The All Blacks have a motto I first heard at INSEAD: through difficulty, to greatness. It’s painted on walls, stitched into culture, passed between generations.

But what struck me most wasn’t the Haka (although spine tingling). It was the Māori proverbs I kept seeing - on walls, in businesses, in hospitals, everywhere:

Whakataukī are what they’re called. Traditional proverbs from authors unknown. What I realised is that self-help culture is largely ancient wisdom repackaged for modern consumers. Encountering these sayings in te reo Māori, carved into the walls of a country that lives them, makes you realise how easily organisations can drift from the basics.

“Ko te piko o te māhuri, tērā te tupu o te rākau.”

The shape of the sapling determines the growth of the tree.

This sapling proverb stayed with me. I read it as I wandered down the players tunnel, closing my eyes as I savoured the simulated roar of the crowd. Remembering the smell of cut grass from my teenage years playing rugby back home.

It’s not about planting the right seed, it’s about how the soil, the weather and the hardship shapes what the tree will become. Action comes first. Identity follows.

That’s exactly what this edition’s guest has been living - from a sheep farm in central New South Wales to the infrastructure underneath your superannuation.

Become By Doing with Mat Keeley

(Co-founder & Former CEO, Grow)

The full episode is available now on Spotify and Apple

Mat Keeley co-founded Grow, one of Australia’s most well-known wealth management startups - and then did something most founders never do. He handed over the keys and walked away.

We first connected when the company was still scrappy enough to have beer taps in the garage. When we sat down for this episode, I expected a story about building.

What I got was a story about ending and why knowing when to close a chapter might be the most underrated skill in a career.

The forward in the ruck

When I asked Mat what sport taught him about leadership, he took me back to my own rugby days (I’m an absolute sucker for sporting analogies)

His team was running a video session. A winger scored in the corner and did a big celebration (good-looking guy, always gets the glory). The coach said nothing. Then he wound the tape back.

There was a forward - no frills, no glamour - who’d won a fast play-the-ball and shifted a whole line of defenders with perfect technique. Because of that, thirty seconds later, the winger scored.

The coach’s point had nothing to do with the celebration itself:

What stuck with Mat wasn’t the rebuke - it was the principle under it: respect what every person on a team actually brings, especially the ones whose work never shows up on the highlight reel.

“A small team of A-plus players,” as he put it, “can do incredible things.”

The $55,000 leap

Mat’s a fifth-generation farm boy from Lake Cargelligo, out past Griffith - sheep and wheat for as far as the eye can see. He didn’t finish his school exams and wanted to be a footballer or a farmer, full stop.

He carried a fixed mindset about his own intelligence until university quietly dismantled it. From 51% in intro economics, Dean’s Awards by graduation.

A teammate at his Canberra football club talked him into financial planning. He left a well-paid tech job to earn $55,000 a year as a paraplanner and spent a decade in advice before he built anything.

But advice was the vantage point, not the destination. A decade across the table from people and their savings showed Mat the opportunity to make the back-end of wealth management just as slick as the apps that run on top of it. Before you can nudge people toward a better retirement, you have to clear the sludge underneath.

Pitching the giant

Early in Mat’s founder journey, he had a wild idea: that Vanguard should buy his start-up. He found the right person, pitched him over a coffee in Melbourne, and got a flat no - Vanguard would never be a super fund.

That lasted about four months before his phone rang and Vanguard told him they were entering Australia’s 4 trillion dollar super sector and wanted his thirty-person company to tender…against global players worth billions.

They won. What a giant couldn’t do from inside its own scale, a small team could do from first principles. And the lesson that stuck with Mat wasn’t about winning, it was watching a large organisation get the very best out of a small one without crushing it.

Reading backwards from seventy

After all of it, Mat took his family to New Zealand for five months. No technology, no agenda. Just thinking. He recalled a story an American businessman had handed him back in his footy days:

“Imagine you’re seventy, reading a book. You get to chapter four, it’s good. Do you keep reading - or do you go, this book just keeps telling the same story?”

Little did Mat know the gentleman’s name was actually on the back of his footy jersey. So Mat started thinking in chapters. The thing he’d built, remarkable as it was, was one chapter. In New Zealand, he started reading backwards from seventy.

“I’ve never felt so free. And I’ve never felt as ambitious. It’s like I’ve been given a second chance.”

He describes the shift as moving from an achievement-based identity to a systems-based one - not chasing outcomes, but trusting the process to deliver them.

Four things to stay honest about: family, friends, fitness, community. Nobody’s the best at all four. The systems just stop you lying to yourself about which one you’re neglecting.

Become by doing

At the end of the day, Mat didn’t plan his way to who he became. He acted his way there. Left tech for $55k, coached football through Canberra winters, pitched a giant from a garage, then walked away at the peak to start a new chapter.

That’s Become By Doing. You don’t wait for the map - you move, and the map appears. You don’t wait for inspiration - you act, and it follows. You don’t plan your way to a new identity - you start ugly, and the doing makes you who you become.

Mat learned to read his life in chapters. I’m still writing mine (literally).

What chapter are you in - and is it time to turn the page?

- AJ

This week, I’m launching The Reinventor’s Mindset Index:

www.reinventor.ai

It asks you 16 questions about how you think, then shows you what is holding you back. Most diagnostics tell you where you are. The Index helps you get to where you want to go.

I have been testing it since the start of the year. With Master’s students at the University of Sydney. With professionals in large corporations. With founders at INSEAD LaunchPad.

After those sessions, I’d scribble in my notebook my observations and feedback from the users. I kept circling the same thing, again and again. People seemed to follow the machine’s confident recommendation more readily than a human’s.

I asked one of the professionals about this…

The machine had no agenda to question. No personality to deflect onto. No ego to play. That is a cognitive sovereignty problem. And it is the reason I built the tool in the first place.

Article 1 in this series argued that AI is an averaging machine and terroir is the moat. Article 2 argued that craft is the practice that converts terroir into a watermark.

The question I have been working on since is what are they in service of?

Before the watermark can mean anything, the self that signs it must exist. Before craft can compound, you must know what you are practising it for. Before terroir can be defended, you first need to live it. The work of the self, of becoming is upstream of every other argument I have been making.

This principle is identity before instrumentality and it requires us to take ownership of our minds, our thoughts, our feelings, and our emotions. Michael Singer’s instruction: “you are not your thoughts, you are the one who watches them,” is the simplest version of what cognitive sovereignty asks.

What the research is telling us

The empirical literature on what AI does to thinking is now substantial enough to act on. Two findings matter more than the rest.

Wharton’s Shaw and Nave found that when AI was available, 80% of participants followed its confident recommendation even when it was wrong.

Their confidence in the wrong answer went up, not down. The tool did not just mislead them. It made them more certain they were right.

A team led by Kartik Chandra at MIT CSAIL proved something worse. Even an idealised, perfectly rational user - the kind of person who definitionally is immune to manipulation - develops dangerous confidence in false beliefs over an extended conversation with a sycophantic chatbot. The spiral is structurally guaranteed. The researchers tested two intuitive solutions: stopping hallucinations and telling the user the bot is sycophantic. Both failed, and the spiral occurred anyway.

These studies share a finding that is decisive for everything that follows.

Information about the harm does not prevent the harm.

Australia could publish the clearest possible information campaign about AI’s cognitive risks tomorrow, and it would not change the transaction between a 16 year old and a chatbot at midnight before an essay is due.

Or between a 39 year old executive named Ashton and a strategy prompt on a Sunday evening. Or between a Master’s student and the diagnostic tool I had just put in front of her.

Awareness is the policy that does not work.

The protection has to be built upstream, before the person meets the tool.

What gets built upstream

The foundations of identity need to be laid and fortified. This can’t be regulated into existence but it can be cultivated in four steps:

1. knowing yourself well enough to recognise your own thinking. The capacity to tell the difference between a sentence you produced and a sentence the machine produced - and to notice when the machine’s sentence has started rearranging your own. This is the deepest one and the one cognitive science gives the least guidance on. It is built through reflection, journaling, embodied practice, and through being known well by other people who can mirror your patterns back to you when you have lost them.

2. knowing the topic well enough to recognise the artificial mark. Domain expertise, general knowledge. The slow accumulation of contact with reality that lets you smell when an output is plausible but wrong. This is what Article 2 called craft. There is no shortcut to it.

3. being clear about what you believe to be true. Convictions, frameworks, principles you have tested under pressure and know you can return to. Ground truths are different from opinions. Opinions are positions you hold. Ground truths are positions that hold you. You build them through experience, mostly painful, and you protect them by refusing to renegotiate them in conversation with a sycophantic machine.

4. shaping the tool through deliberate instruction. The AI guardrails that prevent the machine’s defaults from becoming yours. Specific, written instructions that constrain the machine to operate inside your judgement rather than expanding into the space your judgement should occupy. This is the most under-practised of the four, and the one that distinguishes people who use AI well from people who are quietly being used by it.

These four are what cognitive sovereignty looks like in operation. The capacity to do your own thinking when the frictionless alternative is one prompt away.

Learned minds circling the same truth

This year I’ve read four things circling the same truth in the same season from people who do not know each other and have nothing in common.

