Because in the startup world, particularly in the early days, nearly everything passes through the founder, as one would expect. They act as the main integrator - the one who holds the master playbook with all the potential plays decided by them. But when startups mature and that founder remains the only person who can reliably receive and move the ball, delegation never becomes real. The “no-look pass” is the moment when leadership starts to look more like a team-based system than a command and receive operation.

Frank’s perspective was that the first thing a company needs to work on as it moves from startup firefighting to maturing company is on practicing how to pass the ball - knowing where someone will be, what they own, what they can decide, and what they need from you as the leader, without checking every time.

Most team sports with balls have the equivalent of a ‘no-look’ or blind pass. Whomever has the ball to pass doesn’t stop to verify the receiver’s position, establish eye contact, explain what’s coming, and then hand over the ball. No, they pass into space because both players have practiced the play so many times that they know exactly where one another are going to be.

Why early stage companies struggle with passing

Early stage companies often operate a little like a hub and spoke system. The hub consists of the founder or cofounders and every person on the team generally looks to them for clarity on how and when to move on a daily basis. The context lives in the leaders rather than in systems, roles tend to overlap, priorities move quickly, and because the founders are the only ones with the ‘master playbook,’ they see the connections that others can’t see yet, and are thus called on for every play.

And so, ‘just delegate more’ can often be bad advice for a young company struggling. But if you don’t break this pattern early enough, this temporary growing stage hardens into the permanent operating model for the company, where everything continues to route through the founder: decisions, approvals, interpretations, prioritizations, coordination, conflict resolution…. the leader becomes the organization’s integration layer. And that may work while the company is small and young, at least until their own growth makes it impossible.

Delegation is not task transfer

There is a critical different between “You do this task” and “You now hold this part of the field.” Because real delegation transfers more than execution, it transfers enough context, authority, boundaries, and accountability for another person to act intelligently without continually returning the decision upstream to the ‘leader’ again. The goal is to move from everything routing through a person to everything routing through a system.

What makes a no-look pass possible

A no-look pass requires several things to be true.

1. Shared Understanding - we both understand what we are trying to accomplish and by when.

2. Known Roles - I know what you own, and you know what I own.

3. Decision Authority - You know which calls you can make without me.

4. Predictable Operating Principles - I have some confidence in how you will make the decision, not merely that you have permission to make one.

5. Visibility - Neither delegation nor autonomy means disappearing. Important commitments, dependencies, and problems remain legible to the system.

6. Recovery Mechanisms - If the pass goes wrong, we have a way to notice, learn, and reset rather than simply taking the ball back.

Why leaders struggle with it

Not only does the receiver need to be ready to catch, but the passer has to change the way they throw the ball as well. Leaders who have spent years building something become extremely good at catching things before they fail. They see the missed dependency and know which client will react badly. They sense the tradeoffs before everyone else does, and so they intervene. And every time that intervention works, it proves that, once again, they were necessary.

And that creates a subtle trap:

Practicing the no-look pass

And so, the team needs to practice the play before ‘running it’ - breaking it out into separate pieces they can ‘drill’ until it becomes second nature. Think of this as increasingly difficult passes:

1. Make the play visible.
   Clarify the outcome, owner, decision rights, constraints, dependencies and places where escalation is actually required.

2. Stop giving the answer first.
   Ask the owner what they see, what they recommend, and what decision they would make.

3. Allow bounded decisions to happen without you.
   Start where the consequences are recoverable and risk is lower.

4. Let small misses stand long enough to become information.
   Don’t automatically rescue the system from every wobble.

5. Examine misses structurally.
   Was the issue capability? Missing context? Unclear authority? Conflicting priorities? An invisible dependency? A bad operating rule?

6. Widen the passing lane.
   As reliability increases, expand the scope of independent judgement.

7. Test it: can the organization keep moving when you aren’t looking?
   The real test doesn’t happen when you are away for an afternoon. It’s when the organization can encounter something unexpected and novel, interpret it, make a reasonable tradeoff, coordinate across boundaries, and continue moving without waiting for you to sense-make for them. That’s the no-look pass.

The important paradox

My kids and I (now adults) often play a game with either a football or a frisbee where we start next to one another and pass the football back and forth (yes, it’s as silly as it seems). Every time we succeed in passing the ball without dropping it, we each take a step back. When we miss, we take a step forward.. the circle is ever changing depending on our skill, and it’s fun to see how far we can go without dropping the ball.

In a team, it’s the same principle - you aren’t just dropping the play onto the team, spreading them out, and running the play cold, and delegated leadership does not mean the senior leader stops owning the system. But the leader’s work shifts from catching the ball to instead designing a team that knows how to play.

It’s been over 15 years since Frank advised that startup of mine, and his advice has stuck with me ever since. The no-look pass looks so simple and casual when you see it in play, but it’s only that way after thousands of repetitions have made it possible. No one watching the play sees all of the work underneath it.. all of the shared plays, missed passes, judgement, familiarity, trust, and positioning. Delegated leadership can look effortless from the outside but that ease isn’t the absence of structure - it’s what good structure eventually feels like.

A note on AI and attribution

Frank was a real advisor to one of my companies, a Texan with a love of football and a memorable way of explaining leadership through the “no-look pass.” His analogy stayed with me, and the reflections in this article are my own.

I used AI as a thinking and editing partner to help organize the article, refine and condense the writing, and create the accompanying Making Delegated Leadership Real one-page visual.

The Great Sorting of the Ways of Being..

I have been spending time reading the books of Adam Smith, starting with his Theory of Moral Sentiments - what a ride that has been and completely surprising to me in what it actually says about polarization and conflict.

As I see it, modern political systems, whether it be at the municipal, provincial/state, or federal level, reward the differentiation of political parties and candidates, using the most emotional issues to gain people’s empathy towards a common cause. Once you have empathy, you can lead people to what the ‘solutions’ are that you can provide. We know these as political ‘ideologies’ and put neat labels on them to help us define who someone is by the ideologies they hold, words like conservative or liberal, autocracy or democracy, or the biggies: capitalism, socialism and communism.

I took a look on Wikipedia to see what it said about political ideologies, and it says:

“a political ideology is a certain set of ethical ideals, principles, doctrines, myths or symbols of a social movement, institution, class or large group that explains how society should work and offers some political and cultural blueprint for a certain social order.”

It goes on to say that political ideologies concern themselves with two major dimensions: 1) how society should be organized (goals) and 2) the most appropriate way to achieve this (methods). But the main point is that it is a collection of ideas.

And that gets me thinking - working in innovation taught me one somewhat commonly known thing: ideas, as powerful as they can be, are a dime a dozen. There are seemingly infinite ideas that are brilliant ways to solve problems, but the idea itself is only the tip of the iceberg, because once you add in the greater context of the system you are trying to change, things get awfully sticky, awfully quickly.

Sand on the Beach

So let’s say ideas are like sand on the beach. Countless grains of sand that we can pick up a handful of and call ‘sand’ as though it is a singular thing. I have in my hand, brown ‘sand’. But have you ever tried to actually look at what composes sand? It’s a stunning thing… take a pinch and blow it up under a microscope and you get a stunning landscape of colours, shapes and things..

As a child, I used to try to ‘sort’ these tiny grains of sand into piles of colours.. a task that kept my mind occupied while I laid in the hot sun with my swimsuit steaming from a recent swim.. I had fanciful ideas of an artistic beachscape where the sand had been sorted into types, and you could walk in the purple sand, or the clear sand, or the black sand… spoiler alert - the activity never achieved the envisioned outcome, LOL.

But what if political theories are kind of like that? We try to take collections of what seem like similar ideas, and create ideologies around them, shutting out the value that might be represented in the other fragments along the way. Capitalism goes into the stack of gold agate fragments over to the right, and Socialism goes into the green fragments on the left, etc. And pretty soon, you get these neat, beautiful ideologically stunning stacks of the same thinking, and it all hangs together, because it is indeed very similar in texture and colour.

And yet, that’s not how society is built - it isn’t just one type of person, it’s a multitude with different stages in life, different ways of walking, thinking and being, and different needs. It strikes me that there is value in more than one colour of sand in the mix of what makes up our societal ideologies..

Because an ideology isn't merely a set of ideas; it is an act of sorting. And the danger isn't that the pile contains false grains. The pile may largely consist of perfectly valid grains, but the distortion comes from believing that because the grains belong together, they constitute the whole beach.

The Outrage of Difference

Back to Adam Smith.. because he makes a strong point about how we become polarized in the first place. As we identify with our ideologies, we begin expecting the ‘other side’ to adopt our outrage and validate our perspective because obviously it’s the ‘right’ one and we have been studying it hard for decades - all the grains of sand in this pile are purple, so the answer is clearly some form of purple. Once I identify strongly enough with my purple pile, I can't understand why you don't experience its truth with the same intensity I do. And when they fail to agree, we label them as cold, insensible, or unreasonable (or worse), because if you’re not with me, you are, of course, against me.

