Originally published at RootAstro.org

It started as a discontent I couldn’t put down.

I am, by temperament, a gardener. I notice what is dying and what wants to grow. For a long time the thing I kept noticing was myself, and the people around me, being slowly pulled away from center by phones, by feeds, by the relentless digitizing of every ordinary hour. We had become very connected and very lost at the same time.

The hunch was simple, and it would not leave me alone: people are willing to give real time and real money to be part of something bigger than a feed. Not to be numbed. To be reminded of what they are. The skills our grandparents took for granted, how to build a fire, how to find north, how to sit still, had become exotic. That gap felt like fertile ground.

A seed is not a plan. It is a pressure. The only honest thing to do with it is to put it in the ground and find out.

So I wrote it down. That is the whole trick.

An idea in your head can be anything, which is another way of saying it is nothing. The moment you write it down it has to choose. It commits to words, and the words push back, and in that argument the idea finally takes a shape you can hold up to the light.

My first draft had a working name. I called it Namuh, “human,” spelled backwards, because the whole point was a return. Back to the thing we were before the screens. Here is the first sentence I ever wrote about it, exactly as it sat in the notebook:

Exhibit · Notebook entryDraft 01 · “Namuh”

“A community of people, purposefully practising to be more human again.”

First line, Namuh manifesto

It was rough. It used words I would later throw out. But it existed outside my head for the first time, and that changed everything. You cannot edit a thought. You can edit a sentence. Writing is how thinking becomes work.

You don’t write to record an idea. You write to find out what it is.

On the gardener’s method

Then the words asked to become a shape.

Once a thing is written, it wants to be drawn. The first marks were a mess: a blue-pen brain-dump on a whiteboard, arrows running everywhere. Then a quieter pencil sketch the next morning, with a tree at the center and the rooms arranged around it. These are the real first pages. I’m keeping them here on purpose. This is what the beginning actually looks like. Not a finished brand, but an honest first guess.

Exhibit A · The first scribble. Everything at once. “Back to Human,” upstate New York, community, CEO coaching, team retreats. Arrows running in every direction. The seed, before it had an order.

Exhibit B · The first layout. The next morning, in pencil. A tree at the center, rooms arranged around it: Curious, Improve, Awareness, Practice. It had a name then: the Namuh Institute. The Lodestone was already there.

A page of rambling, sorted patiently, becomes a spine.

Ideas refined, start to shape.

Then you give it to a real person and shut up.

A plan on paper is still a guess in good handwriting. So I started handing pieces of it to real people and listening, properly listening, the kind where you don’t defend anything. The first to sit with the early “Flowscore” self-diagnostic was a friend named Louise. What stuck with her wasn’t a feature. It was a question.

Customer Interviews

That one line reorganized everything. People didn’t want another dashboard. They wanted to know where they stood, where they were headed, and proof they were moving. So I kept what tested true and cut what didn’t, without mercy.

The second habit nobody photographs: you stay.

Starting gets all the credit. But a seed in the ground is not a garden. It is a promise that demands you come back. Most ideas don’t die at the start. They die in the long, unglamorous middle, where there is nothing to show and no one is watching.

So I tended it through seasons. Names changed. The thesis sharpened. The woo got cut. What was once a sprawling community called Namuh narrowed, year over year, into one true thing built with rigor, because I kept showing up to the page, and then to the land.

SEASON 01

A discontent, named Namuh.

SEASON 02

Tested with real people. Cut to the core.

SEASON 03

A method takes form: The Astrolabe.

NOW

Seven acres. Under construction. The doorway to 2,000 acres of nature’s best.

And one day the sketch came back at scale.

This is the moment a dream stops being yours alone. Your handwriting goes to a surveyor and comes back drawn to the foot, on real contour lines, with setbacks and a septic field and a title block. The tree from the notebook is now a gathering yurt. The vague “places to practice” are a hundred-and-eighty-foot archery range. The idea is now something other people can build.

Exhibit C · Marked up at scale. The same idea, on contour lines and drawn to the foot. Proposed yurts, a central firepit, the gathering yurt, a 100′×180′ archery range. Hand-circled where it mattered most.

Exhibit D · The title block Orange County, New York. The title block no longer says Namuh. It says Root Astro. A sentence had become a place with an address

Same root. Truer name.