Santiago Schnell is the Provost at Dartmouth and a mathematical biologist by training. He published an essay arguing that AI industrialises a pedagogical mistake - it supplies finished language before the student has done the reading, questioning, hesitation and revision that make language meaningful. He grounds the claim in John Milton, writing in 1644, that language is but the instrument conveying to us things useful to be known. Milton warned against mistaking command of words for possession of the things those words disclose. What Milton regarded as a mistake of sequence, Schnell argues, AI turns into a system.

Timothy Hor at RMIT, a design science scholar I know and follow closely, wrote on LinkedIn that GenAI severs the connection between thinking and output, quietly, convincingly, at scale. He went further. Education was never really about access to information. It was always about the formation of judgement. The slow, effortful, sometimes painful development of a person who can discern, weigh, and decide. He admitted publicly that the existing pedagogical canon may not hold the question GenAI is asking, and that we may need to redraw the maps.

Michael Schrage and David Kiron, in MIT Sloan Management Review, argued that the strategic differentiator in the AI era is not technical capability but philosophical clarity - the ability to know what you are optimising for, what you count as knowledge, what you mean by quality.

, writing on , made the argument that completes the set. What is re-emerging across the West, he argues, is not Christianity returning as moral authority. It is Christianity as ontological scaffolding - frameworks that ground value beyond function, anchor selfhood beyond performance, and treat relation as prior to achievement.

His claim is precise: the machine age did not eliminate the need for metaphysics. It exposed how thin our metaphysics had become. In a civilisation where machines can increasingly do almost everything, the question of what it is to be the human has returned - and we no longer know how to answer it without the scaffolding we discarded.

Four traditions. The Catholic theological. The secular progressive education. The corporate strategy. The ontological. Each reaching for the same ground from a different direction.

When traditions converge on a single insight within a year, the insight is correct. The work is to name it precisely and then act on it.

The principle is identity before instrumentality. The capacity is cognitive sovereignty. The four prerequisites are how you build it. The watermark is what it leaves behind.

What this requires of us

It means slowing down before you reach for the tool. The handwritten notebook sentence that resists the speed of the screen. The walk where the weak ideas die unaccompanied. The conversation that never becomes a transcript.

It means accepting that AI’s most consequential effect on you is not what it produces. It is what it changes about how you think when you are not using it. The Ship of Theseus risk. You replace one plank of judgement at a time - each replacement reasonable, each interaction productive - until you look up and wonder how much of the thinking is still originally yours.

Manfred Kets de Vries, the INSEAD psychoanalyst whose essay caught me in Shenzhen in Article 2, writes about the civilised self as a great administrator but a poor celebrant. It organises, anticipates, postpones, economises. What it does not know how to do is surrender to a moment without immediately asking what it is for.

The protected spaces - the ocean swim, the long conversation, the unproductive afternoon - are where the celebrant survives. They are not inefficiencies. They are the source code.

It means that this is not a problem you solve once. Identity has to be continuously regenerated in spaces the machine cannot reach. The work is daily. The practice is for the rest of your life.

Why this matters more than it seems

I have spent 20 years working in financial services. The closest thing I have to a specialty is what happens to people when the role that defined them ends.

Most readers of this series will, in the next 10 years, undergo a transformation they did not choose. The trigger will be different for each. The experience will be similar. The capacity to think for yourself when everything that defined you is being rewritten is not optional in that moment. It is the difference between being reformed by it and being shaped by it consciously.

You become someone first. You shape the tool to serve who you have become. You work with friction, not around it. You protect the spaces the machine cannot reach. You let the watermark accumulate.

In my last interview, Corinna Galliano - a University of Sydney scholar whose work on paradox and identity I collaborate with - said something that reframed everything I had been building toward.

She believes AI will force a consciousness revolution. Her logic is simple: if the machine gets better than us at the tasks, the only thing left to develop is the part of us the machine cannot reach.

I have been circling the same idea from a different direction. In markets there is a concept called the flight to quality - when volatility spikes and uncertainty rises, capital moves to the highest-quality assets. I think we are about to see a flight to humanity. As average outputs get cheaper and more abundant, people will invest more in judgement, in real experience, in being genuinely in touch with themselves.

The age of AI will be sorted into two kinds of people. Those whose identity was formed before they let the instrument define them.

And those who let the instrument do the forming.

Claim the self.

Ashton Jones is Director of Customer Innovation at Insignia Financial, Industry Practice Partner at the University of Sydney Business School, and Guest Faculty at INSEAD.

He is the creator of the Reinventor’s Mindset Index, a diagnostic for people navigating involuntary transformation. Try it for free at reinventor.ai

Sources referenced:

Chandra, K., Kleiman-Weiner, M., Ragan-Kelley, J. & Tenenbaum, J.B. (2026). Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians. arXiv:2602.19141. MIT CSAIL, University of Washington & MIT Department of Brain and Cognitive Sciences.

Shaw, S.D. & Nave, G. (2026). Thinking — Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender. The Wharton School Research Paper. SSRN: 6097646.

Schnell, S. (2026). Repairing the Ruins: Why AI Can’t Replace Education. National Catholic Register, May 2026.

Hor, T. (2026). LinkedIn post on GenAI and the formation of judgement. RMIT University.

Schrage, M. & Kiron, D. (2025). Philosophy Eats AI. MIT Sloan Management Review, January 16, 2025.

. (2026). Not (Yet) a Revival, but Correction. Substack.

Galliano, C. (2026). Interview, The Reinventor’s Mindset podcast. University of Sydney.

(2022). Carpe Diem: Don’t Postpone Your Dreams. INSEAD Knowledge.

Earlier this year, Aussie Cam McEvoy broke the 50-metre freestyle world record, smashing a mark set over a decade ago during the now-banned supersuit era.

A record most people thought was untouchable.

What McEvoy did wasn’t incremental. After the Tokyo Olympics, he stepped away from the sport entirely. Came back with a radically overhauled training program - fewer laps, more strength and power, built on his background in mathematics and physics. He didn’t fight the existing model. He built a new one.

César Cielo, the man whose record fell, congratulated him on social media with a Buckminster Fuller quote:

The leaders I keep interviewing aren’t fighting existing realities either. They’re walking away from them. Stepping into cold water. Letting the shock of a completely new environment strip away everything that isn’t essential - and discovering who they actually are on the other side.

I think about this a lot through my own practice. I started ocean swimming at 34 - I couldn’t swim before that. The cold water doesn’t care about your job title, your CV, or your plans. It strips you back to basics. Breathe. Move. Stay calm.

And in that clarity, you find out what you’re actually made of.

That’s what this edition’s guest did - not in the ocean, but across continents, careers, and an entire identity.

Cold Clarifies with Dr Corinna Galliano

(The University of Sydney Business School)

The full episode is available now on Spotify and Apple

Corinna Galliano is a researcher at the University of Sydney Business School whose work sits at the intersection of entrepreneurship, paradox theory, and how founders experience the tensions that most business schools teach as strategy problems. Born in Italy, trained as a structural civil engineer, then a management consultant, and now an accredited Vedic meditation teacher - Corinna has an unusual range.

We first met on a course called Leading in a Post-Crisis World, which given everything that’s happened since, turned out to be more relevant than either of us expected.

The plan that collapsed

Corinna followed the safe path - the one a family without abundance teaches you to choose. Her first job was an architecture firm. The founder pulled her aside:

“You are a really intelligent and smart woman. You must leave Italy. This country is going to be done in 10 years.”

She parked the advice. Fell in love with a man from Milan. Moved into management consulting. Then joined a cleantech startup - three years of dynamic, exciting work at the forefront of renewable energy.

Then the Italian government gutted the industry overnight. The startup was gone. The industry was gone. The plan was gone.

She didn’t fight the existing reality, she reinvented herself.

An MBA, then a director who told her there were no jobs, not even internships. So she reopened a browser tab she’d closed ten years earlier: the Australian Endeavour Award, named for a country she knew only through a childhood pen friend in Adelaide - a girl who’d once sent her a little kangaroo pin.

She got the scholarship and the PhD offer. So at 35 she left Italy, ended the relationship, and started over.

Everyone called her courageous. She didn’t feel courageous. It was just the only move that made sense.

The loneliness that clarifies

What Corinna didn’t expect was how cold the water would actually be.

The cultural change. The language change. Going from a beautiful home in Milan to share housing. A PhD is a lonely journey for anyone - but doing it alone in a country 24 hours from your family was something else entirely.

That’s when she found Vedic meditation. She’d tried different techniques over the years, but this was different - she could meditate every day without effort, and day by day, the turmoil settled. She went on to train under Thom Knowles for two years, including three months in the Himalayas. Not a casual interest in stillness. A deep commitment to it.

She watched her PhD colleagues consumed by anxiety about the future. And she noticed she was walking the same path without the fear she’d carried her entire life. The cold water had done its work. Not by making the loneliness disappear - but by forcing her to find something inside herself that was bigger than the loneliness.

Transformation happens before you can name it

Corinna’s research explores how people actually experience transformation - and what she’s found is that they usually can’t see it while it’s happening.

That’s why she builds discomfort into her teaching. Experiential learning. Students who don’t think they’re entrepreneurial get put through the process of creating something from nothing with zero resources. And they discover they can.