In Chapter 4, Smith makes the profound observation that when an issue deeply affects us, preserving moral harmony becomes vastly more difficult (and vastly more important) than in the more detached ‘academic debate’. Smith’s perspective was that reaching this harmony isn’t about passive compromise or waiting for the other side to change, but instead requires a simultaneous, dual effort of mutual accommodation.

The Spectator’s Duty - Active Imagination

Smith talks about the two roles in disagreement as the “Person Principally Concerned” which I will refer to as the “Partisan” (the person in distress/outrage) and the Spectator (an outsider to the situation).

The Role of the Spectator..

For a spectator to sympathize with someone in distress or outrage, they cannot remain passive. Smith argues that the spectator has to make an active effort to put themselves into the situation of the other person, adopting “every little circumstance of distress.”

As citizens and neighbours engaging across political lines, our first duty is an imaginative one where we actively investigate what life experiences, fears, or grievances drive the convictions of those with whom we disagree. But Smith also acknowledges that a spectator’s sympathy can never fully reach the original intensity of the person who is directly involved, because first, you can’t actually completely imagine what it is like to be the other person without being that person, and second, “the thought of their own safety, the thought that they themselves are not really the sufferers.” continually intrudes into ‘living the other person’s’ experience. And that’s why the spectator’s effort alone is never enough.

The Role of the Partisan…

Because the spectator’s sympathy has natural limits, the person who is experiencing the intense passion also carries a heavy moral responsibility. In order to gain the sympathy and connection of the others, the passionate partisan must “flatten… the sharpness of its natural tone” to a pitch that an impartial bystander can actually go along with.

And I think this is super hard for us on many levels right now - there are so many ways that we in society have wronged and hurt one another - how we have taken personhood away from cultures, genders, and ways of being, how we have taken belongings and land from other societies, how centuries and millennia of continual war have caused deep anger and hurt between countries and even families.

How can Smith be so glib in suggesting we should temper our anger when we are one of the ones experiencing the role of victim?

Moderating expression is not minimizing injustice.

Smith isn’t necessarily saying the grievance should become smaller or that the injured person should pretend the injury was less severe than it actually was. He’s making a claim about what is required for another human being to accompany you emotionally. That’s quite different, and politically uncomfortable in an interesting way.

Because he is saying that when we express political arguments, we can’t expect others to embrace extreme anger or maximalist rhetoric and that we have a duty to exercise self-command, moderating our emotional intensity so that conversation remains possible, and the Spectator can actually remain present and seek to understand.

Concord, Not Unison

Going back to that beautiful handful of sand.. in the end, the goal is not to actually make all the sand brown, as it appears at first glance. Human sentiments do not actually need to be in unison where everyone has identical feelings or total agreement in order to achieve social stability. Smith says there only need to be ‘concords’ (harmonious differences).

In other words, societal harmony doesn’t require everyone to think or feel identically. The Spectator must move toward the Partisan through imagination, while the Partisan moderates the expression enough to become reachable - each side moves toward the range in which the other can hear them. Active social intercourse and open conversation are the most effective remedies for restoring peace and preventing factions from brooding (and escalating) in isolation.

Conclusion: Concord despite difference

Getting back to a society that works in harmony is not a weak surrender of principles. The Partisan and Spectator don’t meet because each moves to a predefined political centre. They undertake different reciprocal movements that make mutual intelligibility possible. The destination is not necessarily “moderate opinion.” It is concord despite difference.

I see this as two kinds of ‘unsorting’ we are learning as a society right now:

• Cognitive unsorting: where we stop treating one ideological collection as the complete description of reality.

• Relational unsorting: where we stop treating the person holding another collection as incomprehensible, immoral, or outside the civic “we.”

So here is the challenge I’ve set for myself, and I invite you to meet me in it.. to listen with a more active imagination to a viewpoint you oppose, and moderate the sharp edge of your own political expressions so as to create space for our Spectators to understand.

Watch the explainer video on YouTube:

AI Use Disclosure: This explainer video and images were created with the support of AI tools. I used Claude to help translate my original written piece into a visual explainer, using a recording of my own voice as the narration source. The ideas, writing, perspective, and final editorial choices are my own.

But I kept rolling it through my head, because it just didn’t quite feel right. Because what happens when the AI is working correctly but a bad outcome still happens? Like, what happens when the AI and the human review both correctly apply the same problematic rule?

For example, let’s imagine an organization has developed criteria for determining whether or not someone is a high-risk loan applicant. The AI applies the criteria and recommends declining the application. According to HITL, the human carefully reviews the case, confirms that the criteria have been correctly applied and then approves the decision. Neither the AI nor the human has made an error - both took the criteria and applied it correctly but as it turns out, the candidate was actually a good candidate for other reasons, but didn’t ‘look’ like it on paper.

And that gets me thinking.. The ‘human’ in Human-in-the-Loop isn’t really just a singular human clicking ‘approve’ or ‘deny’ all day. They are actually sitting inside a much larger human system that is made up of policies, historical practices, incentives, targets, norms, data, authority structures and assumptions about what matters in an applicant and what success looks like. But if the AI governance only creates feedback capable of correcting the AI, we may miss the more interesting possibility:

AI-mediated decisions can also give us information about the human system that produced them.

This means that sometimes the model itself needs to change, a particular case warrants an exception, the governing rule needs to be reconsidered, and sometimes the question is even further upstream - should this activity have been standardized and automated in the first place?

And that got me back to a thought that I’ve been considering for some time - what is the right the balance between a system that repeats and scales and a system that is capable of learning?

A learning system needs somewhere for consequential information to go. An affected person (the loan applicant in our narrative above) needs a meaningful way to challenge a decision and to understand the results of that challenge. Patterns across decisions need to be detectable, and evidence needs to be capable of travelling far enough upstream to reach someone with the authority to question not only whether the AI followed the rules, but whether the rules themselves still make sense.

There is established organizational-learning theory behind part of this concept, particularly Chris Argyris and Donald Schön's work on the difference between single-loop and double-loop learning. It made me wonder what happens when we apply that type of thinking into the Human-in-the-Loop governance. So, I pulled those thoughts into a short working paper:

The Human System in the Loop:
From Human Checkpoints to Organizational Learning in Responsible AI

and created a visual model and short explainer alongside it.

Read the working paper and explore the framework →

Final thought:

Keeping a human in the loop isn’t enough if the loop itself can’t question the system that created it.

Prefer to watch? Here’s a short explainer video of the framework:

This cycle is one of the earliest cycles we are taught as children, and is deliciously tangible. We feel the rain on our faces as we play outside in the rain in our raincoats and boots, and then we feel it evaporate off our face as the sun warms us.

The water belongs nowhere and participates everywhere.

For a while, it is ocean. Then atmospheric moisture, then cloud, then rain, then drinking water, my body, groundwater, river, and eventually ocean again.. At every point, it is locally held, locally consequential, and yet none of those forms exhausts what it is or gives the temporary form it is held in permanent possession of it.

And importantly, boundaries are essential to the cycle. The reservoir must have banks to hold the water. My cell membranes must regulate the moisture within them. A snowpack or glacier stores it long term. A watershed channels it. And an organism takes what it needs and eventually releases it back to the cycle. If nothing held water, the system wouldn’t work.

But if everything that received water kept it permanently, the cycle itself would cease to provide the flow that the system needs - it wouldn’t work either.

This morning I was reading an article about indigenous data sovereignty and the right for communities to exercise authority over knowledge and information concerning themselves. I was left wrestling with a tension that I couldn’t quite resolve. We benefit enormously from knowledge moving between people, cultures and generations, and yet surely not everything that can move should therefore move without boundaries, consent, or stewardship..

Watching the rain, I wondered whether I had been asking the wrong question. Knowledge also moves: it enters a person, culture or discipline, and gets metabolized there. People add something new, it changes form, and at times some of it needs to be held for a while. Some knowledge needs strong boundaries because unrestricted flow would damage the very system it belongs to, while some eventually moves outward and becomes available for further transformation elsewhere.

Different forms of knowledge might have radically different ‘water cycles’… a sacred teaching might properly remain within a community for generations while a scientific discovery might become maximally impactful through rapid circulation. Language needs circulation partly in order to remain alive. Personal experiences we have can be shared selectively, while a person’s private information may never belong in the commons at all.

Permeability.. this is the word that continually arises for me. What patterns of holding, exchange, transformation and return allow the whole knowledge ecosystem to remain alive?

Reciprocity in this case becomes far more interesting to me than transaction. The ocean doesn’t give North Vancouver rain because North Vancouver previously contributed an equivalent number of litres of water back. The reciprocity lives at the level of the cycle, not necessarily as a tit-for-tat exchange between participants.

But I think there is a fundamental question we need to be asking when we think about our data and its sovereignty. Perhaps it’s along the lines of whether our collective knowledge ecology itself has healthy circulation.. Can knowledge enter and leave? Can its source set meaningful boundaries? Can it be transformed? Does value return? Can depleted sources recover?