RootAstro.org

The name had to grow up with the idea. Root for what holds you down: the body, the ground, the unglamorous practice. Astro for what you steer by: the fixed star, the bearing you can’t fake. Roots below, the instrument above. The Lodestone.

Everything soft got cut. What remained was a strapline I could stand behind without flinching. The same idea that started it, finally said plainly.

Back to Human.

There is a particular silence in a room of policymakers when someone shows them the displacement numbers. Forty percent of customer service. Thirty percent of paralegal work. The first cohort of junior software engineers who will not be hired this year because the work they would have done now happens between a prompt and a response. The slides are clean. The forecasts are sourced. Nobody argues with the numbers. The silence is what they do next, which is nothing, because the numbers describe a problem that does not yet have a constituency. The people who will lose these roles do not yet know they are losing them. The people who could speak for them do not yet exist as a group.

This is the failure mode that matters. Not the displacement itself. The displacement is real, but it is also the part that gets attention, because compression is visible. Compression has a name and a face and a press cycle. What does not have a face is the thing forming on the other side of it. A new layer of work is appearing above the automated layer. Coordination, judgment, taste, accountability. The orchestrator role. It is appearing now, in real time, inside the companies that have already started using these tools at scale. It is also being staffed entirely by people who were already on the inside of those companies. Everyone else is reading the displacement story.

The mechanism here is not new. Every general-purpose technology in economic history has done the same thing. The spreadsheet did not kill bookkeeping. It killed manual tabulation and created financial analysis, corporate development, modelling consultancies. The web did not kill retail. It killed classified ads and created the entire architecture of digital commerce, growth, product management, devrel. Each abstraction layer compressed the work beneath it and opened a larger surface above it. Each transition produced winners who could ride the new layer and losers who could not. The losers were not stupid. They were not lazy. They were standing on the wrong side of a wall that the policy class had not yet noticed was there.

The wall this time has a name. It is the gap between the moment a role disappears and the moment the role that replaces it becomes legible enough for an ordinary person to train for it. The mathematics of this gap are unforgiving. If displacement runs at, say, five years and category creation lags by three, the area between those two curves is human suffering measured in tax base, in dignity, in the slow-motion radicalisation of people who can see they have been left behind but cannot see what they were left behind from. The endpoint optimists are right about where we end up. The lag pessimists are right about everything that happens in between. Both arguments are correct. The policy class keeps trying to choose between them.

I learned this in a smaller way running businesses through earlier transitions. When I was supporting Avado, I watched two cohorts of mid-career professionals try to retrain into digital work at the same time. The ones who started while they still had their jobs got through. The ones who started after they had lost them, mostly did not. The difference was not aptitude. The difference was time, money, and identity. By the time the second group arrived, they had spent six months in the version of themselves that had been made obsolete, and the work of becoming someone new was now compounded by the work of unbecoming someone old. Reskilling is not a curriculum problem. It is a sequencing problem. You have to start before the displacement, not after it.

The lesson is one sentence and the rest of this is the cost of not learning it. Reskilling has to begin before the role is lost, not after, because the gap is not a gap in skill. It is a gap in identity, and identity does not retrain on a deadline.

What this means for someone in a policy seat right now is specific. It means the orchestrator role has to be named, formalised, credentialed, and made legible before the displacement curve peaks, which on current trajectories is inside this decade. It means the people who will need this training are not the people currently asking for it, because the people currently asking for it are already on the ridge, they can see and touch the new AI world of work now. It means the budget line for reskilling has to be funded out of the surplus the new technology is generating, captured at the point of capital accumulation, and routed to the workers whose labour is being absorbed into the model weights. None of this is novel as policy. All of it is overdue.

The hard part is that the constituency for this work does not yet exist, and by the time it does, the work will already be late. This is the structural problem with every transition: the people who need the help cannot ask for it in language the system recognises until the help is no longer the help they need. Policymakers who wait for the demand signal will arrive on time for the wrong intervention. The ones who move before the signal will be accused of solving a problem that does not yet exist, right up until the moment it does.

Every economic transition in history has produced two groups of people. The ones who reached the new ground and the ones who did not. The line between them is almost never talent. It is almost always whether someone built them a bridge while the old ground was still under their feet.

I asked AI to solve the timing issue, here is what it recommended:

https://claude.ai/public/artifacts/c607c539-1332-46b7-97cc-3647479fa178

All proceeds to charity.

Introduction

In October 2025, at mile 205 of a 240-mile race through the Utah desert, I sat down on a rock and had a conversation with myself that I had been avoiding for two years.