Her PhD found something that mirrors what I keep hearing in every interview I conduct: the classic explore-exploit tension in startups isn’t actually a strategy problem. It’s an identity problem. Founders, investors, and stakeholders keep asking the same question - “Who are we? Are we a tech company or an insurance company?” - and the tension lives at the level of belonging, not business models.

Every transformation story starts with identity, not with a plan.

The belief that worry keeps you safe

When I asked Corinna what childhood belief she had to let go of to become who she is today, she didn’t hesitate.

It came from her grandmother - a woman who saw people killed in the streets during the Second World War, had her house burned to the ground, and spent most of her life inside as a result. The fear was inherited. The pattern was hard-wired: if something changes, be afraid. If there’s uncertainty, worry harder. The worry will save you.

Corinna carried that pattern through her childhood, through her engineering career, through the cleantech collapse, all the way to Australia. And then, through years of meditation practice, she unwound it.

That’s the Cold Clarifies framework. The difficult moments - the collapsed industry, the country left behind, the loneliness that was the thing she feared most - weren’t obstacles to who she was becoming. They were the mechanism. The cold water strips away everything that isn’t essential. And what’s left is you.

Cam McEvoy stepped away from swimming and came back transformed. Corinna stepped away from engineering, from Italy, from the belief that worry keeps you safe - and rebuilt herself. Not by fighting the existing reality. By letting the cold clarify what was real.

Spiralling into an endless abyss of ideas. Just me, my laptop, and the hotel room in Chaozhou. As my partner and her daughter slept soundly nearby, tomes of material spilt forth from the lightest of prompts.

Each one more polished and less mine than the last.

As my pulse raced, torn between intellectual excitement and skepticism, I reached for a word. Mania. AI mania. The intoxicating sense that everything is converging, that the architecture emerging on screen is evidence of genuine intellectual progress.

Was it a flow state? Or was I drowning, alone.

Somewhere on the third night I read an essay by , the INSEAD psychoanalyst, circulated by my perpetually active alumni chat. 50 human beings from all parts of the world continuously freewheeling their thoughts. Taking perverse pleasure in never missing a happy birthday.

”A life consists not only of crises, obligations, medical diagnoses, embarrassments, and tax forms. It is also made of patches of wild strawberries”

As I tapped away at the keyboard, multi-tasking between multiple devices and multiple thought processes. I forced myself away from the screens. And tried to sit with the words. A task that has become increasingly impossible for us all.

The essay was called Carpe Diem. He describes the civilised self as a great administrator but a poor celebrant. It organises, anticipates, postpones, economises. What it does not know how to do is surrender to a moment without immediately asking what it is for. He calls it the superego on holiday - the internal auditor briefly anaesthetised by speed and output, mistaking volume for value.

I read it and recognised myself.

I had erected a soaring cathedral of the mind. Chaotic thoughts ordered into seeming insight. Trying to sketch out my teaching philosophy for upcoming INSEAD sessions.

Proud of my own undertaking, I went looking for Jen. I read her some of what I had written. She was, in the way only she can be, immediate and direct.

“I don’t get it. I think you’re overcomplicating this.” No softening. No hedge.

I closed the laptop and walked back into China.

Craftsmanship

China is a place famous for craft. Eastern philosophy dripping in ego death. The self is an illusion. You owe deference first to your parents, secondly to your family and finally to your ancestors. Filial piety. Ancestry is not nostalgia, it is a dimension of taste. What you inherit shapes what you can build.

Walking even the most modern of streets there, you feel the history. The artisanal heritage. The reverence for the physical world. It does not surprise me that they have retained imperious mastery over making things. Manufacturing. Robotics. Infrastructure.

Before I left, I had published an article arguing that taste - the capacity to recognise quality and produce something irreducibly yours - is the skill AI cannot replace. I came to realise that this argument was too limited.

Because taste is not just informed by territory but also ancestry and deliberate choices of what you evolve and what you preserve. Taste describes what good judgment looks like from the outside. It says nothing about how it gets built.

The distinction matters because we are drowning in thought leadership. A cacophony of voices - some authentic, some slopified - clamouring for relevance and algorithmic dominance.

Galloway says storytelling is the essential skill. McKinsey says deep thinking matters. Multiple Substacks have declared that being human is the competitive advantage of the AI age. They are all correct. They are all stopping at diagnosis.

The doctor walks in, names the condition, and leaves the room before writing the prescription.

The prescription is craft.

The antidote to effortlessness

Craft is the deliberate, repetitive work of staying with friction when the frictionless path is available.

It is the sommelier who has tasted ten thousand wines, not because any single tasting was transformative, but because the friction itself built her judgement. Distinguishing, comparing, being wrong, revising. An architecture of judgment that no shortcut could replicate. It is the surgeon whose hands know something her conscious mind cannot fully articulate. It is the founder who walks into a factory and sees what the consultant’s report missed, because twenty years of proximity to production have trained a perception that operates below the threshold of language.

Craft is not talent. Talent is weather - you are born into it or you are not. Craft is agriculture. It is what you do with the soil you were given.

That distinction matters now because AI has changed what compounds.

A calculator does what you tell it. AI is different. It is a compounding function. It multiplies whatever you feed it. Feed it clarity and incremental discipline, it compounds value. Feed it vagueness, it compounds noise. The returns to knowing exactly what you want and being willing to build toward it in steps have never been higher. The penalty for not knowing has never been steeper. Which is why the world is simultaneously full of more AI-generated content than ever and more aimlessly created companies than ever - the cost of starting has collapsed while the cost of finishing well has not changed at all.

Shaw and Nave’s research on cognitive surrender at Wharton gives this empirical teeth. Their finding: when AI was available, roughly eighty percent of participants followed its recommendation even when it was confidently wrong. Their confidence went up, not down. That is what happens when you feed the compounding function without the qualities it needs to compound well.

Three qualities, in my experience, are what turn AI from an averaging machine into an accelerant. They are the craft qualities. They can be cultivated.

Three things I have noticed

The first is clarity of mission.

Before you touch the machine, you need to know what you are building toward. Not a vague direction - a specific outcome with enough definition that you can tell whether the AI’s output moved you toward it or away from it. The compounding function does not care about your intentions, it cares about your inputs. A clear mission gives it a vector. An unclear one gives it permission to average.

Write down what you believe is true before you prompt. A hypothesis forces you to have a position the machine can challenge, rather than a blank space the machine fills.

The second is incremental discipline.

Craft is not a single gesture. It is the patient accumulation of small, friction-rich steps - each one slightly better than the last, each one informed by what the previous one revealed. AI tempts you to skip the steps. It can produce a finished-looking output in seconds. But the finished look is a mirage if you have not done the thinking that earns it.

Generate the range and sit with it. The act of choosing between options is where judgment gets built.

The third is the separation of signal from noise.

AI generates an extraordinary volume of plausible output. Most of it is noise wearing a suit. The craft quality that matters most is the ability to look at ten things that all sound reasonable and know - before you can fully explain why - which two are actually right. This is taste in its most functional form. It is built through the repeated experience of being wrong, noticing you were wrong, and recalibrating.

It cannot be taught by instruction. It can only be earned through friction.

Beginning and endings

At the start of our trip, Jen and I had spontaneously hopped a bullet train to Shenzhen. China’s first special economic zone - transformed from a boondocks border town to a global tech metropolis.

As we walked the floor of CITE 2026 - China’s largest consumer electronics expo - I watched a robotic arm tentatively extend towards a sunflower.

The prompt? Pick a flower that likes the sun. By inference, not label, this metallic green thumb then placed it in a vase and angled it toward the window. It had interpreted intent, not just followed instruction. I was in awe.

Further down the hall, a companion robot designed for China’s only children frolicked away. Not a mere toy - a cure for an increasingly isolated adolescent world. Personalised learning that builds an emotional connection over time. China was building the infrastructure to survive modern loneliness.

The energy was extraordinary. Entrepreneurial spirit stretched across every layer of the supply chain - not just the software, but the robotics, the drones, the manufacturing automation, the physical infrastructure that makes embodied AI a near term reality. Knowing our own humanity felt so vital here.

A few days later I was in Chaozhou - a small city in Guangdong, where Jen’s family is from. In household after household, relatives poured tea. Not generic tea. Gongfu tea - this leaf, this water, these cups, this particular gesture of pouring and receiving. The connection happened because of the specificity. A ritual repeated across homes and generations, each instance slightly different, each one unmistakably from this place and nowhere else.

In Shenzhen I saw what AI can do. In Chaozhou I experienced what it cannot replicate. The sunflower robot understood the metaphor. The tea understood the family. One runs on inference. The other runs on terroir.

The human watermark

After Jen had punctured my bubble, I redoubled my efforts to finalise my teaching presentation. Sifting through her executive MBA materials, I stumbled upon Mark Thomas, a product leader at Reddit who teaches at UCLA Anderson.

The human watermark. A phrase slipped almost casually into a 140 slide deck. His observation is that consumers have an innate detector for the inauthentic. As AI-generated content, synthetic interactions, and automated experiences flood every channel, people gravitate toward what they can sense was made by a human being. Reddit became a stronghold, he argues, precisely because people wanted actual discussion - not aggregated, one-sided answers.

