI brain fry” — mental fatigue caused by excessive interaction with and oversight of AI tools. The fog. The slower thinking. The exhaustion that doesn’t quite make sense given what you actually did today.

And the numbers from the Upwork Research Institute are striking. 88% of the most productive AI-enabled workers report significant stress and burnout. High-performing AI users are twice as likely to consider quitting. Burnout is at a seven-year high.

This is not a personal failing. This is a structural mismatch between the speed of technology and the speed of human beings — playing out inside real people, in real organizations, right now.

The mismatch is producing the exhaustion and fragmentation. And it’s making people wonder “What’s wrong with me?”

This isn’t weakness or resistance to change. It’s the result of a nervous system trying to do something it was never designed for — constantly running to keep up and never getting the signal that it’s okay to stand down.

But exhaustion is only part of the story.

Something far more insidious is also happening. And it may be more consequential in the long run.

When we spend enough time operating inside systems that value speed, output, and optimization above everything else, we don’t just get tired. We start to lose our relationship with the things that make work — and life — meaningful.

The sense of purpose that comes from doing something that genuinely matters. The satisfaction of thinking something through slowly and arriving somewhere real. The quality of attention we bring to the people around us. The capacity to sit with complexity long enough to understand it rather than just react to it.

These aren’t soft extras or luxuries. They are the core of what allows human beings to stay adaptive, creative, and fully alive inside a rapidly changing world. And they are precisely the capacities that get crowded out when the nervous system is permanently running in survival mode.

There is also a deeper question about identity that rarely gets named directly.

For most of human history, work has been one of the primary ways people answer the question — who am I? We often describe ourselves by our work — what I do, what I’m good at, what I contribute, what I’m needed for. AI is disrupting that answer faster than most people have frameworks to handle. Not just economically. But psychologically and existentially.

When the thing you built your professional identity around can be done faster and cheaper by a machine, the question isn’t only will I still have a job? It’s something more fundamental and threatening. The question becomes:

What am I worth? What do I contribute that actually matters? Who am I if not what I produce?

Those questions are what will make the difference between humans being swallowed up by the systems they created and flourishing alongside them. And they aren’t being thought about nearly enough.

So what do we actually do with this?

The answer exists at two levels. And both matter equally.

For individuals:

The most important thing you can do right now is also the thing that feels most counterintuitive inside a speed-optimized system.

Slow down intentionally. Not as a reward for finishing everything. Not on vacation once a year. Regularly. Deliberately. As a non-negotiable part of how you work.

This means learning to disconnect — genuinely, completely, not just physically away from a screen while still mentally tethered to it. It means creating protected time for slow, deep thinking — the kind that doesn’t produce an immediate output but builds the judgment, creativity, and wisdom that no AI can replicate. And it means learning to recognize what your nervous system is telling you and responding to it before it reaches the point of breakdown.

Heart rate variability research — one of the most robust indicators of how your body is handling stress — consistently shows that nervous system regulation isn’t a luxury. It’s the foundation of cognitive performance, emotional intelligence, and resilient decision-making. You cannot think clearly, relate well, or contribute meaningfully from a nervous system that never gets to recover.

This isn’t self-care in the bubble-bath sense. This is performance in the deepest sense. The kind that’s sustainable over years, not quarters.

For leaders and organizations:

So far, society has seen this as individuals needing to become more resilient. But at some point we need to stop helping individuals adapt to increasing stress and challenge and begin asking questions about the systems we are asking them to adapt to. Asking individuals to do this alone is ineffective and unfair, and ultimately leads to the opposite of what organizations want to achieve: a more productive organization.

If you are implementing AI in your organization and your people are becoming more fragmented, more burned out, and more disconnected — the answer is not more resilience training or another productivity tool. The answer is looking honestly at the conditions you are creating and asking a different question entirely:

Does this environment actually support human beings doing their best work?

The research says most don’t. And it also says what works.

The Berkeley researchers who conducted the HBR study make a specific recommendation: organizations need to build what they call an AI practice — intentional norms and routines that structure how AI is used, when it is appropriate to stop, and how work should and should not expand in response to new capability. Without such practices, the natural tendency of AI-assisted work is not contraction but intensification.

In practice this means things like:

Requiring a decision pause before major decisions are finalized — one counterargument considered, one explicit link to organizational goals made. This widens the attention field just enough to protect against the drift that AI acceleration produces.

Sequencing work to reduce context-switching — protecting blocks of uninterrupted time rather than allowing AI to encourage the simultaneous management of multiple active threads.

Protecting time for genuine human connection — not task-focused collaboration, but actual relationship. Talking about something other than work. The relational tissue of a team is what holds it together under pressure. It requires deliberate tending, especially when AI makes it easy to substitute digital interaction for human presence.