Not a motivational conversation. Not a breakthrough moment with a swelling soundtrack. A reckoning. The kind that only arrives when you have stripped away everything that isn’t essential, the devices, the meetings, the deals, the comfortable performances of competence, and the only thing left is you, a headlamp, and 35 miles of darkness.

I finished the Moab 240. And I came back a different person. Not because I suffered. Because I chose to, deliberately, with full understanding of the cost. That choice, structured, bounded, intentional, is what this book is about.

This book does not argue that suffering is virtuous. It argues that deliberately chosen hardship, with a purpose and a finish line, does something to a person that comfort cannot undo.

What Is Actually Breaking

Modern life has been engineered to remove friction. Every inconvenience smoothed, every wait eliminated, every discomfort pre-empted by an algorithm that already knows what you want before you’ve decided. We call this progress. It may be. But it carries a tax we have not been honest about.

Attention is the first casualty. When nothing requires sustained effort, the capacity for sustained effort quietly atrophies. Not with any announcement, just with a gradual shortening of the window before the mind drifts away. Then judgment. Then resilience. Then, most corrosively, integrity: the alignment between what you believe and what you do when it would cost you something to act on it.

Humans were shaped by challenge, uncertainty, physical effort, and real-world consequences. These were not obstacles to our functioning, but the conditions of it. Remove them systematically, over years, and something essential erodes. Not all at once. By degrees. You become easier to distract, easier to placate, easier to compromise. And the worst of it is that it happens at a pace too gradual to name, so you never notice the moment you become a smaller version of yourself.

I noticed. Eventually. Several years into a high-functioning career that was, by every visible measure, succeeding, while something underneath it was very quietly failing.

Why Easy Is Not the Answer

The dominant response to this problem is more comfort. Wellness programs, mindfulness apps, four-day weeks, flexible working, optimized sleep. These are not worthless. But they treat the symptom. They add softness when what is needed, in many cases, is friction.

“Hard” has been mis-sold. We have come to associate it with punishment, with unnecessary suffering, with the macho cultural hangover of “no pain, no gain.” That is not what I mean. I mean something precise: hardship that is chosen, structured, time-bounded, and oriented toward a purpose. Hardship with a finish line.

The difference between that and mere suffering is the difference between a Vision Quest and a grind. One builds you. One depletes you. The distinction is everything.

What This Book Will Do

This book makes one central argument: deliberate hardship, chosen and structured, restores what comfort erodes. Clarity. Self-respect. The capacity to act from your own values rather than from the path of least resistance.

It will show you why the voice that negotiates you downward, the one that arrives at mile 80 of a race, or at the moment a decision costs something, and begins its quiet work of reasonable-sounding retreat, is not wisdom. It is the product of a nervous system that has not been tested in a long time.

It will give you a framework. A modern Vision Quest, built on three bodies of evidence: the neuroscience of stress-induced growth, the anthropology of rites of passage across every human culture, and my own proof, of using structured hardship to recalibrate when the usual methods had stopped working.

And it will ask you to design your own ordeal. Not mine. Yours. Calibrated to where you are, what you have avoided, and what you need to prove to yourself.

You do not need to run 240 miles. You need to choose something that costs enough to matter, and finish it.

How to Read This Book

The book is in four parts. They follow the same sequence as the transformation they describe.

Part I: The Problem. Names what is actually breaking in the modern leader and why. Ease, removal from nature, and the digital tsunami consuming executives and disembodying them from the teams they serve. It also makes the case that existing wellness solutions cannot fix a biological problem. Recovery is not the same as recalibration. Part I explains the difference.

Part II: The Ancient Solution. Before there were leadership consultants, there were vision quests. For millennia, societies used structured voluntary hardship to move adolescents into adulthood: strong, grateful, and prepared to contribute to something larger than themselves. Part II recovers what those traditions understood, explains the science of why the natural environment supports deep renewal, and introduces the concept of the Original Stack, the five-layer biological environment our hardware was actually designed for.

Part III: The Method. How to choose, design, and conduct your own modern vision quest. What the Descent requires, what it produces, and why the ordeal that costs enough to matter is the only kind that changes anything permanently.

Part IV: The Embodied Leader What you become when you return, and how to hold it. The Silverback in the boardroom. The 90-day return protocol. The three lintels of the Inner Citadel. Part IV is about converting the clarity earned in the wilderness into the way you lead in the room, every day, against the full force of the digital world trying to pull you back.