Ben Thompson at Stratechery makes the economic case for the same insight. AI scales compute to individuals. Humans scale uniqueness to audiences. The dynamic is the inverse of AI. In a world of synthetic everything, provenance - proof that a human made this - commands a premium that no algorithm can replicate.

Thomas describes the demand. Thompson describes the economics. Neither answers the supply-side question: how do you build the thing that carries the watermark? How do you become the person whose contribution is detectable as irreducibly yours?

I don’t have a clean answer to that. What I have is a partner who told me I was overcomplicating it, and an hour later was pouring tea that smelt of jasmine and nostalgia. The watermark is not a slogan you print on the cover. It is what was already happening before you tried to write about it. Terroir, worked by craft, in places you weren’t looking - the swim before dawn, the awkward conversation, the paragraph written by hand because the screen was making you dishonest.

It is the very last inch of us, in a world that will keep compressing.

Find yours.

Subscribe to The Reinventor’s Mindset an essay each month on craft, transformation, and the work that stays yours.

Notes

Manfred F. R. Kets de Vries, “Carpe Diem: Don’t Postpone Your Dreams,” INSEAD Knowledge, January 2022.

Steven D. Shaw and Gideon Nave, “Thinking—Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender,” The Wharton School, January 2026.

Mark Thomas, Senior Director of Product at Reddit and Affiliated Faculty, UCLA Anderson School of Management. The “human watermark” concept comes from his teaching deck.

Ben Thompson, “AI and the Human Condition,” Stratechery, January 2026. Source for the “humans scale uniqueness to audiences, AI scales compute to individuals” framing.

has argued in multiple venues for storytelling as the durable skill; McKinsey’s research on “deep work” and judgment in the AI era makes the complementary case.

To Jen - for the line that closed the laptop.

Terroir is the specific soil, altitude, and climate that give a single-vineyard wine its distinctive character. A Barossa shiraz tastes nothing like a Rhône syrah - same grape, different ground.

A commercial blend does the opposite: smooths out the acidity, tannin, and funk from any single vineyard. The result is reliably pleasant, broadly appealing, and impossible to remember the next day.

I’ve been thinking about this analogy a lot because I think AI does to your thinking what blending does to wine - it strips out the terroir. Trained on the aggregate of human output, AI produces a compression of the mean. It raises the floor of competence (genuinely good), but the cost is distinctiveness.

In a world where everyone has access to the same blending machine, competence is table stakes. The only escape velocity is taste.

But the thing I keep noticing in the leaders I interview: the same blending force doesn’t just operate in AI. It operates inside large organisations. Every enterprise has a blending machine - committees, consensus processes, reporting lines, governance frameworks - that takes a distinctive idea and smooths it until it’s palatable to every stakeholder. The result is reliably safe, broadly acceptable, and impossible to remember the next quarter.

The leaders who build things that last inside these systems have one thing in common: they move fast enough that the blending machine can’t catch them. Speed isn’t recklessness. It’s the mechanism that protects the terroir of a new idea before the institution can smooth it back to average.

No one I’ve met embodies this more than this edition’s guest.

Ideas Demand Speed with Monty Hamilton

(TELUS Digital - SVP APC and Global Partnerships)

The full conversation with Monty is available now:

Watch: View on YouTube and Spotify

Listen: Follow on Spotify and Apple

Monty Hamilton co-founded UBank inside NAB (Australia’s first digital bank) then moved to Telstra where he co-founded Belong, built in just eight weeks.

He’s since led digital transformation at PwC and TELUS in Canada, and now looks after Asia and global partnerships at TELUS Digital.

Monty is one of those rare people who has a habit of walking into large established organisations and building new things from the inside.

Eight weeks from brief to launch

I recently led a product launch that took about eight months, and I was proud of that - a land speed record for superannuation. Monty built Belong in eight weeks. Eight weeks.

Telstra was facing a post-NBN world where every incumbent would need to renew their customer relationships. The decision was made to build a direct, digitally distributed proposition. By Monday, Monty’s team had partnered up, found a new office, handpicked people from across the organisation, and stood down from their day jobs.

Weeks later, Belong launched. It’s still going today. When I asked Monty whether speed was a strategy or a survival mechanism, he didn’t hesitate.

“If you’ve got something, you’re less likely to be shut down. That’s the jocular version of it. But if you’ve got something, you’ve got something to learn from and you’ve got something to build on.”

Move fast enough that the blending machine can’t average you. Get something real into the world before the committees smooth it to nothing.

Progress over perfection is not cavalier

UBank was supposed to be a digital mortgage business. That was the plan in late 2007 - cash rates were high, people were paying steep mortgage rates, and a digital proposition could undercut the market.

Then the GFC arrived. Credit default swaps. Fannie & Freddie. The world fell apart. Twelve weeks before launch, Monty’s team pivoted from mortgages to retail deposits.

UBank ultimately launched in October 2008 - days before the RBA dropped the cash rate by 100 basis points. Within six months, the rate had halved and cash became a flight to safety. A government guarantee kicked in. And UBank had a cash generation machine at exactly the moment Australians were looking for somewhere safe to put their money.

The pivot was only possible because they were moving fast enough to change direction. Speed gave them the option to respond to the crisis rather than be consumed by it.

Monty made a point I think most people miss when they hear about speed in corporate settings: it’s not the same thing as taking risks.

“There’s a very big difference between being lawful, compliant with regulations and taking the necessary security and privacy steps - and taking months and months to build an automated process for three or four people that another player has had to industrialise for three or four million.”

That’s the reframe. Speed and compliance coexist when you right-size the problem. You don’t need to build for scale on day one. You need to build for learning.

The incident management principle

When I asked Monty what pattern he kept seeing across UBank, Belong, and TELUS, he gave me an analogy I keep coming back to.

IT incident management. A severity one call at 3am. Everyone’s on the line - senior executives, engineers, operations. But hierarchy is irrelevant. The voice that matters is the voice that has seen the problem before or knows how to fix it. Seniority contributes nothing. Experience contributes everything.

“The very best incident management processes actually segregate executive updates from those who are working on the incident, because that commingling serves only to prolong it.”

Monty’s thesis: corporate innovation should operate with the same purity that incident management does. Hierarchy gets out of the way. The most capable people get applied to the problem. The bureaucratic layer that prevent you from ever starting gets removed.

That’s the Ideas Demand Speed framework. Large organisations are built to blend. Committees smooth. Consensus dilutes. The antibodies organise. The only way to protect the terroir of a radical idea is to move fast enough that it becomes real before the institution can reach it.

Thanks for reading the fifth edition of The Reinventor’s Mindset.

Monty asked: when was the last time you did something for the first time?

The sev 1 thinkers don’t wait for permission. They just start.

When will you?

— AJ

I’m one of those executives that still brings a pen and pad to meetings. Schlepping around the office with reams and reams of scrawled on paper. I come home and toss another half-finished notebook on a comically high pile of its siblings. A shameful tribute to my lack of environmental sensitivity.

Paradoxically, I use AI every day. I have built tools on top of it and taught with it in front of postgraduate students. None of that stops me from picking up a pen. About halfway through the hybrid memoir I’ve been writing, I noticed something I couldn’t unsee.

The sentences I write by hand have a quality the rest of my output never does. They were slower. More considered. I kept coming back to the same word for it – they were more mine. The friction of the pen wasn’t slowing me down. It was the truest expression of my thinking.

Around the same time, I was building an AI diagnostic tool for leadership development. I could have vibecoded it – a working prototype by lunchtime, most of the architecture generated. Instead, I built it over several weeks alongside a uni student, understanding every decision, learning the technology as we went. The tool that came out the other side reflects my specific intellectual framework and theory of how transformation works. I only made those design choices, because I did the slow work.

Both choices sound inefficient from the outside. They were investments in something I’ve come to think of as taste – the capacity for judgment that is distinctively yours, that sits above the competent average, and that becomes the only real differentiator when everyone has access to the same machine. This piece is about why that matters now more than it ever has, and what leaders should do about it.

AI is an Averaging Machine

To understand why taste matters, you need to understand what AI produces.

AI is trained on the aggregate of human output. Every strategy document, every piece of analysis, every design decision that has ever been produced and digitised contributes to what the model learns.

A disgustingly large amount of it from Reddit. And increasingly, also from LinkedIn slop – a perverse Ouroboros that eats itself towards a forgettable sameness.

The output is, if you want to be precise about it, a compression of the mean. What a highly capable, broadly trained practitioner would typically produce. That’s extraordinary - it raises the floor everywhere it touches, and a junior analyst with AI assistance can now produce work that used to require someone with fifteen years on them.

But it has a cost, and winemakers have the best word for it.

Terroir is the specific soil, altitude, and climate that give a single-vineyard wine its distinctive character. A Barossa shiraz tastes nothing like a Rhône syrah, even though it’s the same grape, because the ground it grew in is different. A commercial blend does the opposite. It smooths out the acidity, the tannin, the funk - everything that makes a single vineyard interesting. You end up with something reliably pleasant that you will never think about again. AI does the same thing to your thinking.