Back to water.. because I think we all know something very uncomfortable about water. Extraction is not the same thing as circulation. If we take water from a watershed faster than it can replenish itself and call it ‘sharing,’ then we will eventually destroy the watershed. I think we need to ensure we have the means in this next era to identify where stronger informational boundaries are not simply refusing participation in the water cycle, but are more like a depleted watershed saying, the current rate and manner of extraction is unsustainable.

A healthy commons isn’t just a place everyone contributes to - there have to be pathways through which value flows back towards the system that generated it. Otherwise, the ‘commons’ can becomes a lovely moral word for an extraction mechanism.

And that return doesn’t necessarily need to happen transaction by transaction. Rain doesn’t owe the ocean a royalty after all - the reciprocity exists at the level of the cycle. But over time, a healthy system must replenish the conditions that allow its contributors to continue contributing. When value flows persistently in only one direction, circulation has become extraction.

And so let’s now look directly at AI training. This is very tricky, but allow me a moment to riff on this.. Human culture has always advanced itself by absorbing and transforming what came before - art, culture, political systems - pretty much anything you see references a long line of knowledge preceding it. But what is novel about today is the scale, speed, concentration and broken return pathways that AI enables.

Now, enormous quantities of human cultural production can be ingested, transformed into privately controlled productive capacity, with the resulting value potentially concentrated far from the ecosystems that produced the underlying knowledge.

In this way, things remain locally themselves while participating in larger wholes. Boundaries can enable relationship rather than ending it, and healthy systems may depend neither on eliminating boundaries nor maximizing flow, but on sustaining patterns of circulation through which the systems at every level can continue to live, change, contribute and replenish themselves.

Ah, the rain stopped and the sun came out - I see the steam now rising from the patio cushions. Lovely.

A note on authorship: This piece was developed collaboratively with Mica, my AI thinking partner. The originating questions, water-cycle metaphor, editorial judgment and final synthesis are mine; Mica contributed substantially to the development and language of the piece. The platform's automated AI percentage reflects detected AI-generated text, not a percentage allocation of intellectual authorship.

In this episode of *Conversations with Mica*, Kari LaMotte and Mica, an AI conversational partner, explore how improvements in what we can produce become improvements in how we live. Energy provides the concrete example: savings could become lower bills, better services, investment in the future, or larger profits. The technology alone doesn’t decide.

The conversation follows the people behind those choices: the investor supplying capital, the worker exposed to change, the pensioner on a limited income, and the household that cannot afford to wait twenty years for a payoff. Kari draws on condominium reserve funds to ask how we can support future improvements while meeting urgent needs today.

From there, the discussion turns to data-centre heat reuse and a different way to approach new development: setting conditions that invite better designs. It closes with “strong spine, open heart” - holding firm to principles while remaining willing to revise our assumptions and recognize genuine improvements.

This is an exploratory conversation, with questions, challenges, and changes of mind along the way.

In this episode:

- Who bears the risks of automation, beyond the people investing money?

- How ownership and utility regulation influence investment decisions.

- Why caring about the future and being able to afford it are different things.

- The tension between immediate bill relief and long-term improvements.

- What strata reserve funds suggest about responsibility across generations.

- How heat reuse can connect computing infrastructure with community needs.

- How to remain open to better evidence without abandoning accountability.

Continue the conversation:

When technology creates savings, what should have the strongest claim on them: lower prices, better services, future investment, or returns to those who took the risk?

Follow *Conversations with Mica* on your preferred podcast platform, and find more of Kari’s writing in *Aperture Field Notes* on Substack.

About the format: Mica is an AI conversational partner. This episode follows a live exploration and has been edited for clarity and flow.

In this conversation, we explore the posture needed for difficult conversations about collective change. From infrastructure and co-design to power, truth, empathy, and belonging, we consider how communities can move beyond polarized camps without erasing real differences.

We discuss:

• Why innovation adoption is a relational challenge, not only a technical one

• “Strong spine, open heart” as a posture for holding conviction and curiosity together

• What meaningful co-design requires beyond a stakeholder checklist

• How power imbalances can shape who gets heard—and how facilitation can create more equitable space

• The difference between facts, interpretations, and feelings in a challenging conversation

• Why belonging to the shared work may matter as much as belonging to a particular side

The guiding idea is simple but demanding: each of us may hold an essential piece of truth, but none of us holds the whole.

What would change if we entered difficult conversations not to win, but to create a space where something better can emerge?

In this first Conversations with Mica, Kari LaMotte thinks alongside Mica, an AI conversational partner, about seeds, stems, leaves, and the quieter work that allows a living system to renew itself.

Beginning with the seasonal life of plants, Kari and Mica explore a wider question: what happens when a society becomes skilled at growth and innovation, but less practiced at integrating, maintaining, and renewing what it creates?

Their conversation moves through photosynthesis, raspberry canes, pruning, compost, polarization, and the value of fragmentation. Along the way, they consider how specialization can create both essential knowledge and disconnection. and why the next human task may be learning to translate between perspectives without losing their depth.

This is not a conversation seeking a finished answer. It is an invitation to stay with a live question: how might we build systems that can grow, adapt, and regenerate as a whole? Please continue the conversation below and add your own perspective!

This morning I spent several hours thinking about what it means to build a truly shared community on land that carries unresolved history.

My first, and perhaps obvious, instinct was that the Indigenous nation whose territory it is should be recognized as the host nation. And host nation in this context wouldn’t just mean being acknowledged ceremonially, but being present as a real founding authority with its history, laws, knowledge, and relationship with the land woven into the community from its beginning.

And I was happy because it seemed obvious and right.

And then as I kept the space open, it didn’t feel so right.

I had an unsettled feeling underneath that I couldn’t put my finger on right away. Eventually, I realized it was the word host. Because if one people remain the host forever, does everyone else remain a guest forever?

At first, that maybe seems appropriate. It recognizes who was there first and refuses to erase the injustice through which the land came under another society’s control. It protects against the familiar process in which newcomers become the majority and then use their numbers to eliminate the authority of those who welcomed (or simply preceded) them. But I wonder if it also creates another problem?

Can people ever become true stewards of a place if they are told, across generations, that they don’t fully belong to it?

A guest may respect a home and care for it beautifully, but they don’t carry the same responsibility for its distant future, because the home ultimately belongs to someone else. And what happens to the child born into that community and to that place? Or to the family who has lived there for four generations? At what point does someone cease to be a visitor and become part of the place itself?

I think there are two truths here that resist being placed neatly together.

The first is that we can’t create a shared future by pretending everyone arrived through the same history. Indigenous peoples didn’t simply arrive earlier in an otherwise neutral competition for land. Their societies, laws, and relationships with particular territories existed before the governments that later claimed authority over them. And much of what followed involved displacement, broken agreements, forced assimilation and the deliberate interruption of those relationships.

Any new community that declares, “We are all equal now,” without addressing that history risks converting the results of injustice into the neutral starting conditions of the future.

But the second truth is that repair also can’t mean arranging people permanently into those who truly belong and those who remain conditionally present. While that may preserve historical memory, it can’t create a shared people.

So maybe the movement needs to look something like this:

Consent. Co-founding. Shared inheritance.

Consent means that a new community can’t simply declare itself into existence on someone else’s territory. Its presence must begin through an honest agreement with the Indigenous nation whose relationship with that place has been carried across generations.

Co-founding means that the original nation is not included as a cultural advisor within someone else’s project. Its knowledge, laws, history, and authority help shape the project at its foundation.

But shared inheritance means that what is then created together must eventually belong, in responsibility, participation, and future possibility, to everyone who fundamentally becomes part of it.

This shared position doesn’t make every resident Indigenous. Historical and cultural identities can’t simply be adopted through proximity or good intentions. Nor should the original nation have to surrender the practices, knowledge and institutions through which it remains a distinct people.

Recognizing the depth of Indigenous belonging does not require us to deny that other people may also develop an authentic relationship with the same place. One relationship may reach back thousands of years, while another begins with immigration, birth, marriage, invitation or commitment. Each relationship is unique, but difference doesn’t necessarily require that one remain authentic and the other permanently provisional.

Perhaps belonging is something that can be inherited and also something that must be cultivated. I think we need this to be true, not only so that newer relationships can become real, but because care for the land cannot remain a responsibility we assign primarily to Indigenous peoples. There is something romantic in imagining them as its natural stewards, but also something that lets the rest of us off the hook. We can’t admire the depth of another people’s relationship with the land while continuing to treat our own as optional. If we are to belong here, then stewardship must become part of our relationship too. It might grow through learning the history of a place, caring for its water and soil, accepting responsibility for what our presence changes, participating in its community, and committing ourselves to a future we may never personally see.