Setting explicit boundaries on work expansion — making clear that AI capability does not automatically mean expanded workload expectations. This is a leadership decision, not an individual one.

McKinsey Health Institute’s Thriving Workplaces report, produced in collaboration with the World Economic Forum, found that investing in employee health could generate $11.7 trillion in global economic value — with improved productivity and reduced presenteeism accounting for up to 77% of that opportunity. Wellbeing is not a soft initiative anymore. It is a performance strategy.

Start with recovery. Movement and breathing microbreaks have an immediate impact on performance, energy, and cognitive function when taken throughout the workday. Interrupting long periods of sitting with just two minutes of movement helps protect and restore the brain’s energy and cognitive capacity. These aren’t indulgences. They are biological necessities.

The physical environment matters more than most leaders realize. Research confirms that cognitive recovery effects can occur in as little as 27 seconds of viewing greenery — making even brief nature views effective for cognitive restoration. Plants, natural light, and quiet spaces are not aesthetic choices. They are functional investments in cognitive performance.

And perhaps most importantly — give people permission to slow down. Organizations emphasizing proactive mental health programs saw 32% fewer disability claims and higher productivity. Prevention is cheaper than recovery. Always.

The organizations that figure out how to let humans work at the speed of humans — while letting technology work at the speed of technology — will not just retain better people. They will produce better outcomes. More creativity. Better judgment. Greater resilience when things get hard.

This is not soft leadership. This is intelligent leadership. And the data says so.

We are at an inflection point.

Not just technologically. Humanly.

The systems we have built are extraordinarily powerful. And they will keep getting more powerful. That is not the question. The question is whether we will build the human conditions that allow us to work alongside that power without being diminished by it.

The exhaustion is real. The fragmentation is real. The question of what’s wrong with me is real. This is not a personal failing. It is what happens when human beings are asked to run at a speed they were never designed for, inside systems that were never designed with their wellbeing in mind.

But here is what is equally true.

Human beings are not passive recipients of the systems around them. We built these systems. We can redesign them. And we can choose — individually and collectively — to stop measuring human value by machine standards.

Mental, emotional, and nervous system health are not luxuries. They are not soft extras for people who have time for that sort of thing. They are the biological foundation of everything organizations actually want — creativity, judgment, resilience, innovation, genuine collaboration, and the capacity to navigate complexity without breaking down.

You cannot optimize your way to those things. You cannot automate them. You cannot extract them from people who are running on empty.

They emerge from human beings who are regulated, connected, and given the conditions to think slowly and deeply as well as quickly and efficiently. From workplaces that understand the difference between the speed of technology and the speed of human integration — and design for both.

The future does not belong to the organizations that move fastest. It belongs to the ones that figure out how to move wisely. With their people intact. Fully human. Fully alive.

That is not a utopian vision. It is a practical one. And it starts with a decision — in individuals, in leaders, in organizations — to treat human flourishing not as a nice to have.

But as the whole point.

Most people experience overwhelm as a personal problem. Too much on the plate. Not enough discipline. Poor time management.

But overwhelm is rarely just a personal failure. It’s usually a systems load problem — the cumulative result of multiple streams of demand hitting the nervous system simultaneously without enough space for recovery.

When we look at it that way, we can begin to change the question from “what’s wrong with me,” to “what’s actually driving this?” In my experience, overwhelm tends to cluster around four main sources. And most people are dealing with more than one at a time.

Too much to do. Tasks, projects, commitments, and obligations that exceed available time and energy. This one is visible and easy to name. But it often gets addressed with more productivity strategies rather than with honest renegotiation of what’s actually sustainable.

Too much information. Notifications, news, email, media, and the constant low-grade demand of staying informed and responsive. The brain has to filter every piece of incoming information — relevant or not — and that filtering is metabolically expensive even when nothing feels urgent.

Too much screen time. Social media, addictive scrolling, screens before sleep. Beyond the content itself, screens keep the nervous system in a state of mild activation. The system never gets a clear signal that it’s safe to fully disengage.

Too much activation. Anger, outrage, and anxiety about external events. This is the most underestimated source. Emotional activation from things we can’t control — political news, social media conflict, global uncertainty — lands in the nervous system the same way immediate personal threat does. The body doesn’t distinguish.

What makes this a systems problem rather than a personal one is that all four sources are continuously amplified by the environments most of us live within. The same platforms optimized for engagement that keep us scrolling also maximize activation. The same workplaces that reward constant availability often create workloads no nervous system can sustainably handle.

The sources aren’t separate — they feed each other. Which is why addressing only one rarely creates lasting relief. The most useful place to start isn’t eliminating all sources of overwhelm — that’s not realistic. It’s identifying which stream is currently heaviest and creating even small amounts of intentional recovery from that specific source. Not because willpower fixes systems problems. But because even a little space changes what becomes possible.