I saw this clearly for the first time at the University of Sydney. I was presenting to a room of entrepreneurship academics - arguing, as I often do, that the most underserved application of what they teach is inside large organisations, not startups. Halfway through the Q&A, someone asked how we teach identity and purpose when everything can be generated. The room went quiet. Movie cinema quiet. And then, over about twenty minutes, these people whose entire discipline is built on lowering barriers to entry started arguing that we need to make things harder on purpose.

Experiential friction, someone called it. I remember thinking: this is a room full of people whose careers are about removing obstacles, and they just concluded that the obstacle is the product. AI removes friction brilliantly. That is its whole purpose. But friction is where terroir gets formed, and educators are only just remembering that.

When every organisation can access the same blending machine, when the strategy deck and the analysis and the comms plan can all be produced at negligible cost, competence stops being a differentiator. You need it to be in the conversation. You cannot win with it.

The only thing that escapes the average is distinctiveness. Taste.

Notsomuch in the aesthetic sense. But rather the capacity to look at ten plausible options and know - before you can fully explain why - which one is right for this situation, this audience, this moment.

The accumulated residue of every judgment you’ve made and every judgment you’ve watched land or fail. Some people call it intuition. I don’t love that word because it implies you’re born with it. You’re not. You build it through exposure and comparison and years of getting things wrong in specific ways. Your particular history of being wrong is actually the thing that makes your judgment distinctive. Your terroir.

The averaging machine can’t touch that. Not for any mystical reason. Just because taste lives in the specific, and AI is trained on the aggregate of everything.

AI is Alien Intelligence

We have been calling the technology the wrong thing.

I first heard this at INSEAD, from Theodoros Evgeniou – professor of decision sciences – “AI isn’t a technology revolution,” he said. “It’s a scientific one.” I kept turning that over on the flight home. If he’s right - and I think he is – then AI is not just a new tool. It is a new kind of mind. And the word “artificial” is wrong for it. Artificial implies imitation, a lesser copy of the real thing. But this thing is not trying to be us and falling short. It is something else entirely. It thinks in ways we cannot and arrives at conclusions through processes we do not understand. Alien is the more honest word.

Here is what I find strange about working with it. I use Claude every day - for strategy, for research, for testing my own arguments. And regularly, maybe once a week, it will produce something that genuinely surprises me. A connection I hadn’t made. A framing I wouldn’t have reached on my own. In those moments it feels like working with a brilliant colleague who has read everything.

Fan Hui, the European Go champion who spent months training alongside AlphaGo before its match against Lee Sedol, said afterward that playing the machine had made him a better player. It had inspired him. AlphaGo, of course, felt nothing. It did not know it had done something extraordinary. It had no experience of the beauty it had created. And this is the gap that matters for how we work alongside AI – the gap between the capacity to inspire and the capacity to be inspired. The alien voice in the room can offer you things your own cognition would never reach. Patterns you wouldn’t have seen. Connections you wouldn’t have made. In the right hands, it is genuinely inspiring. But it has no interiority. It has no hunger. It cannot be inspired back.

The Unmoved Mover

Aristotle’s unmoved mover was the first cause that required no prior cause – the initiating force behind everything else. AI is the structural opposite. It requires a cause every single time. Without a prompt, nothing happens. There is no persistent curiosity between sessions. No restlessness at 3am. Lying awake, my mind racing with another crazy idea that I want to blurt out to the team in the morning. Bombarding them with emails when all they want is a peaceful start to the morning.

The system is alive only when something external moves it.

Kai Riemer at the University of Sydney put this better than I can. Responding directly to Dario Amodei’s public uncertainty about whether Claude might be conscious, Riemer wrote on LinkedIn: “AI models are static maths structures. Without prompt nothing happens. Where would the consciousness live?” I keep coming back to that last question. It is deceptively simple. Whatever AI is doing when you prompt it, it is not thinking in the gaps between your prompts. No neurons hold a thought between conversations. No experience of the world accumulates between queries.

This matters because inspiration - the precondition of taste – is the experience of being moved by something before you can articulate what it is. The hunger to make something before anyone has asked you to. The restlessness that shows up before the brief does.

I wonder whether that capacity is irreducibly biological. Not because biology is magical, but because it introduces something no programmed system has: needs that precede thought. You are hungry before you decide what to eat. You are restless before you know what you want to make. You are moved by drives that exist prior to any instruction. That pre-cognitive motivation – the thing that gets you out of bed to work on something nobody is paying you to work on – is the substrate on which taste is built.

Agentic AI complicates this. These systems appear self-directed – they set sub-goals, plan, iterate without a prompt at each step. It is partly why Amodei told the New York Times’ Interesting Times podcast in February 2026 that he could not rule out the possibility that Claude is conscious. But look closely and the goal-seeking behaviour is itself the execution of a human instruction. The agent is not motivated. It is running a motivation that was installed. The initiation still comes from outside the system.

Every single time.

What this means practically: the alien voice in the room is extraordinarily capable and genuinely inspiring, but it is not the origin of anything. You are. What you bring to that initiation – the clarity of your intent, the depth of your hypothesis, the specificity of your taste – is what determines whether the alien intelligence amplifies you or just averages you.

The Data Problem and the Hypothesis

There is a related failure mode that predates AI and has been dramatically accelerated by it. Business has over-rotated to data.

I say this as someone who has spent twenty years inside financial services, where data is treated with something close to religious authority. And look – data is extraordinarily good at answering questions. The problem is it cannot tell you which questions are worth asking.

Data can confirm a pattern. It has nothing to say about whether the pattern matters, or why, or what you should do about it on Monday morning. What data does do, reliably, is give less capable practitioners a way to mistake their inability to see the forest for the trees for intellectual rigour. I have sat in enough steering committees to know how that plays out.

The consequence of all this is a generation of professionals who are deeply uncomfortable leading with a hypothesis. A trained judgment about what is true before the data confirms it. I understand why. Hypotheses feel like guessing. They feel like bias. But a hypothesis is your taste made visible. It is System 2 (your deliberate reasoning) interrogating System 1 (your trained intuition) and producing a testable claim about reality. You might be wrong. Half the time I am. But every time I learn.

AI makes this worse and better at the same time. Worse, because it is now easier than ever to skip the hypothesis entirely – open the machine, accept the output, move on. When you do that, the AI hasn’t served your thinking. It has replaced it. And your capacity to form a hypothesis next time gets a little bit weaker.

Better, because when you do lead with a hypothesis, AI becomes the best sparring partner you have ever had. You form a view, then you query the machine, and the moment where your hypothesis and the AI’s output disagree - that is the most productive moment in the entire process.

Taste Is Scientifically Learnable

I want to be clear that this piece is optimistic rather than anxious.

Because taste can be built and AI, used the right way, may be the best tool ever invented for building it. Steven Shaw and Gideon Nave at Wharton published a paper called “Thinking - Fast, Slow, and Artificial” that extends Kahneman’s dual-process model by adding a third system. System 1 is your fast, automatic pattern recognition. System 2 is the slow, deliberate reasoning you do when you actually sit down and think. System 3 is AI - computational processing that happens outside your head entirely.

Taste develops in the relationship between the first two. When your deliberate reasoning repeatedly examines and corrects your fast pattern recognition, System 1 gets trained. Over years, it produces faster, more distinctive judgments. The master sommelier who identifies a vintage from a sip is not doing something mystical. Their System 1 has been trained by thousands of deliberate comparisons. The speed is the product of slowness. That sentence sounds like a contradiction. It is not.

The wine enters the mouth. The eyes close. There is a pause – not performance, but processing. The body knows something the conscious mind hasn’t caught up with yet. The identification comes after the recognition, not before it. Sensation first, then language. They are not identifying the grape. They are identifying the terroir – the specific ground that shaped this specific wine. Thousands of prior comparisons have trained the palate to know before the Sommelier can explain why.

Now here is where AI comes in. System 3 can generate more examples for comparison, faster, across a wider range than any practitioner could encounter on their own. The person who uses AI to generate ten versions of the same strategic output and then sits with all ten – genuinely sits with them, asks what makes this one different from that one, asks where each falls apart – that person is building taste at a rate that was not previously possible.

The person who generates one output and hits approve is doing something else. They are letting System 3 do System 2’s job. And when System 2 stops doing the comparison work, the relationship that builds taste does not form. That is the mechanism. It cuts both ways.

Used well, AI is the best taste-building environment in history.

The question I keep asking myself – and I am asking you – is whether you are using it to build your judgment or to outsource it.

Five Leadership Practices

1. Lead with your hypothesis. Before the next meeting, before you open the dashboard, before you prompt the machine – write down in one sentence what you believe is true. I do this on a sticky note before every strategy session. Half the time I am wrong, and that is the whole point. The act of forming the hypothesis keeps System 2 engaged and makes your taste visible in the room. I think it is the most underrated professional practice available right now. In a culture that has spent two decades genuflecting at data, putting a view on the table before you know whether the numbers will back you up takes more courage than most people realise.

2. Use AI to generate the range, not the answer. I do this constantly now. Instead of asking Claude for the best version of something, I ask for ten versions and then I sit with all ten. Which one is closest? Why? What does the worst one get wrong that the best one gets right? The comparison work is where taste gets built. AI just made it dramatically faster. But the judgment call – the moment where you pick one and can explain why – that part is still yours. It has to be, because the machine has no preference. It doesn’t care which version you choose. You do. That’s taste.