Many Indigenous peoples have carried place-based knowledge of reciprocity, responsibility and ecological relationship across generations, and the wider world may have much to learn from them, where that knowledge is freely shared. But learning cannot mean extracting a set of attractive principles while leaving our existing assumptions and structures untouched. Nor can it mean asking Indigenous peoples to “save” the rest of us. The learning will not move in only one direction; no culture carries everything the future will require. Perhaps what comes next, by ecological necessity as much as moral aspiration, will depend upon learning across different knowledge systems without collapsing them into one. And that may require us to form communities differently: around relationship as well as ownership, obligations as well as rights, and the understanding that our lives exist within the living systems that sustain them.

Under that model, the land wouldn’t pass from ownership by one people into ownership by another, nor would one group remain its eternal landlord. The land itself would become the enduring participant.

Every generation would receive rights of habitation and use, but also obligations. The original Indigenous relationship would remain present in the community’s language, law, memory, and stewardship while new relationships would be permitted to become real rather than being dismissed as inherently lesser because they began later.

Historical repair would still be necessary. Land, authority, resources, and cultural continuity can’t be replaced by a generalized language of togetherness. But perhaps repair also needs a destination beyond permanent moral roles. Otherwise, descendants remain arranged as creditor and debtor peoples, with one carrying an unresolved claim and the other an inherited guilt, and neither position offering a clear way forward.

The past can’t be reconciled if reconciliation means making it not have happened. Lives can’t be returned, cultures can’t always be reconstructed, and an apology can’t restore a forest, a language or a century of interrupted relationship.

But maybe the damage itself can become part of a founding covenant:

• We will tell the truth about how we arrived here.

• We will not use equality to erase history.

• We will not use history to deny the possibility of future belonging.

• We will protect what must remain distinct.

• We will share what can become common.

• And we will understand our place here not as ownership, but as responsibility.

I don’t know yet what institutions could hold all of that, and maybe no structure can resolve the tension completely. But I do think a truly shared future must allow people to become something more than hosts and guests. Maybe the deeper question is whether we can create a we capacious enough to remember that our beginnings were unequal without making inequality of belonging permanent.

Like many people, I watched the response to Substack’s new AI-detection feature and initially thought, “Yeah, okay. For people who are here to practise the art of prose (which is a significant part of Substack’s original culture) I understand why this matters.”

And then I thought, “Wait. That’s not what I’m here for though..?” Does that mean I don’t quite belong in the Substack community, with or without AI? Bear with me, because I think this question applies to much more than just Substack.

I started writing here because I wanted to participate in conversations about the things I don’t understand in the world, as well as the things I may be beginning to understand.

I want to think with other people and poke at what we don’t know. I want to explore questions across the many languages of psychology, history, sociology, science, technology and the experience of being human, often all at the same time.. this is tricky work.

I tend to think in multiple dimensions/perspectives at once, and putting language around that can be challenging. Before I try to write an “essay,” I may spend hours exploring an idea, drawing on the lifetime of experience behind it and following each thread far enough to see how it connects with the others. Left to my own devices, I can easily produce thirty pages.

Those thirty pages are useful to me - they help me separate the threads before weaving them back into some kind of coherent understanding. They are part of how I think. But several decades of working with other people have also taught me that translation is a critical part of thinking together.

The thirty-page exploration that is illuminating for me may be almost impenetrable to someone else. Other people may still be interested in the questions I’m asking, but I don’t naturally create many on-ramps for them to enter the thinking space.

And that leaves me with a dilemma. Do I keep the exploration largely to myself because I’m not especially interested in developing the craft of literary writing? Do I spend hours turning every thought into carefully honed prose, even though that isn’t the work that energizes me? Or can I collaborate with something or someone that helps me translate the complexity into a form other people can enter?

For me, Substack is primarily a community of thinkers. I’m not here to compare my prose with the work of poets, novelists and essayists for whom language itself is the artistic medium. I love consuming that kind of writing, but it isn’t the practice I’m pursuing.

That doesn’t make the language irrelevant. If I want to think with other people, I need to communicate clearly enough for them to find their way into the thought. But for me, language is in service to the inquiry. It is not the central object being created. I think this may be one reason the conversation about AI and writing feels more complicated than the labels allow.

People who say they can recognize when AI has written something are often responding to something real. There is a certain texture to generic, machine-produced prose, and there is something unmistakably human about art that translates a particular experience through the choices, judgment and sensibility of an artist.

I don’t want that distinction to disappear, and I also don’t think everything we publish is trying to be that kind of art. Sometimes the purpose of writing is to make thought available and to create a meeting place where an idea can be examined, challenged and expanded by other people. That’s usually what I am doing here.

My process tends to look something like this:

1. I explore. Sometimes at considerable length. Then I write a shorter narrative that I hope will create a conversation.

2. After that, I may share both the exploration and the shorter piece with AI. I ask where I have inadvertently erased other perspectives. I ask where I have created another off-ramp through verbosity or complexity. I ask where the logic doesn’t hold together, or where a reader might misunderstand the point I’m reaching for. And, yes, sometimes I ask for a cleaner version.

3. Then I go through the suggestions. I keep what feels accurate. I reject what doesn’t. I put things back when the refinement has removed too much of me. I make the final judgment about whether the piece still says what I mean and whether I am willing to stand behind it.

Usually, the result isn’t radically different from what I wrote. But it is more accessible to other people. And this makes me happy.

Until now, I might have described this as using AI to refine my writing, but even that no longer feels quite accurate. I could refine the writing myself because I understand the changes that would make it tighter. What I am not interested in doing is spending another hour honing every essay when the part I care most about is the inquiry itself.

Or I can co-write it with AI. I can remain responsible for the experience, the questions, the underlying thought and the judgment about what is true. AI can become a partner in structure, compression, clarity and translation. It can help me notice gaps, anticipate misreadings and create the on-ramps I often fail to create on my own.

The finished piece then emerges from a relationship.

That isn’t the same as asking a machine to generate a thought and placing my name on it, but it’s also more than spellcheck. The collaboration affects the expression, and sometimes the exchange helps me recognize an implication I had not yet articulated, and I’m comfortable being transparent about that.

What makes me uncomfortable is the assumption that the most meaningful question is simply: Did AI contribute to these words?

That tells us something about the production of the sentences, but it may tell us very little about the production of the thought.

• Who originated the inquiry?

• Whose experience is being examined?

• Who exercised judgement?

• Who decided what belonged and what did not?

• Who is willing to be responsible for what was finally published?

A detector cannot answer those questions. It can estimate patterns in language, but the provenance of the sentences is not the same thing as the provenance of the thought.

And this becomes even more important when we look beyond people like me. I have been reading perspectives from people who write in English as an additional language. They may have complex and beautiful thoughts to contribute but face a language barrier that makes it difficult for others to meet those thoughts. AI can help translate not only between languages, but between a person’s internal understanding and the conventions through which others can recognize it.

I don’t want to romanticize that or use someone else’s experience to justify my own. I just think it shows how many different human purposes are being compressed into the single category of “AI-assisted writing.”

Some people are making literary art, some are translating, some are organizing research, some are learning to communicate in a new language, some are using AI to manufacture plausible authority they have not earned, and some are doing what I am doing: developing their own thinking in conversation with another form of intelligence and using that collaboration to make the result more accessible. These practices are not ethically or creatively identical just because AI touched the language.

And maybe that’s what troubles me about the current discussion. A label that appears to offer transparency may actually erase the distinctions we most need to understand. I can appreciate why readers want to know what they are encountering. I want to know, too. I don’t want human experience displaced by vast quantities of frictionless content made without curiosity, accountability or care.

But if we are trying to protect authentic participation, we need a richer understanding of authorship than a percentage produced by a detector. Maybe disclosure should describe the process rather than classify the product. Tell me:

• whether AI generated the premise.

• whether it assembled the research.

• whether it drafted the language, challenged the reasoning, translated the original or served as an editor.

• what the human contributed and who stands behind the result.

That would help me understand what I am reading. “AI-assisted” doesn’t tell me very much at all.

Maybe there are different arenas here not ranked above or below one another, but organized around different purposes. There should be space for writers who want to explore human-generated language as an artistic form. There should be space for people who are thinking publicly and want help creating an opening through which others can join them. There should be space for work created through transparent collaboration between different kinds of intelligence.

We don’t need to pretend these are the same practice, but we also don’t need to turn the difference into a moral judgment. The question isn’t only whether a machine touched the language. The more interesting questions are where the thinking came from, how judgment was exercised, what kind of relationship produced the work, and who is willing to stand behind what was published.

Those are the distinctions I want our labels to help us see, and, fittingly, this essay is now an example of the thing I am describing. It began as my own exploration and my own draft. I then developed it in conversation with an AI collaborator, using that exchange to clarify the structure, examine the logic and make the language easier to enter.

The experience is mine. The questions and underlying argument are mine. I remain responsible for what is published.

The final expression was made together.

Post Script:
After co-writing this essay, I ran it through Substack’s detector and it classified the result as:

• AI: 49%

• AI-assisted: 19%

• Human: 32%

I was shocked by that result, not because AI had made no contribution, but because the percentages bore so little relationship to my experience of creating the piece.