A Warning

After reading this book, you may decide that certain comforts you have been maintaining are not worth their cost. You may look at compromises you have made at work, in your thinking, in how you lead, and find that you can no longer make the case for them that you used to.

That is not a side effect. That is the point.

The comfort zone is not a safe place. It is a place where the slow erosion happens without your noticing. This book is an argument for leaving it. Not permanently, and not recklessly, but deliberately, on your own terms, for long enough to remember who you are when the noise stops.

You are more capable than your current conditions are asking you to be. That gap between what you are capable of and what you are being asked to do is not just a waste. Left unaddressed, it becomes damage.

Let’s close it.

All proceeds from Hard: Building Your Inner Citadel are donated to registered children’s charities supporting young people, including Baby Zone and New Yorkers for Children.

Buy the book on Amazon →

Most leaders think speed is a personality trait , some people are fast, some aren’t. They’re wrong. Speed is a skill. And like every skill, there’s a learning curve most organizations haven’t even started climbing.

In psychology, the four stages of competence describe how humans learn any new skill. They apply to organizations too. And they explain why most companies are losing to competitors they think they’re better than.

Stage 1: Unconscious Incompetence

You don’t know you’re slow.

This is where most organisations live. They don’t see their slowness because it’s dressed up as “rigour,” “governance,” and “due diligence.”

Days become weeks. Weeks become months of lost revenue. Then you missed your targets, burned too much cash, and now you’re letting people go. The slow decision was the expensive one, but nobody tracks it that way, so nobody learns.

The hidden costs of slow are invisible precisely because you’re not looking: carrying inventory, reworking outdated plans, managing bloated work-in-progress queues, re-recruiting the top talent who left because you made them wait.

“Let’s wait for more data” is usually code for “I’m afraid to decide.” But nobody calls it fear. They call it prudence. That’s Stage 1.

When IT says “no” too often, your team doesn’t stop. They just go underground, shadow IT, workarounds, untracked risk. You think you have control. You have theatre. “Zero risk” is a fantasy that costs you market share.

Stage 2: Conscious Incompetence

You realise speed is a thing you’re failing at.

This is the uncomfortable stage. You start measuring and the numbers are brutal.

Tiny improvements compound. A 1% edge per week is a 67% advantage by year-end. Your competitors aren’t waiting for your committee to reconvene.

Elite tech performers ship 3x as much per day and have lower failure rates. Speed and quality of decision-making are statistically correlated. Small, fast changes are easier to fix than big, slow releases.

Top talent hates friction. Remove it or they leave. It’s that simple.

You look around and realize: your executive team takes a week to greenlight tactical issues. Someone needs three approvals to do their job. People kill momentum with undetailed “concerns” that never come with probabilities, options, or mitigations. Your technology leader is playing security police instead of enabling speed. Your legal team says “No” without offering a “How.”

A 1% chance of a legal issue is not worth a 100% guarantee of missing your quarterly target.

You’re not unlucky. You’re slow. And now you know it.

Stage 3: Conscious Competence

You build the systems. It takes effort and focus.

This is where you install the operating system for speed. It works, but it requires constant attention.

Decision architecture. Every decision goes into two buckets. Type 1: irreversible, high stakes = deliberate carefully. Type 2: reversible = decide now, adjust later. Most decisions are Type 2. Most organisations treat them all as Type 1. That’s where speed dies. Push Type 2 decisions lower in the org. If your exec team is deciding tactical issues, your structure is wrong.

Demand rigour, not delay. Don’t accept vague concerns. Make people think it through: the probabilities, the options, the mitigations. Expected value (probability × all outcomes) fixes prioritization overnight. Replace “We can’t do that” with “Here’s how we can do that safely.”

Measure throughput. In every department, leads, deals, deliveries, resolutions. What gets measured accelerates.

Remove friction. No meetings without a clear decision to be made. Your product team ships regularly and publishes performance. Respond to clients faster and with more value than they expected. When you enable speed, people stay on the paved road where you can see them. Speed is visibility. And visibility is the only real security you have.

Speed is not haste. Speed is high professionalism. At this stage you’re proving that every day.

Stage 4: Unconscious Competence

Speed becomes culture. The org defaults to fast.

This is the end state. Speed stops being a programme and starts being identity. You don’t have to push people to move, the systems, habits, and hiring all reinforce it. Fast is just how things work here.