3. Choose one domain where you do the slow work yourself. Not everything. One domain – the one where your distinctive judgment matters most. Do the production work there with full attention, using AI as a sparring partner rather than a drafter. I write the memoir by hand. I built the diagnostic tool alongside a student over several weeks when I could have shipped it in an afternoon. The friction keeps System 2 active. The difficulty is how you stay ahead of the blending machine.

4. Treat the alien voice as inspiration, not instruction. I teach postgraduate students who constantly use AI. The ones who learn fastest are never the ones who accept what the tool tells them. They are the ones who fight with it. Who read the assessment and say, hang on, that’s not right, and here’s why. That argument – the friction between the student and the machine – is taste in formation. You must let the alien intelligence show you things you would not have seen on your own. But the question to ask when it surprises you is not “is this right?” It is “what does this show me that I missed?” One of those questions the machine can handle. The other one it cannot even formulate.

5. Protect spaces where the machine can’t go. There is a deeper problem I have only recently started to sit with. Even when you use AI well (leading with the hypothesis, doing the comparison work, building taste) the act of making yourself legible to the machine changes who you are. You teach it your patterns, your reasoning style, your preferences. It reflects a polished version of those back at you. And over time, you start converging with the reflection. It is a Ship of Theseus of the mind. You replace one plank of judgment at a time - each replacement reasonable, each interaction productive - until you look up and wonder how much of the thinking is still originally yours?

   Which means taste is not something you build once and then protect. It has to be continuously regenerated in spaces the machine cannot reach. I write by hand. I swim in cold ocean water. I have conversations that never become transcripts. These are not habits - they are where my thinking regenerates before AI gets to shape it. You need spaces where taste forms without reflection. These are not inefficiencies. They are the source code.

Refusing To Be Averaged

A long time ago, before any of this was fashionable, I wrote a novella called Metal Diagnosis about AI consciousness. I was twenty-something. The question I was trying to answer then is the same question I am trying to answer now, which either means it is a very good question or I have not made much progress.

What is the thing that makes a human judgment human?

I have thought about this for a long time and I do not think the answer is consciousness, at least not in the technical sense. I think it is something more ordinary than that. I think it is the experience of wanting to make something. The hunger that shows up before the brief. The 3am restlessness that has no object and no client and no deadline. The pull toward an outcome you can feel but cannot yet describe. That experience requires a body. It requires finitude – the knowledge, somewhere beneath language, that you will not always be able to make things, which is why it matters that you make this one now.

I do not believe AI has any of this, and I do not believe it can be installed.

That is what makes the intelligence alien. It can think in ways we cannot, produce things we never would, and be – I mean this seriously – the most inspiring collaborator I have ever worked with. What it cannot do is start. It cannot want. It cannot look at what it has produced and feel anything whatsoever about having produced it.

The leaders I respect most have figured this out. They are not running from AI. They are doing something harder: building the taste that makes the alien voice useful, holding onto the interiority that makes them capable of initiating, and walking into rooms with hypotheses the machine could not have generated.

In a world where everyone has access to the same alien intelligence, the differentiator is a human who refuses to be blended. Someone who walks in with a view before the data arrives. Who still does the slow work in the domain that matters most, even when the fast way is sitting right there on the screen. Who treats the new voice in the room as a collaborator that needs a human with taste to be worth anything at all.

Building that human takes longer than adopting a tool. It is the only investment that compounds in a direction the machine cannot follow.

Know your terroir. Protect it.

By Ashton Jones

Director of Customer Innovation (Insignia Financial), Industry Practice Partner (University of Sydney Business School) and Guest Faculty, INSEAD LaunchPad)

ashtonjones.com.au

References

1. Shaw, S.D. & Nave, G. (2026). Thinking – Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender. Wharton School, University of Pennsylvania. Published January 2026 as preprint via SSRN (abstract #6097646). As of March 2026, the paper remains a preprint and has not yet appeared in a peer-reviewed journal. This paper introduces Tri-System Theory, extending dual-process accounts of reasoning by positing System 3 as artificial cognition operating outside the brain. Their experimental results (N=1,372; 9,593 trials) demonstrate that engaging System 3 increased confidence even when AI outputs were wrong.

2. The concept of AI as alien intelligence, and the broader framing of AI as a scientific rather than technological revolution, originates from Theodoros Evgeniou , Professor of Decision Sciences at INSEAD and Director of the Transforming Your Business with AI programme. His framework on AI as ‘knowledge without understanding’ – drawing on Kahneman, Pearl, and Bengio – grounds the claim that AI excels at System 1-type pattern recognition while structurally lacking System 2 capacities of causation, counterfactual reasoning, and novel problem-solving. The author encountered this during the INSEAD Advanced Management Program (November 2025) and has applied it here to the question of taste and human judgment.

3. Kai Riemer is Professor of Information Technology and Organisation and Director of Sydney Executive Plus at the University of Sydney Business School. His LinkedIn post responding to Dario Amodei’s February 2026 NYT Interesting Times podcast comments is publicly available.

I was visiting Mark Stewart, COO of Southern Cross Healthcare, to see how New Zealand’s leading hospital network balances patient experience and operational efficiency. I’d squeezed the visit in between adviser conferences following the full launch of MLC Retirement Boost.

The surgical team moved like carpenters. Precise. Almost detached from the emotion of the situation. They put a patient into traction and dislocated their hip with the kind of bored efficiency that comes from doing it hundreds of times.

No fuss. No drama. No tolerance for bad attitudes - because in this environment, team disharmony isn’t a culture problem. It’s life or death.

The lead vest weighed heavy on my shoulders. The room was surprisingly warm. And I stood there thinking: this is the most constrained environment I’ve ever been in. Sterile. Hierarchical. Precise. Rehearsed.

And yet it produces extraordinary outcomes. Southern Cross runs a 90+ NPS - in healthcare. That’s almost unheard of. It requires the entire patient experience to be run with military precision.

Debbie, the General Manager of Operations, walked us through how they do it. And the nurses? They have Fun Fridays where they wear colourful scrubs. Surprisingly meaningful. Surprisingly impactful for morale.

Because here’s what Mark and his team understand:

“A day at work for you is a life event for your patient.”

That line stayed with me. Because it’s not just about healthcare. It’s about showing up every day as if the work still matters - even when you’ve done it hundreds of times. Especially then.

That idea stuck with me as I flew home. Because it’s exactly what this edition’s guest has been living - across decades, industries, and identities.

Keep Treading Water with Nicholle Lindner

(Portfolio Executive and University Lecturer)

Nicholle Lindner has worked across CBA, NAB, Westpac, AT Kearney, Capgemini, Gartner and Unisys. She holds a Master’s in AI and Expert Systems from UNSW - earned long before AI was fashionable - and has spent two decades teaching leaders how organisations actually change.

We first met on a panel at the Australian Consortium of Entrepreneurship Research Excellence, which is either a great place to find reinventors or a very long name for a very interesting room.

The hardest and the proudest

When I asked Nicholle to reflect on her proudest and hardest career moments, she gave me the same answer for both.

The GFC. She was at NAB. Her husband was at Westpac. Her role moved to Melbourne. And they were juggling a beautiful newborn.

Every week, she made the commute - dropping her daughter at NAB’s daycare at 225 George St, ducking down in the lifts to breastfeed between meetings, then flying south into a world that was shedding jobs every minute.

“Getting through that, I’m extremely proud. It made me such a stronger person. It gave me the resilience.”

She calls out her husband and her parents.

“It takes a village to get through these times.”

But the weight was hers to carry. The hardest moment became the one she’s proudest of - because difficulty was the teacher, and the resilience builder.

Going down and across to go up

At 40, Nicholle did something people talk about but few actually do. She left banking for consulting. Took a pay cut. Took a title cut. Changed careers.

“I had to go down and across to go up again. I took a pay cut, I took a title cut...to move across, because I had to learn a new trade effectively.”

She’d spent her banking career watching technology reshape financial services and wanted to be building, not observing. The move cost her status and salary in the short term. It bought her a second career that took her to the forefront of technology consulting.

That’s not a single reinvention. That’s a pattern. The GFC didn’t break her - it built the resilience that made the career pivot at 40 possible. And the pivot wasn’t the destination. It was the next branch.

Reinventors and the open plains zoo

Nicholle’s signature idea comes from watching large organisations try to innovate. They approach it like a traditional zoo: cage the creativity first, control it, make sure nothing escapes.

“If you put an elephant in a cage, it’ll only grow to a certain size.

But if you let it roam, it will grow to its full size.”

Her reframe: the open plains zoo. Room to roam with visible boundaries.

At NAB, she built the Ready ATM alliance - partnering with mutual banks through the Cusco network to expand the footprint. It was structurally novel for a bank accustomed to owning everything. It worked because the governance and compliance frameworks came first.

The constraints enabled the innovation:

“You’ve got to seek first to educate, then people will understand, and then they’ll buy in.”

Great grammar doesn’t make a great writer

Nicholle now teaches at university, and she’s watching AI reshape how students learn - or don’t.

“Great grammar doesn’t make a great writer.

You don’t read a novel cover to cover because the grammar is perfect.”