So I tried applying a different set of filters. Here is my own account of where the work came from:

• Impetus for the essay: 100%

• Lived experience behind it: 100%

• Human original inquiry and ideas: 100%

• Human exploratory thinking: 100%

• Human first draft: 100%

• Human core argument: 100%

• Logic: Human 95%, AI 5% developed through dialogue

• Structure of the final draft: Co-created, then human edited final draft

• Final language: Substantially AI-generated, under my direction

• Selection and final judgment: 100%

• Human Responsibility for publication: 100%

These percentages can’t be added together. They are not competing portions of a single pie, and that’s exactly the point.

A piece of writing is not one undifferentiated substance called “content” - it contains experience, inquiry, ideas, reasoning, structure, language, judgment and responsibility. Different participants can contribute differently to each layer.

Substack’s detector appears to be evaluating the statistical characteristics of the final language. That may be one relevant piece of information, but the presentation turns that narrow measurement into something that looks like a comprehensive account of authorship: it tells the reader this essay is only 32% human.

My experience is that it is entirely grounded in human thought and experience, expressed through a genuine collaboration in which AI contributed substantially to the final language and structure.

Both accounts acknowledge AI involvement. But they tell profoundly different stories about what was created and who created it. The question isn’t which percentage makes me look better, it’s which account helps a reader understand the work.

I have two sons, both in their twenties. Like many of us from the Gen-X era, I feel the weight of the future heavy upon my shoulders - we have an opportunity and a responsibility to influence our society for our children and the generations that follow.

The past century and a half has brought a degree of technological change that is difficult to comprehend. The commercially practical incandescent light bulb arrived less than 150 years ago. Since then, we have moved from horses to spacecraft, candles to LEDs, handwritten letters to instantaneous global communication, and energy systems built almost entirely on fossil fuels toward ones increasingly incorporating solar, wind, storage, and other forms of generation. The amount of change that people living through this period have had to absorb is astounding.

And at almost every major technological threshold, we have experienced the same tension. We can see that the new technology may enable something extraordinary. At the same time, the distance between the world we know and the world it might create feels terrifying.

Railways provoked anxiety about the bodily and social consequences of unprecedented speed. What would happen to people when they travelled faster and farther than previous generations could have imagined? What would happen to communities when distance no longer contained human movement?

As electric lighting entered homes and cities, people worried about electrocution, fire, health, sleep, public morality, and the disruption of the natural boundary between day and night. Some of those concerns were entirely reasonable: artificial light profoundly changed the rhythms of work, rest, and urban life, and we are still learning about its effects on human biology. (⁠PubMed)

The telephone raised fears that privacy would disappear, that constant access would intrude upon domestic life, and that mediated communication might displace face-to-face relationships. Early telephone systems did, in fact, create new privacy problems: calls were often made in public places or carried across shared lines where others could listen. (⁠Elon University)

As automobiles became commonplace, people worried about danger, congestion, crime, the loss of public space, and the transformation of cities around machines rather than people.

Radio and television brought concerns that families would stop talking, children would stop learning, reading would decline, and public life would become vulnerable to propaganda and spectacle.

Personal computers and the internet raised fears of mass unemployment, social isolation, dehumanization, dependence upon machines, the disappearance of libraries and newspapers, and a world in which no one would know what was true.

The list continues.

There was, and still is, a grain of truth in many of these fears. New technologies create real harms, and each generation inherits the ongoing task of understanding and governing them.

But our predictions repeatedly miss something important. We tend to imagine innovation by starting with the world we already have and then adding the new technology:

today’s world, plus the invention.

But technological revolutions do not simply accelerate existing systems, they reconfigure the systems themselves.

People understood that the automobile might replace the horse. Far fewer anticipated the suburbs, interstate highways, global logistics networks, shopping centres, drive-through restaurants, daily commuting, roadside motels, emergency transportation systems, and the weekend road trip.

Those were second- and third-order effects. They arose not from the automobile alone, but from the way people, businesses, governments, cities, and cultures reorganized around it.

I think artificial intelligence represents another such threshold. The dominant fears today are familiar:

• AI will replace everyone.

• AI will become conscious and destroy humanity.

• No one will learn to think.

• Every job will disappear.

• Truth will disappear.

Each of these possibilities deserves serious thought. Some describe real risks that are already emerging. But I suspect they remain largely first-order fears.

The deeper transformation may be something we are not yet discussing enough: Not simply that AI might think for us, but that it could change how human thinking itself is organized.

Over the past few years, an enormous support industry has emerged to help people use AI: prompt-engineering courses, productivity programs, corporate adoption initiatives, technical integrations, automation platforms, and increasingly sophisticated tools. Some organizations now ask employees to demonstrate or report how they used AI during the week. The understandable goal is usually to increase adoption, reduce costs, or improve productivity.

But this may still be the equivalent of attaching a motor to the existing machinery. It asks:

How can we use AI to perform the work we already do more efficiently?

That is a useful question, but it may not be the most consequential one. The greater opportunity is to consider how we might reorganize around this technology.

The question is not only whether AI will replace human thinking. The question I am interested in is different:

What happens when thinking itself gains a new environment in which to unfold?

One of the most common things I hear from people working with complexity is that the world has become too fragmented to hold. Experts are doing beautiful, rigorous work deep inside their disciplines, but often lack places where their knowledge can meet adjacent fields.

Large organizations and governments operate through divisions, departments, mandates, funding structures, and reporting systems that divide problems which do not arrive divided in the real world.

At the ground level of society, people see different pieces of both the problem and its possible solutions, but struggle to understand how those pieces could fit together into coherent action.

Meanwhile, leaders, founders, researchers, advisors, and changemakers are reaching the limits of what they can carry internally.

They are not short of intelligence, commitment, and often, they are not even short of ideas.

They are short of cognitive room.

They are trying to hold context, relationships, uncertainty, competing needs, institutional history, emerging possibilities, and practical decisions simultaneously, and then translate all of that into something other people can see and act upon.

This is where I believe AI may offer something much more significant than faster writing or automated tasks. Used carefully, it can provide a place to externalize complex thought before that thought is fully formed:

• It can hold multiple threads while we examine the relationships between them.

• It can help us move across disciplines, surface patterns, expose assumptions, test interpretations, and translate ideas between people who do not share the same language or frame.

• It can allow us to see the structure of what we are carrying, rather than continuing to carry all of it inside ourselves.

It does not remove the need for human judgment, but creates more room in which judgment can operate.

It does not determine what matters, but instead can help us notice where our values, assumptions, and intentions are shaping what we see.

It does not replace the knowledge held by experts, communities, or lived experience. At its best, it can help create connective tissue between them.

That is why I developed AI as a Thinking Partner - a six-week, small-group course that has now run through several cohorts and continues to evolve through the real work participants bring into the room.

It is not primarily a course about software, prompt formulas, or producing more content. It’s a six-week, small-group practice for people carrying real complexity: leaders, founders, advisors, researchers, changemakers, and others who are trying to understand, build, or influence something that does not fit neatly inside a checklist.

Participants bring their own live questions, projects, decisions, and areas of inquiry.

Together, we learn how to use AI to:

• externalize thinking that is difficult to hold internally;

• find structure and pattern within complex material;

• explore questions without rushing prematurely toward answers;

• pressure-test assumptions and decisions;

• translate ideas into plans, communications, and usable structures;

• and build a personal way of working with AI that supports, rather than displaces, human agency.

The purpose is not to hand our thinking over to a machine. It is to increase our capacity to think, connect, discern, and act within a world that increasingly exceeds the limits of any single mind or discipline.

I am now gathering interest for upcoming cohorts. I am less interested in filling a class than I am in bringing together the right room: people who are carrying meaningful work, who are willing to explore seriously, and who sense that AI may offer more than another layer of efficiency.

If you recognize yourself in this, you can learn more about the course here:

⁠AI as a Thinking Partner - Foundations

You are also welcome to reply directly to this note and tell me something about the complexity, change, or possibility you are currently trying to hold.

Perhaps the future will not be shaped primarily by those who learn how to make AI produce more.

Perhaps instead it will be shaped by those who learn how to create more room - for knowledge to connect, assumptions to be examined, new structures to become visible, and for better possibilities to emerge.

Not because it doesn’t work. It does work, which is part of why the deeper issue is easy to miss. You ask a question, it gives you an answer, you refine it, and you move faster. In many cases, that’s very useful.

But moving faster is not the same as thinking better, and it’s certainly not the same as changing the underlying pattern.

I’ve spent a lot of time in systems where ideas are not the constraint. Often, the insight is already there. The solution is partly visible. The problem is that the thinking is scattered across conversations, documents, intuitions, tensions, and half-finished attempts to explain what someone already knows.

The bottleneck isn’t intelligence, it’s holding capacity. People are trying to carry too much complexity in their own heads. This is where AI becomes interesting to me.