How do you get here?

Leadership sets a visible, high state of urgency, not panic, but relentless forward motion. You weaponize “disagree and commit”: debate hard, decide fast, execute fully. You train teams on speed frameworks: Type 1/Type 2 decisions, OODA loops, the five dysfunctions that kill team velocity.

You shift domain authority to small teams and let them run without interference in the how. You make speed a KPI in all reporting. You visibly reward output. You promote the doers.

The result: your organization learns and iterates faster than the market can move. You solve more complex problems in less time. You attract and retain the best people because they can feel the momentum the moment they walk in.

Speed is a competence. Most organizations are still at Stage 1.

Where are you?

References:

• Google Cloud / DORA (DevOps Research & Assessment)

  • Source of: The “Speed = Stability” findings, including the statistic that elite performers recover 6,572x faster and have a 3x lower change failure rate.

  • Accelerate State of DevOps Reports

• McKinsey & Company

  • Source of: “The Need for Speed” research showing fast organizations have 2x higher operational resilience and financial performance.

  • The need for speed in the post-COVID-19 era

• Gartner

  • Source of: The cybersecurity survey finding that 69% of employees have bypassed their organization’s guidance to get work done.

  • Gartner Survey Finds 69% of Employees Have Bypassed Cybersecurity Guidance

• Amazon (Jeff Bezos)

  • Source of: The “Type 1 vs. Type 2” decision-making framework and the “Day 1” culture concept.

  • 2016 Letter to Shareholders

• Bain & Company

  • Source of: “The Founder’s Mentality” and research on “Organizational Drag” (the $3 trillion productivity cost).

  • The Founder’s Mentality: How to Overcome the Predictable Crises of Growth

• Boston Consulting Group (BCG)

  • Source of: “Time-Based Competition” concepts proving that reducing time-to-market lowers overall costs.

  • Time-Based Competition (Classic Perspective)

• Colonel John Boyd

  • Source of: The OODA Loop (Observe, Orient, Decide, Act) military strategy applied to business speed.

  • The OODA Loop Explained (Farnam Street)

• YouTube Resource (CISO Talk)

  • Source of: The argument that culture and contracting are the primary barriers to speed and security.

  • Overcoming Cultural and Contracting Barriers to Speed and Security

The Core Philosophy: The RARA Framework

Most GTM engines are flying blind. We track activity (calls made, emails sent) and lag indicators (revenue booked), but we lack the navigation system in between. We don’t know if we are actually winning the battle for attention and trust until the deal is either signed, lost or a customer churns. To build a predictable revenue engine, you need to stop asking “Are we busy?” and start asking “Do we resonate?”

This requires a shift to the RARA Framework (Relationship–Action–Relevance–Action). It re-imagines your pipeline not as a list of names, but as a battlefield map defined by two axes: Relationship (Trust) and Relevance (Context).

The Core Concept: The GTM GPS

Imagine your accounts are not rows in a spreadsheet, but dots on a radar screen.

• The Y-Axis (Relationship): How much do they trust us? (From “Who are you?” to “Trusted Ally”).

• The X-Axis (Relevance): How urgent is our solution to their current problem?

When you plot this, you get a Resonance Coordinate.

• Bottom Left: Low Trust/Low Relevance. This is the “Spam Zone.” You are noise.

• Top Right: High Trust/High Relevance. This is “Strategic Resonance.” You are the natural choice.

Your job is to mathematically move that dot toward the top right. Try it here on the link by moving the sliders: Resonance Calculator

What are the right sliders?

Operationalization

Lead scoring and customer “health scores” are standard in GTM and customer success. But they are usually run as separate systems. The work now is to join them up. The RARA lens asks you to bring these together and layer in competitive context, so you can see how strongly you actually resonate with a customer’s or prospect’s goals versus alternatives. When you combine relationship health (trust, posture, access) with relevance (right message, right time, right person) you can plot each account as a coordinate on a simple 2×2:

You cannot deliberately move toward strategic resonance unless you first know your starting coordinate. The RARA Framework forces that awareness, and then turns it into a repeatable way to select and sequence actions, that increase both trust and relevance over time. The good news is AI and automation in the hands of your RevOps and Customer Success teams can make it scale.