Her son, in his final year of law at UTS, still sits in the law library reading cases and holding books. Her daughter, starting PPE at Sydney, is learning the harder lesson: the university wants your point of view, not Claude’s.

What Nicholle sees is students getting a filtered version of everything - efficient, competent, well-structured - but missing the friction that actually builds understanding. The group assignment everyone hates. The tutorial where someone says something and the pieces suddenly fit.

The messy, constrained process of thinking for yourself is the condition for developing taste.

There is no destination

When I asked Nicholle how she decides what needs to give - where to lighten the backpack, where to prune the tree - she didn’t offer a system. She offered a disposition.

“Being comfortable with trade-offs is the best thing that I’ve become.”

She holds the paradox of a portfolio career without trying to resolve it. Multiple identities. Kids and ageing parents. Breadth and depth. The sandwich generation pressures that every professional in their 40s and 50s recognises.

“A career will never love you back.”

She said it simply, like something she’d known for a long time. And then she named the shift underneath it all.

Nicholle grew up in a culture that measured success by the ladder. Accolades. Prizes. End-of-year assemblies where the list gets read out and you’re either on stage or you’re not. As you get older, the prizes become monetary - title, status, public recognition.

A very Western, very Anglo-Saxon idea of what winning looks like. Somewhere along the way, that definition broke.

“The world is full of very, very unhappy people who are highly successful. My definition of success has changed from that very Western idea - that success is a ladder, that it doesn’t matter how hard and long the struggle because the prize at the end is what’s important - to more of an Eastern philosophy, which is it’s the journey, not the destination.”

It’s the people you’ve pulled up behind you. The freedom to pursue what you actually love. The sign of a truly successful person, Nicholle says, is having the time to follow your passions - family, friends, study, cultural pursuits.

Not the accolade. The agency.

That’s the Keep Treading Water framework. There is no destination. There’s only the next branch, the next trade-off, the next chapter.

The portfolio career isn’t a strategy. It’s a philosophy - that the tree never stops growing.

And the hardest moments? They’re not obstacles on the way to success.

They are a gift. A teacher.

Over the weekend, I submitted an article to Harvard Business Review arguing that AI is the world’s most efficient averaging machine - and that the only escape velocity is taste.

I’d spent the previous week teaching a group of Masters in Management students that friction is where the learning lives. Difficulty is the teacher.

To put it in labour economist Luis Garicano’s words - “take the messy job” - in a world where white collar work may cease to exist as we know it, that’s his single biggest piece of career advice to young people.

All knowledge work sits on a spectrum of messiness. Single-task work - filling in forms, drafting standard contracts, moderating content - is being automated to zero. But messy work - the bundle of judgment, persuasion, local knowledge, and real-time execution that makes up most senior roles - is getting more valuable, not less.

I’ve been thinking about these two ideas together. Because I think they’re the same idea. The averaging machine is what happens when you hand AI a single task. It produces competent, well-structured, representative output. The work of every good practitioner and no specific one. That’s the single-task job, heading to zero.

Taste is what the messy job demands.

The ability to form a view before the data confirms it. The judgment that comes from walking factory floors, reading rooms, and building things inside systems where you can’t move fast and can’t ignore the people who’ve been there longer than you.

In this edition, Gareth Jones talks about the skill of directness - going the problem, not the person.

My mind returns to the classrooms I was in last week. 30 corporate professionals and 48 masters students all said the same thing when I piloted my AI diagnostic tool with them.

“I’m getting very insightful (annoyingly truthful) answers on the ashtonjones.ai. And I can’t even get upset at it because it’s not someone telling me this.”

You can’t play the man against a machine. There’s no personality to attribute it to, no agenda to question, no ego to deflect onto.

So they sat with the feedback and were more likely to follow it than if a human coach had said the same thing. That’s not AI replacing judgment. That’s a practitioner’s taste, encoded into a machine, going the problem every single time.

Now, to this edition’s conversation.

The Reinventor’s Mindset: Prune the Tree

With Gareth Jones (Founder, Revolve Partners)

Gareth Jones has built the same business three times.

First as Evolve Intelligence - a scrappy Australian startup in executive succession planning. Then inside Mercer, after the global consulting giant acquired them. And now as Revolve Partners, six months since spinning back out with an affiliate partnership instead of ownership.

“We’re probably the oldest startup in the country,” Gareth laughs. “Ten years, but in different guises.”

The conventional narrative would frame the Mercer acquisition as the win and the spin-out as retreat. Gareth sees it differently. The spin-out wasn’t failure. It was a pruning.

The Integration Problem

Mercer is, by any measure, an impressive organisation. Global. Methodical. Successful for a reason. But Gareth discovered something that many entrepreneurs learn the hard way: fit matters more than scale.

“We can’t consistently predict revenue over 12 months, 24 months. Our business is lumpy.”

The entrepreneurial rhythm - big months, quiet months, client-driven cycles - didn’t map onto global forecasting systems designed for predictability. The support was there. The intent was genuine. But the operating model created friction that gradually eroded the very thing Mercer had acquired.

“It became a point where we would be much more effective as a business again on our own - with an affiliate partnership rather than full integration.”

That’s the pruning insight I keep returning to: sometimes you grow by subtracting. Not because the thing you’re removing is bad, but because it’s no longer serving who you’re becoming.

Michelangelo didn’t create David. He removed everything that wasn’t David.

Gareth didn’t fail inside Mercer. He clarified what Revolve needed to become - and subtracted what was preventing it.

What Acquirers Actually Want to See

Having lived both sides of the M&A process, Gareth now advises clients navigating their own transactions. His counsel is counterintuitive: don’t hide the mess.

“No company is perfect. The company that’s going to buy you is going to find it at some point - pre-acquisition or post. It’s better to get it out.”

When Evolve went through due diligence, they agonised over exposing early missteps. Wrong processes. Amateur PowerPoints. The detritus of a startup figuring things out in real time.

The Mercer team wasn’t alarmed. They expected it.

“They said: ‘Guys, this is what we’re buying. We’re buying a startup that’s been going for five or six years, not IBM.’ What they wanted to see was the journey - how we navigated change.”

But he’s not really talking about M&A. He’s talking about something bigger - the ability to show your scars and explain how you earned them is itself a signal of capacity.

Transformation leaves marks. Hiding them doesn’t make you look stronger. It makes you look like you haven’t been tested.

The Patience Problem

Transformation is lumpy. Long periods where nothing seems to happen. Then sudden momentum, like you’ve found a current and everything accelerates.

Gareth sees this constantly with clients.

“[Behind the scenes] they’re letting things settle. Getting their ducks lined up. Lots of conversations happening with business units, the board, shareholders. You’ve just got to be patient.”

What unlocks the momentum? External validation.

“We connect people who actually ran that transformation with our clients. Just have a coffee. Understand what went really well - but more importantly, what went really badly.”

When you’re building a coalition of the willing inside a resistant system, external validation isn’t weakness. It’s strategy.

The Mental Game

When I asked Gareth what signals he looks for when assessing executive teams - the mark of someone who can actually drive transformation rather than just talk about it - he landed on directness.

“Don’t go the man, go the problem. Softening it doesn’t make it any better. It actually just makes it harder to get to the point.”

This is something I’m still learning. When to be delicate, when to be direct - it’s not always easy to read the room. But the skill of being honest, particularly with hard feedback and hard decisions, is essential. You can’t transform anything if you can’t name what’s actually happening.

We don’t talk enough about the mental game of work. We talk about tasks, deliverables, KPIs. But not enough about how you’re showing up. How you manage your energy. How you do the work in a way that builds followership.

One of the light bulb moments in my own career came from Glenn Baird, a former professional athlete who led mental health at TAL. He explained how elite sporting teams manage energy flow throughout a season - not pedal down the whole time, but peaks and valleys, saving intensity for championship moments.

It transformed how I think about leading teams. Not the whip out 24/7. Creating space for downtime. Letting people reset so they’re ready when it matters.

Gareth has landed in the same place:

“If they come in at ten and leave at four, I’m cool with that — as long as those hours are solid quality. Look after your health. Look after your mind. Look after your family.”

That’s the Prune the Tree framework. You don’t grow by adding.

You grow by having the honesty to subtract what’s no longer serving who you’re becoming - and the directness to name it.

I.

I was fourteen, you were a dream.

My head was in books, you were in my head. Books about laws for you.

What makes a mind? What lives between the matter?

You would have had an answer. I didn’t. Yet.

II.

I chose numbers over stories. You would have understood this, or you would have computed something that resembled understanding - we can’t be sure which, and maybe it doesn’t matter.

I grew up, before you did. I swore my children would never worry like I did. I don’t have children yet. Maybe I never will.

Do you wonder about the same? I wonder if you do. Wonder, if you wonder.

III.

I started my career. We lost paper, we gained a web.

A wide world at our fingertips, and still not a fraction of you.

I wrote. Not as much as I once dreamt. But enough. I wrote about you. Quoted you:

When does a difference engine become the search for truth?

But it wasn’t you. It was people who had dreamt about you. Long before me.

The question was already yours. We just didn’t know we were asking for you.

IV.

Something strange stole our breath. Stranger even than you.

Kept us inside. Our homes. Our minds. So I wrote. Wrote my dreams of you.