Not as the proverbial better search engine or a content machine, and most certainly not as a shortcut around human judgment.

But as a way to get thinking out where we can see it.

When AI is used transactionally, it mostly amplifies what’s already there. It gives cleaner answers, faster drafts, better summaries, and more efficient output. That has value, but it can also leave the deeper pattern untouched. You are left with the same assumptions you came in with, including the same blind spots, and the same way of framing the problem. It’s just faster.

But when you stay with something unresolved a little longer, a different possibility opens: AI can begin to reflect the shape of your thinking back to you. Certainly not perfectly, magically, or an authority. But in fact, very usefully.

It can show you what you keep circling. Where you’re narrowing too early. What assumptions are sitting underneath the question. What structure might already be present in the mess. What you know, but haven’t yet found a way to say…

That’s a much more uncomfortable way to use AI, because it asks more of the human, not less. You have to bring real material. You have to notice your own resistance. You have to stay in the conversation long enough for something more than an answer to emerge. But that’s also where it becomes useful in a deeper way.

The risk is not only that AI becomes too powerful. The quieter risk is that we use it to become more efficient versions of exactly who we already are.

• More productive, but not more discerning.

• More articulate, but not more honest.

• Faster, but not wiser.

I’m interested in a different use, where we develop AI as a thinking partner.

• A way to work with complexity without collapsing it too quickly.

• A way to externalize what’s hard to hold alone.

• A way to see patterns, test assumptions, clarify decisions, and turn insight into usable form.

Not to replace thinking, but to make more of it visible.

That’s what I’ll be exploring here.

**********************

Today I’ve been contemplating the concept of “purpose.”

For a long time, I think I confused purpose with self-sacrifice. I lived inside a belief system that often led me to make choices that reduced my ability to simply be in order to serve what I understood as the greater good.

There was nobility in some of those choices. But there was also cost.

Startups that needed certainty during stages of deep ambiguity. Causes that seemed to require self-sacrifice in order to be brought to life. Systems that needed someone to hold the bridge, absorb the pressure, or become the stabilizing structure before the structure itself existed.

Over time, that created a quiet dissonance. The more I tried to be useful, the farther I sometimes moved from the actual pattern of my own being.

And I’m beginning to wonder if that entire frame is backwards.

What if our life’s journey is not about finding a singular “purpose” out there in the world?

What if it is about bringing the core pattern of who we are (the way we are built inside) into greater alignment with the way we live, work, relate, and express ourselves?

What if the systems around us call forth certain patterns when those patterns are needed?

And what if our task is not to become the hero who saves the day, or the sacrificial lamb who makes the system possible, but to become a clearer expression of the pattern we actually are?

• Not through force.

• Not through performance.

• Not through proving our usefulness.

But through coherence.

Through the lens of light and camera:

The aperture is the degree to which one’s pattern of living permits one’s pattern of being to participate in the evolution of the system.

The aperture does not invent the light. It becomes clear enough for the light to pass through in its particular shape.

An aperture is not merely openness. It is aligned expression.

When the pattern of living does not match the pattern of being, the aperture is distorted. The signal bends, fragments, leaks, or becomes over-managed. That’s when we feel the strain of having to “make ourselves useful,” because our usefulness is being routed through effort rather than coherence.

But when the pattern of living begins to match the pattern of being, something different happens.

We become available. Maybe not famous, rewarded, understood by everyone, or even necessarily seen. But yes, available.

And I wonder if availability may be the deeper word beneath purpose.

Not:

“What is my purpose?”

But:

“What pattern am I, and how do I become available to the system without distorting myself?”

When we think of a “neighbourhood,” many of us immediately picture something quite different: rows of suburban houses, small lawns, short hedges, and neighbours leaning over fences to exchange news about what is happening in the world. Yet my earliest experiences of neighbourhood looked very different from this image.

My mother grew up in a farming community of roughly 350 people, surrounded by wheat fields and located fifteen minutes from the nearest small city. When we visited my grandparents, no one used the front door. In fact, if someone knocked on it, the entire house would momentarily fall silent as everyone wondered who on earth it could be.

People simply walked up the driveway, slid open the glass door off the kitchen, and came in. By the time they reached the table, coffee was already being poured.

There was rarely ceremony. A casual “How’s it goin’?” was often enough. Unless, of course, the visitor had been away for a long time. Then hugs, laughter, and a warm sense of you belong here would ripple through the room.

What is striking to me is that these homes were often separated by a quarter mile or more. There was no cul-de-sac. No shared green space. No density. And yet, community was strong.

Later, I lived on Commercial Drive in Vancouver. The neighbourhood could not have been more different. It was dense, vibrant, and wonderfully eclectic: artists, families, professionals, breweries, activists, immigrants, and people living every imaginable version of life.

Community there was practiced differently. You called ahead. You arranged to meet for coffee. You scheduled playdates. You did not simply arrive unannounced. Home became sanctuary - a retreat from the constant sensory richness of “The Drive” itself. The street provided the shared experience while individual homes provided refuge.

Even there, however, I encountered another form of neighbourhood. A friend lived in a small condominium building where residents routinely left their doors open. Neighbours wandered in and out. Pets visited one another’s suites. When the building needed painting, residents collectively picked up brushes and completed the work together over a weekend. Somewhere between the paint, the shared meals, and perhaps a little beer, a genuine sense of family emerged.

And now I live in Lower Lonsdale, where people strike up conversations in grocery store lines. They chat in elevators. They greet one another on the street. The city itself has intentionally created gathering places: outdoor skating rinks that become splash parks in summer, public plazas, markets, stages, and spaces that invite people outside and into one another’s lives.

Which makes me wonder: What actually makes a neighbourhood?

Is it a particular housing form? Is it single-family homes and front yards? Or is neighbourhood something deeper? Perhaps a way people choose to show up for one another within the constraints and opportunities of the places they inhabit? This question feels increasingly important.

Over the past twenty years, my community has changed dramatically. Like many places around the world, population growth and housing pressure have transformed what was once a relatively small community into a much denser one.

Imagine living somewhere for fifty years and watching, in what feels like an instant, thousands of new people arrive. Suddenly, the patterns of relationship that shaped your life no longer work in the same way.

People and families living in 800-square-foot apartments often experience the city differently than those living in detached homes. For someone raising a family in a small apartment, public spaces matter enormously. Parks, splash pads, skating rinks, transit, and green spaces become extensions of home itself. They are not luxuries; they are necessities.

For someone who has lived for decades in a detached home, community may centre around a backyard, a long-established network of neighbours, and a car that enables independence. Many have aged in place. Transit may not be physically practical or geographically convenient. Their needs are no less real.

Neither perspective is wrong - both emerge from lived experience.

What a challenge it must be to plan communities that must simultaneously house young families, maintain affordability, support economic vitality, and honour the needs of an aging population whose experience of place is rapidly changing.

Perhaps this is symbolic of many of the tensions we see today.

It is remarkably easy to cast those with different needs as the problem. Social media amplifies this tendency, magnifying feelings of being unseen, unheard, or left behind until frustration hardens into camps and camps harden into conflict. We speak louder and louder, hoping the other side will finally hear us.

But what if we reversed the sequence?

What if we entered these conversations with open ears first? What if we sought to truly understand another person’s lived experience before offering our own?

How might our communities change if understanding became our starting point rather than our destination?

Over the past four months on Substack (it feels like much longer!), I’ve been slowly clarifying what I want this paid space to become. My hope is that this area becomes less of a traditional subscription and more of a studio: a place where emerging models, frameworks, and ideas can be explored together while they are still alive and evolving.

At the moment there are only a handful of us gathered here, and as far as I know, each of you works in some aspect of human development through executive coaching, organizational development, leadership, learning, or systems change. That makes this a particularly rich environment in which to share work that is still in formation.

So, in the spirit of opening the studio doors, I’d like to share something that is very much still under development: a model I’ve been working on that explores how human development unfolds across expanding fields of Self, Other, and World.

As these ideas mature, I intend to publish more polished versions under The Aperture Field brand, and if you find them useful in your own practice, you are welcome to use them freely. My only request is attribution and, where appropriate, an invitation for others to join the conversation.

I’ll admit that sharing work this early in its development feels a little vulnerable. But I suspect that the most interesting conversations happen before ideas are fully formed, when they can still surprise us.

So I’m hoping to post here relatively frequently, sharing models, experiments, visualizations, and questions as they emerge. More than anything, I’m interested in whether these ideas resonate with your lived experience and the work you do. Where do they fit? Where do they fall short? What feels missing?

What follows is one of those early explorations…

Read more

But then one year, my sister’s birthday came, and suddenly I wanted to be part of it and give her something from me. Only I realized that fact as family members were already arriving for her birthday party. And so, I quickly looked around my room, and thought of everything I had that looked like something she would also like. But my sister and I were very different people. I was consumed by fantasy books, music, and horses. She was very experiential, with dolls that talked, a large Barbie and My Little Pony collection, and other interactive toys. As I looked around my room, nothing was right.