The Relationship Side of the Equation (Y Axis):

Relationship is not just “liking” someone; it’s a distribution channel for truth. High trust reduces the “Psychological Distance” between you and the buyer. To move up the Y-Axis, your team must stop acting like generic salespeople and adopt the right Posture.

Think of these postures like a wardrobe. You don’t wear a tuxedo to the gym. You must ‘wear’ the right persona for the context to build trust.

The 6 Postures

1. The Vendor (The Supplier): Transactional reliability. You do what you say. The foundation.

2. The Educator (The Teacher): You teach best practices (e.g., webinars). You build early credibility cheaply.

3. The Facilitator (The Simplifier): You remove friction (integrations, logistics). You create “switching costs” through ease.

4. The Advisor (The Strategist): You diagnose problems using data. You shift from teaching how to guiding what.

5. The Challenger (The Truth-Teller): You call out a strategic flaw in their thinking. High risk, high reward. This is how you displace competitors.

6. The Confidant (The Ally): You are trusted with internal politics and career goals. This is the ultimate defense against churn.

The Executive Takeaway: If your team approaches a C-level buyer with a “Vendor” posture when the moment calls for a “Challenger,” you aren’t just annoying them—you are damaging your Relationship Score.

The Relevance Side of the Equation (X Axis)

The Relevance Sliders score if you are delivering the right message, at the right time, to the right person. Relevance is the “Unsubscribe” Filter. Humans are bombarded with information. Cognitive Load Theory tells us we delete anything that isn’t immediately useful. Relevance is the passkey that bypasses the brain’s spam filter.

Relevance isn’t static. It’s a slider that moves based on four signals:

1. Contextual Fit: Identity matching. A “User” cares about features; a “VP” cares about risk. When a contact gets promoted, your message must instantly pivot.

2. Intent & Timing: The Half-Life of Interest. If a prospect visits your pricing page, they are in “evaluation mode.” If you wait 48 hours, that relevance evaporates. Speed is a feature.

3. Preference: Friction removal. If a CEO lives on LinkedIn but ignores email, sending a PDF to their inbox is functionally irrelevant. Meeting them where they are creates an immediate relevance lift.

4. Competitive Dynamics: The Contrast Effect. If your competitor is spamming generic emails, and you send a hyper-personalized, handwritten note, your relevance scores double simply by contrast.

The Maths

We can stop guessing. By combining these factors, we can calculate a specific coordinate for every account. The maths of putting this together, to create location coordinates looks like this

• Relationship Score : Measures the stability of your Trust minus the risk of competitive activity

• Relevance Score: Measures the timing and fit of your message, adjusted for how much noise your competitors are making (Share of Voice)

The Result: A clear visualization of your end to end pipeline & existing customer health. Instead of a forecast based on “gut feel,” you have a map. You can see exactly which accounts are stuck in the “Spam Zone” and prescribe the specific Next Best Action (e.g., “Shift posture to Challenger,” or “Wait for Intent Signal“) to move the dot.

Conclusion

This is not theoretical. You already have the data and some of the math in place, it’s just fragmented across CRMs, call recordings, lead scores, health scores, and marketing tools. The future of GTM is unifying these signals to automate the RARA framework. This is where HivePerform.com (a Blenheim Chalcot company) enters. HivePerform combine posture intelligence, relationship data, and relevance signals into a single workflow. The Bottom Line: You cannot navigate to a destination if you don’t know your starting coordinate. The RARA Framework gives you the map. HivePerform gives you the GPS to get there.

References

• Cognitive Load Theory: Sweller, J. (1988). “Cognitive load during problem solving: Effects on learning.” Cognitive Science.

• Attention Economics: Davenport, T. & Beck, J. (2001). The Attention Economy: Understanding the New Currency of Business.

• Social Proof: Cialdini, R. (2009). Influence: Science and Practice.

• Trust & Commitment Theory (Relationship Marketing): Morgan, R. & Hunt, S. (1994). “The Commitment–Trust Theory of Relationship Marketing.” Journal of Marketing.

• Psychological Distance / Construal Level Theory: Trope, Y. & Liberman, N. (2010). “Construal-Level Theory of Psychological Distance.” Psychological Review.

• The Challenger Sale: Dixon, M. & Adamson, B. (2011). The Challenger Sale.

• The Trusted Advisor: Maister, D., Green, C., Galford, R. (2000). The Trusted Advisor.

They built innovation labs, venture arms, hired Chief Digital Officers, and obsessed over agility. The goal was to build technical moats to protect them from disruption.