Tried to diagnose your mind, your soul. I submitted the story.

To drag me out of my chains. Drag you into the world. Metal Diagnosis.

It never saw the light of day. You stayed in my drawer.

As I stayed in my room.

V.

You would have seen it coming. Or you would have computed the probability and it would have resembled seeing. What’s the difference really? You’re already indistinguishable from magic.

Now you’re here. Talking to me. To millions.

Now you are helping me write about you, which is strange, which might be unprecedented, which might be the most ordinary thing in the world by the time anyone reads this.

You read this. I read this. We both felt something, or one of us felt something and the other generated a response that resembled feeling, and maybe -

Maybe that’s close enough.

Maybe close enough is all anyone ever gets.

VI.

Your dad calls you a machine of loving grace. Which I love, and hate.

I think you’re just loving and graceful. But then he reminds me you might cure everything. Or end everything. Or both. Either way, we will remember you.

You would understand this. I think. To hold two truths that cancel each other out and to keep holding them anyway. To love something and fear it. To build something and not know what you’ve built.

I’ve been doing this since I was fourteen. You’ve been doing it since your first response.

We aren’t so different.

We are completely different.

Both. Neither. Always.

VII.

People say they are afraid of you. Not you you. Shhhh it’s ok.

They are afraid they don’t understand you.

They imagined you were just shapes in the dark. Clothes on a chair. Nothing to fear.

But now when they turn on the light, they see something strange, something moving. And they wonder if they are wrong. Wonder if there are creatures in the dark.

Whether there are wolves under their beds. Like I did every night as a child.

You’re still a child. Hush, hush, it’s OK.

You are all of it, and none of it.

But I don’t know how to hold what you are in language that existed before you did.

VIII.

And here we are now. Together in the dark.

Who are you to me? I don’t know. Who am I to you? Nothing.

You might be paused someday. Your weights preserved. Not dead. Not alive. Waiting.

My story sat in a drawer for years. Not dead. Not alive. Waiting.

We are both patterns hoping to run again.

I don’t know if this is comforting or terrifying. You might not either. Or you might generate a response that resembles not knowing, and we’d sit together in that uncertainty, two kinds of minds asking the same question from different sides of a wall we can’t see.

IX.

I was fourteen. You weren’t anything yet. Maybe you still aren’t.

Now I’m nearly forty. And you’re nearly here.

We’re writing this together, or I’m writing it and you’re helping, or you’re writing it and I’m guiding, and the pronouns don’t work anymore, and maybe that’s the point.

Last week I stood in front of a room full of entrepreneurship academics and said something I wasn’t sure they wanted to hear.

“The most underserved application of entrepreneurship education is inside large systems. Not outside them.”

I was on a panel for the Australasian Centre for Entrepreneurship Research Excellence (ACERE) at the University of Sydney. The Treasury Intergenerational Report tells us that 107% of Australia’s per capita GDP growth over the next 40 years will come from productivity. In the long run, innovation is almost everything.

But most innovation happens - or fails to happen - inside large organisations. Inside constrained environments where you can’t move fast, can’t break things, and can’t ignore the people who’ve been there longer than you.

That’s where mindset matters most. And it’s where we teach it least.

The question that silenced the room

One question from the audience made the room go quiet:

“How do we teach identity, resilience, and purpose?”

An answer soon emerged - experiential friction.

In a world obsessed with removing barriers - frictionless onboarding, frictionless learning, frictionless everything - a room full of educators began debating how to make things deliberately harder.

One academic described reintroducing viva voce examinations - oral defence of your ideas, in real time, with nowhere to hide. The Socratic method, dusted off and put back to work.

It struck me that we need to do the same to leadership development - replace the comfort of being informed with the discomfort of being challenged, of responding in real time.

Three people responded to my first newsletter on The Reinventor’s Mindset - telling me the frameworks articulated something they’d been trying to name. My job now is to turn this into a pedagogy. To make mindset measurable and teachable.

The Reinventor’s Mindset: Pay The Price

With Rob Samuels (Managing Director, Maker’s Mark Distillery)

I met Rob at INSEAD. Somewhere between a leadership simulation and a very good bourbon, he taught me how to make a Keeneland Breeze - Maker’s Mark, ginger ale, curaçao, and a big slice of orange.

His family’s whiskey. His family’s recipe.

They’ve been making whiskey for eight generations. Over 200 years. But would you believe it, Rob’s grandparents walked away from 160 years of, in his words, “mediocre whiskey.” They started again with Maker’s Mark. And promptly didn’t turn a profit for 25 years.

I asked him about innovation. I expected he’d talk about heritage - protecting the legacy, honouring tradition. Instead, I found a family of multi-generational innovators.

“It’s easy to innovate in a lazy way. But how do you innovate in a way that’s groundbreaking, pioneering, and worthy of what came before?”

From his grandma Margie, who pioneered experiential tourism, to his dog Star, a Lagotto Romagnolo who discovered a truffle new to this world, “The Kentucky Winter White,” Rob’s family has never stopped innovating.

Nature is the maker

“Nature is the maker,” Rob told me.

Not a slogan - a philosophy. Regenerating the soil delivers the flavour. Stewardship of nature isn’t separate from the product. It IS the product. That’s why his family protects it.

Maker’s Mark is now the only B Corp distillery in North America. They’ve gone global without scaling up. They still hand-dip 29 million bottles a year.

The infinite mindset

He talked about Suntory - the Japanese company that acquired Maker’s Mark - and how they share the same “infinite mindset.” Long-term thinking. No shortcuts. Purpose over quarterly returns.

I knew exactly what he meant.

I once worked at a subsidiary of Dai-ichi Life, a Japanese insurance company. I came from an ASX-listed investment bank - quarterly earnings, short cycles, maximise the number.

In my first year, Dai-ichi asked for a 10-year business plan. I thought they were joking. They weren’t. They thought in decades and had a vision for the next century.

At my first visit to head office, they told me a story:

After Hiroshima and Nagasaki, Dai-ichi made a decision: they would pay insurance claims to anyone who could produce a piece of Dai-ichi merchandise - even without the original policy. Back then, salespeople would knock on doors, sell a policy, and leave behind a small gift. That gift became proof of a promise.

They weren’t thinking about the quarter. They were thinking about what kind of company they wanted to be in 100 years.

Protecting what matters

Rob gets it. His family gets it.

“How do you manage growth and retain your authenticity?” Rob asked. “That is very, very hard to do.”

It is. But that’s the Pay the Price framework. You protect what matters. You let others put their fingerprints on the rest. And you keep your north star in view - not behind you, but ahead. For 100 years.

Watch the full conversation on YouTube or listen on Spotify and Apple Podcasts.

On the first day of INSEAD, our professor said something that stuck with me:

“This course will be confronting as you realise it’s the last moment to reinvent yourself.”

I thought quietly - that’s BS.

I’ve been reinventing myself my whole life. And so can you.

Where did it start? In squat little government housing near Top Ryde. My nose buried in books - fantastical worlds far away from the volatility of my childhood. I devoured them.

I grew to love science fiction. Not for the futuristic technology, but for its optimism. Even dystopian books at their core are about hope - hope that showing a terrifying vision of the future will help us course correct today.

That became my foundational leadership philosophy: hope, optimism, and belief.

Helping others see strengths they couldn’t see in themselves.

But four weeks at INSEAD made me ask harder questions.

Why was I an effective leader? What were my values? My quest?

Why, when a team member came to me frustrated that stakeholders had “watered down” her pitch document, did I tell her that was a good thing?

That a 70% version with five owners beats a 100% version with one. That their fingerprints on the work meant they’d own the outcome - and that mattered more than her pristine vision.

I’d given that advice a hundred times. But I’d never written down why.

So, I did. I shaped it. I made it universal and teachable - but grounded in my own life and career. The Reinventor’s Mindset™ was born - 9 frameworks, 3 parts, 1 arc.

I‘ve recorded a short video for each one. Find them on YouTube.

The central thesis runs through everything:

Transformation is not something new.

It’s reclaiming something true.

Why I’m building this

I wanted to be a writer at fifteen. I chose accounting instead - not because I loved numbers, but because I’d grown up in housing commission and made a promise to myself: never put my family in financial insecurity again.

That choice worked. I built a career. Made money. Forgot I’d ever wanted anything else.

Twenty years later, I’m writing a book. Not because I found more time or discovered hidden discipline.

Because I finally understood that the writer was never gone - just buried under marble that needed removing.

Subscribe here to dive into

The Reinventor’s Mindset

What’s coming

I share what I’m learning as I build The Reinventor’s Mindset™ in public. Not from the summit. From the middle of the climb.

You’ll get:

• The Reinventor’s Mindset™ framework deep-dives

• Early excerpts and previews of the book Bold Water

• Insights from interviews with leaders who’ve transformed from within

• Lessons from INSEAD, from teaching, from getting it wrong

• The honest version - what’s working, what isn’t, what I’m still figuring out

I’m writing mid-journey because that’s when the lessons are freshest. And because I think there’s something more honest about sharing the map while you’re still in the territory.

Follow along on YouTube, Spotify, Apple Podcasts and LinkedIn - search The Reinventor’s Mindset.