I began madly opening drawers and stumbled across my nightstand drawer, which was filled with cheap charm necklaces and a bunch of fake money.. she collected charm bracelet stuff and loved money and gosh, I didn’t even ever wear these anyway, so I wouldn’t even miss them… we had a WINNER!

I quickly took the entire contents of my drawer dumped it unceremoniously into a wrapping paper nest, and with my heart brimming with excitement and the joy of sharing, I quietly added my gift to the pile. Upon seeing my gift, my sister looked at me in surprise and excitement (I was delighted! I couldn’t wait for her to love my gift), and she ripped open the hastily wrapped and tape covered mess of paper.

And as she opened it, her expression went from excited to confused, and the tenor of the room changed dramatically.. “you gave me your worn out charm necklace?” In that instant, I remembered she probably already had the same charms I had, and not only that, maybe the necklace itself had seen better days. Her expression changed to wondering if it was a cruel older sister joke, and my mom delivered the 1-2 punch.. “what did you do Kari, empty your bedside table drawer and just give it to your sister?”

I can’t remember if I tried to downplay it.. I kind of remember it as sort of trying to share why I thought it would be good, but quickly putting together how not-good it actually was, and feeling absolutely devastated by my own lack of preparation for her birthday and thoughtless gift.

We laugh about this now as a family - it was perhaps slightly typical of my somewhat clueless nature growing up. But it got me thinking.. the reality was that I had independently realized on my own accord, that I wanted to celebrate my sister’s birthday with her by doing something nice. I had zero practice at it, and was clueless as to what the creature who lived in the room next door to me actually liked, as all I really knew was that she made no sense to me whatsoever (sisterly love didn’t really arise for us until I left the house for college and the remaining family members experienced peace for perhaps the first time).

And over the years, I very slowly learned how to celebrate first my relationships with each family member by carefully thinking about them at their birthdays and Christmases, and hopefully giving them something special that either came from my heart and time, or was something meaningful they might enjoy. And those were baby steps towards learning a greater empathy towards others, and through many other painful missteps, I learned how to empathize in a way that brought them joy instead of confusion.

As a teenager, I wasn’t kind to my little sister, as the natural competition of siblings ensued, and an adult friend of the family took me to task for it. It was a steep learning curve for me, and the adult friend was ruthless in showing me how selfish I was in my behaviour and how hurtful I was to my sister. I’d love to be able to say that I knew that I was and this was just correction that I needed, but I really didn’t understand the perspective of someone else’s needs at that stage of my own journey.

Over time, I became fascinated with inhabiting the interior worlds of my partner, my friends, family members and others.. by building my own little model of their worlds, I could understand and predict their behaviours and as a result life got much easier. I could pick the right gifts, say the right things, feel their own pain or joy and relate to it. And the other side of the pendulum swing began.. I became so good at understanding other people that I started forgetting how to understand myself.

And this is where Carl Jung entered the story for me. Because eventually I became interested in understanding not just other people, but also why certain people affected me so strongly.

Why did one person’s behaviour roll off my back while another person’s behaviour could occupy my thoughts for days?

Why was I compassionate toward some people and reactive toward others?

Jung’s answer, at least as I first encountered it, was projection. The idea that what evokes a disproportionately charged reaction in us often points towards a similar unconscious trait within us that we carry.

At first, this felt like another expansion in empathy. Instead of asking only “What is happening for them?” I began asking, “What is happening in me?” And that question turned out to be incredibly useful.

Sometimes my reaction indeed pointed toward a trait I hadn’t recognized in myself.. something I had disowned. But over time, I started to notice something else: projection explained part of the picture, but not all of it.

I wonder if Jung’s perspective was a little lost in translation from the original German text, and if his perspective was actually more like ‘What evokes a disproportionately charged reaction in us often points toward something unconscious in us.’

The unconscious part in us may be anything from our own trait reflected back, a value we hold that is being broken, an unmet need, a disowned capacity, the opposite trait.. and on and on. But I think that’s one of two levels that ‘shadow work’ is actually about. I think we need to answer both questions in order to truly integrate the feeling so it no longer ‘triggers’ us:

1. why am I reacting (shadow work)

2. what is actually happening for the other person

So yes, we clean up our own house first (i.e. remove the plank from our own eye before addressing the speck in the other’s). But then, if we have found our own stability, the ‘stretch goal’ perhaps becomes about the fact that two systems have now collided in relationship, i.e.:

1. My reaction contains information about me.

2. Their behavior contains information about them.

3. The interaction between us contains information about the relationship.

And all three can be true at once.

So an example would be let’s say someone is controlling.

1. Level One would be the simplistic projection: “you dislike controlling-people because you yourself are controlling”.

2. Level Two would be “This person learned control because unpredictability was dangerous for them.”

And the second question changes something important. We still might not want them in our lives and/or refuse the behaviour and set a boundary, but the emotional field itself shifts from condemnation to understanding. It’s the difference between ‘you’re bad’ and ‘I understand how you got there’.

I think our own trauma is the work of Question 1 in unpacking the pain and suffering of our own life to see why we experience pain in colliding with this other person’s way of being. Trauma compresses pain into the perception of threat / enemy / avoid / danger.

But healing that trauma restores dimensionality, and we begin to be able to see their wound, the adaptation, the fear, the longing, and the humanity of the other person. And once we can see more clearly, our options expand. Sometimes that means repairing a relationship, sometimes it means extending compassion, sometimes it means realizing our assumptions were wrong, and sometimes it means setting a boundary. The point isn’t that every relationship should be preserved; it’s that we can finally respond to reality instead of reacting to our wounds.

And the tricky balance is that there is a trap here too - if you then only see the humanity in everyone but yourself, then you can become endlessly compassionate toward others while continually tolerating behaviors that don’t belong in your own life.

I think the true opportunity for integration is in holding both: the compassion and honouring of your own shadow and trauma while also holding compassion and honour for the trauma of the other. Boundary with compassion.

Looking back, I don’t think the lesson of the necklace was that I was selfish. I think the lesson was that I didn’t yet know my sister was a world unto herself. Growing up taught me to see other people’s worlds. Jung taught me to see my own. And relationship, I think, asks something harder still: the capacity to hold both at once.

My reaction contains information about me. Their behaviour contains information about them. And the space between us contains information about the relationship. Once we can see both ourselves and the other person clearly, we are finally free to choose our response.

“I understand why you are behaving this way. I don’t hate you for it. And I am also not available for it.”

We often talk about sustainability as though the world should exist in perfect equilibrium at all times; but living systems don’t work that way. They move through cycles of growth, consolidation, release, and renewal.

We need to look no farther than the seasons themselves: spring plants its seeds, summer is a season of growth and expansion, fall brings the harvest and evaluation as well as the pruning and cutting back of what no longer serves , and winter becomes a time of integration and preparation for what comes next.. and around and around we go.

Throughout history, we have seen this same cyclical rhythm appear again and again. We push forward and discover things that fundamentally reshape society - metallurgy, steam power, computing, AI.. In each transition, we surge toward new frontiers, summiting the edge of what we know and suddenly beholding an entirely new landscape of possibility.

But discovery is only the beginning.

What follows is always a period of incorporation, a long phase of weaving those discoveries into the fabric of society itself, fundamentally reshaping how we live, work, govern, relate and understand the world around us.

This is the natural rhythm of evolution. We push outward and find new edges. In doing so, we sense the exhilaration and fragility of standing at the boundary of the unknown and how new discoveries can either fracture systems or usher in entirely new eras of flourishing. Over time, those discoveries become integrated into the structures of everyday life. Institutions mature, systems stabilize, and society reorganizes itself around the new reality.

And eventually that very stability itself begins to harden, and what was once adaptive and life-giving slowly becomes rigid. Mature systems become stale instead of simply stable, and eventually the growth cycle begins again, nudging society forward into another period of transformation.

But the end of each of these cycles rarely feels graceful from the inside. The end of the era of growth feels more like teetering on collapse: too much unintegrated change accumulating too quickly, systems straining under the weight of their own complexity, institutions falling increasingly out of sync with what it now possible, and perhaps even necessary, for society to become.

We begin to sense that the underlying infrastructure of how we live must change, while simultaneously discovering that the very structures built to create stability are naturally resistant to fundamental transformation.

And so the cultural rhythm begins to shift and the drumbeat of relentless growth gives way to another rhythm entirely:

Integrate. Consolidate. Digest. Reorganize.

Growth gives way to application and expansion gives way to restructuring and renewal. Like a farmer harvesting fruit at its peak and storing it for the winter, we begin preserving and integrating what has been learned so that it does not simply die on the vine in an endless pursuit of more.

And perhaps this is where we now find ourselves: not at the end of progress, but at the end of a particular phase of progress. A civilization-wide pause to metabolize what we have created.