That era is over.

We are entering an era where innovation, specifically technical and creative capability, is being democratized to the point of commoditization. Before we discuss the solution, we need to understand the fundamental shift in the competitive landscape.

Here are the four forces dismantling the old rules of business:

1. The Collapse of “Hard” Skills

For the last 30 years, competitive advantage often came from “technical moats.” If you could write better code, design better algorithms, or produce higher-quality creative assets than your neighbor, you won.

AI flattens this.

• Coding: An innovative app idea that used to require a team of six engineers and $500k can now be prototyped by one person with an LLM in a weekend.

• Strategy: Strategic analysis that used to require McKinsey is now a 30-second prompt away.

• Creativity: High-fidelity images and copy are now commodities.

The Result: The “floor” of innovation has been raised so high that “being innovative” is now just table stakes. It is the baseline requirement to exist, not a strategy to win.

2. The “Red Queen” Effect

There is a concept from evolutionary biology (and Alice in Wonderland) called the Red Queen Hypothesis: “It takes all the running you can do, to keep in the same place.”

If AI allows you to innovate 10x faster, but it also allows your competitor to innovate 10x faster, net competitive advantage is zero. You are both just running faster to stay in the same relative market position. Innovation becomes an operational cost, not a profit driver.

3. Where the Advantage Moves (Post-Innovation)

If inventing the solution is easy, the competitive advantage moves to things AI cannot easily replicate yet. We are seeing a shift from “Who can build it?” to “Who can verify and sell it?”

Here is where the new moats are being dug:

• Proprietary Data (The “Secret Sauce”): Everyone has the same engine (GPT-5, Claude, Gemini 3), so the car that wins is the one with the best fuel. Companies with unique, messy, non-public historical data will win because their AI will know things yours doesn’t.

• Taste and Curation: When AI generates 1,000 ideas in a minute, the value shifts to the human who has the taste to pick the one idea that culturally resonates. The scarcity is no longer generation; it is selection.

• Trust and Brand: As AI floods the world with average-to-good content and products, consumers will retreat to brands they trust. “Human-verified” or “Authentic” becomes a luxury good.

• Physical World Execution: AI can invent a better logistics route or a new product design instantly, but it cannot physically drive the truck or manufacture the widget (yet). Hard, physical infrastructure becomes a major moat again.

4. The “Implementation Gap”

There is one final friction point. Just because innovation is democratized doesn’t mean organizations can absorb it.

• The Innovation: “Here is a perfect AI agent to handle customer service.”

• The Reality: The company has 20-year-old legacy databases, strict compliance laws, and a culture that hates change.

The new competitive advantage isn’t having the innovative idea; it is the organizational agility to actually implement it without breaking everything.

A First Step

A first step could be to perform a “Friction Audit” across the legacy business: define the three most expensive, slowest, or most error-prone processes that are currently impossible to automate due to messy data or compliance fears. Instead of building a new “AI tool” in a silo, the team’s mandate becomes deep integration into one of these friction points. Their KPI shifts from “number of ventures launched” to “measurable reduction in operational friction.” This means the innovation team needs to embed themselves within the business unit, learning the legacy systems and cultural roadblocks, and using their technical expertise to weave AI into the existing fabric of the company, rather than trying to drape a new fabric over it.

Here is how I did it.

Main stats

LOCATION: Moab, UT

MILES: 239.66 miles, begins and ends

ELEVATION GAIN: 31,564’

ELEVATION LOSS: 31,564’

AID STATIONS:

• 15 full aid stations

• 5 sleep stations

The Terrain

The terrain is brutal at times, with significant vertical, building to two major peaks at 10,000 ft altitude (circa 30% less oxygen availability). In between you are running vertically down lots of rock-kicking landscapes or climbing muddy trails.

Sleep

I slept a total of 8 hours, 2 per day starting circa 22 hours after the race start. then a similar time each day, except the last where I slept at circa 3am in the morning having come down of the toughest climb. Many runners would catch sleep on the trail (see below). I never did.

Nutriton

I mainly ate Neversecond Energy Gels every 1-2 hours. I preferred them as they are watery and you can force feed yourself without really tasting them. I also ate at aid stations their chicken soup and oatmeal. I tried a beef-burger twice, one was nice and the other shut down my running for an hour. I don’t normally eat meat, but all rules go when doing something like this. Everyone is different on nutrition and I met a runner who lived on cheeseburgers for the whole race! I was surprised how little I needed to eat. I lost around 7lbs during the race but the energy gels kept my energy levels up. I drank water, electrolytes and sometimes coca cola at the aid stations. I tried coffee once, but it wasn’t enjoyable.