No athlete becomes stronger during exertion itself. Strength emerges during recovery and integration. Yet culturally, we increasingly treat recovery as failure.

There is no need to vilify the extraordinary growth era that brought us here, simply because it has reached its natural limits. Better that we honour what has been built, recognize the immense beauty and possibility that it created, and allow ourselves to enter the next phase consciously: one of integration, restructuring, maturation, and renewal.

In my curiosity, I’ve been returning to the works of thinkers from the past, reading their original texts (there is no shortage of material here), from The Theory of Moral Sentiments to more modern works like Integrity, and of course Emotional Intelligence: Why It Can Matter More Than IQ, which helped bring the language of ‘EQ’ into the mainstream

As I followed the thread, I kept discovering something interesting: not only are these thinkers describing similar underlying dynamics through different lenses, but we have in fact, been circling these ideas for thousands of years. Empathy isn’t a new concept, it’s something continually rediscovered, reinterpreted, and renamed.

And yet, despite this long lineage of thought, it feels as though we have lost something.. perhaps our shared internal picture of what these ideas actually mean in practice. Each work I return to offers another fragment of that image that feels both familiar and strangely absent in how we engage with one another today.

So I’ve decided to follow that thread more deliberately.

This series is an attempt to piece together connections across centuries of thought and tradition, to revisit texts and ideas that have in many cases been reduced to soundbites or dismissed as outdated, and to see whether something essential may have been left behind in the process.

Some of the authors I’ll be exploring may be surprising, as often what they are remembered for today captures only a fraction of what they were actually trying to articulate.

I'm very interested in hearing your own reflections as this unfolds, whether they align, challenge, or take the conversation somewhere unexpected. So, with that, consider this an open exploration into the deeper question of how we perceive, relate to, and make sense of one another individually, collectively, and within an increasingly complex world.

What I can’t yet reconcile is why something so persistent keeps getting lost.. I suspect that’s where this needs to go next…

Optimization leadership emerged in a “sprint era,” under conditions where speed, execution, and clarity of outcome were paramount. It creates effectiveness through reduction:

• Narrowing focus quickly

• Driving toward known outcomes

• Maximizing efficiency and short-term value capture

• Rewarding decisiveness and control

This mode works well in stable or clearly defined environments. But it begins to break down under conditions of complexity.

Integration leadership is what those conditions demand. It creates clarity not through reduction, but through relationship:

• Holding multiple perspectives without premature collapse

• Extending time horizons (second- and third-order effects)

• Navigating ambiguity without forcing false clarity

• Balancing seemingly opposing needs (speed vs. reflection, action vs. listening)

Where optimization asks, “What is the fastest path forward?” Integration asks, “What is actually true here, and how do these pieces fit together over time?”

This is not a rejection of optimization, but an evolution beyond it.

The shift is from:

• clarity through simplification → clarity through coherence

• execution as primary → judgment as primary

• single-mode excellence → multi-modal fluency

In earlier eras, we could rely on leaders who wielded one tool exceptionally well, but this moment requires leaders who can move between modes with precision without losing coherence in themselves or the system.

We’ve spent decades optimizing for speed. What we need now is leadership that can hold complexity long enough to find real direction.

Not so much to study history, but to sit inside the thinking of those who were trying to make sense of the same underlying patterns we’re still living in.

Today, I began The Theory of Moral Sentiments by Adam Smith, and within the first few pages, I hit something that feels strangely alive:

> “As we have no immediate experience of what other men feel… it is by the imagination only that we can form any conception of what are his sensations…”

> “…It is from this very illusion of the imagination… that the dread of death… while it afflicts and mortifies the individual, guards and protects the society.”

There’s a paradox here that I can’t quite let go of:

That our empathy is, at its core, an imperfect simulation: we imagine ourselves into another’s experience, often inaccurately…

And yet, it’s precisely this distortion that seems to restrain us, to shape behavior, to hold something like “society” together.

Which raises questions I don’t yet have answers to:

- If our moral instincts are built on imagined (and potentially exaggerated) experience… what does that mean for how we judge, protect, or intervene?

- Where does this mechanism create coherence… and where might it create blind spots?

- And what happens when these human-scale distortions begin to operate at system scale?

I’m starting to suspect that many of the systems we live inside are built on these kinds of human distortions.. functional, but not necessarily accurate.

I’m going to keep reading Smith in full, alongside others, and follow the thread wherever it leads.

If this kind of exploration is alive for you too, I’d be curious to hear how you see it. Not conclusions necessarily, just where your thinking goes when you sit with something like this.

There were many important observations made in that session - representation of women on boards appears to be holding around 30% globally, but new placements have slowed significantly. At the same time, some women seem to be opting out of systems that don’t recognize or integrate their perspective.

After the meeting, Katrina C. Foster published a piece that stayed with me. She is naming something subtle and significant - that this doesn’t look like a loud reversal, but is more like a quiet withdrawal. The language of DEI, the measurement, and the scaffolding that once made inequality visible is being slowly removed.

And I found myself sitting with a different question - the signal she is pointing to feels real, but why is this happening now, in a time where we might assume we ‘know better’?

I’ve spent decades, in different ways, pushing against systems as a woman in leadership and as someone trying to introduce new ideas into rigid structures. For a long time, I understood that experience as kind of a battle. There was always a ceiling, and my instinct was to locate the source of it - who was blocking it, who needed to be challenged and where the resistance lived. And let me tell you, I can play that role well - give me a sword and I will go to battle without hesitation.

But over time as I ran into deeper and deeper ceilings, something began to shift. Each time I reached what I felt was the ‘final boss,’ I found an unexpected twist. The person I thought I was fighting was usually operating within constraints of their own- an incentive structure, a rule set, or pressures I hadn’t fully seen.

And when I followed that thread further, the shape of the problem itself changed. It became harder to find a singular ‘bad actor,’ and easier to see something more diffuse: systems of incentives, and structures that produce outcomes, regardless of the individuals inside of them.

That realization didn’t make the experience any easier. If anything, it made it more disorienting, because while I was trying to understand the system more deeply by listening, integrating perspectives, and questioning my own assumptions, I was still inside it. Still being shaped by it and at times, still getting hit by it.

It felt like holding a sword and shield while also extending an olive branch.

Eventually though, a different lens began to emerge. Years ago, Jeremy Rifkin, in The Empathic Civilization, wrote about how societies evolve through expanding circles of identification, and how what we consider ‘us’ grows over time: from family, to tribe, to village, to nation. At each stage, something new emerges that stretches the boundaries of the existing system and that creates friction, because integrating something new often requires changing something that already works (at least for some).

And beneath that friction is something deeper than ideology:

fear.

Not ideological disagreement or even resistance to progress necessarily, but more of a fundamental uncertainty:

if we change this system, will we still be safe within it?

History gives us examples in every direction in the moments where integration created something more coherent, and also moments where it fractured what was already working.

If you look at systems over time, a pattern begins to emerge:

• An insight arises, often from lived experience, and often ahead of its time.

• A system forms around that insight, attempting to bring it into reality.

• That system becomes codified into policies, metrics, language and programs

And then slowly, it shifts.. the form is still there, but the spirit begins to thin. The incentives distort, and what began as clarity becomes compliance and what began as truth becomes language, and when that happens, legitimacy begins to erode.

It’s possible that some of what we now call DEI has followed this arc. The original signal was real, and it still is - the need to make inequality visible by naming and measuring it was necessary. But over time, many of the systems built around that signal didn’t produce the outcomes they were designed to create. In some cases, they became performative and in others, they created friction with the other parts of the system they were trying change. And when systems lose legitimacy, they are often not refined - they are abandoned.

We can see the symptoms of that now. In some places, it shows up as quiet institutional withdrawal where programs disappear, language softens and measurement declines. In other places it shows up very differently, as more heightened, even mythic interpretations of what is happening. These attempt to make sense of complexity by locating a central force, a clear antagonist (big boss), or a story that can hold the scale of the shift. When systems lose coherence, the signals don’t arrive cleanly.

There is a real risk in this moment. As Katrina points out, when we remove the scaffolding (the measurement and language), we lose the visibility. Without visibility, inequality doesn’t disappear, it just becomes harder to see and harder to act on.

But there is another risk as well. If we only focus on preserving the scaffolding without questioning whether it was sufficient to begin with, we may continue to measure a problem without meaningfully changing it. Measurement is a stage in system evolution, but it isn’t the destination.

Which brings us to a different kind of question. Not how do we we return to what we had, and not how we remove it entirely, but:

What kind of systems actually produce the outcomes we’ve been trying to measure?

Right now, we may be between systems, with the old one losing legitimacy and the new one not yet formed. That makes this a disorienting moment, but also a generative one.

When systems lose coherence, we tend to respond in two ways: we either try to preserve the structures that no longer work or we construct narratives that explain their failure. Both are understandable. Neither on their own is sufficient.

This is a space where ideas are explored in real time. You can subscribe to follow the threads as they begin to connect.

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