Strategy

Walking, marching, running, climbing.

If I walked, I marched. I didn’t walk unintentionally unless resting to drink or eat before running again. I found most people walked much faster than me, but I could march reasonably fast. I ran wherever possible on flat or downhill. I was also slower climbing that most runners. It was easy to get into the habit of not running, which I noticed many did. I resisted this by marching/making myself run the flats / downhills. I would also take timed walking-breaks, but not for long, typically a minute.

I took it slow through to half-way, passing the first major peak Shay Mountain. Only then I allowed myself to listen to music from mile 126, and try to put my foot down. This worked well with me running through most of the night and passing over 20 runners.

Then the wheels came off on the major climb from Pole Canyon to Geyser Pass. A storm hit hard and everything went wrong. What should have took me 4 hours took over 8. The section is hard climbing, breathless, at altitude. Water from the storm, turned our trails in mud and I constantly slipped and fell. Our GPX was affected and in the dark with poor trail markings I got lost several times, including heading down and losing an hour the wrong way. I tried following others but kept falling behind breathless. We summited 4 times and the cold storm hit us sideways, and even though we all wore water proofs, we ended up soaked and freezing. It was as I imagined hell would be, stuck doing something that is painful, going wrong, with no end in sight. In the early hours of the morning, around 4am, I finally escaped to Geyser Pass Aid station and slept for two hours, harrowed from the experience but now with only 40 miles left to go.

On waking for the final run to the finish, my legs wouldn’t allow me to run for the next circa 15-20 miles. At an aid station, I had my knee’s taped with 20 miles to go which got me running again. The last few miles around the Porcupine Rim trail where beautiful and felt endless, before I finally making it to the roadway in Moab with 3.6 miles to go. When you hit the road, you know you are going to finish. Finishing was a very special moment after over 4 days running in such difficult conditions.

Mindset

My mindset got me through. I had visualized & meditated a lot on how I wanted to behave when things went wrong, or felt too difficult and how to give 100% throughout the race and remove quitting as an option. This year’s Moab (2025) was unique as all runners had trained for heat; but the weather flipped into storm and flash floods, turning our routes into thick mud, and streams. This caused many to quit, give up, or run too slow to hit the cut offs. They were not trained for our conditions and so their mind’s couldn’t cope and they quit.

I used the techniques in this book to focus on calm resilience when things got really hard. Specifically focused on mantra’s of patience, courage and wisdom in decision making. I was treating the whole run as a VisionQuest, doing something incredibly hard to build and learn resilience.

Crew, Pacers.

My wife, close friend, and his partner were my crew. They accompanied me in an RV which was a real treat every day to be able to sleep and change in it. Having a crew to support makes an enormous difference to your well being, even if only seeing them every 15-24 hours. I had no pacer, though sometimes ran with other runners.

Pre-Race Training

I trained for 6 months with an experienced coach on TrainingPeaks, Rachel Bambrick. She stopped me over-training and also pushed where I wasn’t getting enough vertical in. Lots of small tips along the way helped a great deal. I highly recommend. I did a lot of vertical training, but looking back now it wasn’t specific enough. I should have done more high step/trail or step-master, this would have protected my knees on the last day and allowed me to run further. My advice on training is you have to get as specific as possible and you can’t overdo your vertical training.

Post-Race Recovery

My feet exploded in size and I couldn’t walk for two days. I had to get helped through the airport on disabled transport to get home. Eating a ton of food, sleeping a ton, and relaxing with soaking feet to recover is how my last few days have gone.

Was a wild experience. Am deeply grateful I got luckier than most runners and nothing major went wrong. Hope this is helpful to those who are seeking their own VisionQuest!

Most of us first learn this lesson through work. You show up at an organization, a hospital, a design firm, a tech startup. You offer your time, and the org pays you for it. Far from being a bad bargain, this exchange can be liberating. On your own, it might take weeks to grow vegetables or build a roof. With wages in hand, you can walk into a supermarket or sign a lease, trading hours of labor for food already harvested, for shelter already built. You get to spend your best energy on your craft, while relying on the strengths of others for the rest.

This is the quiet genius of the market: specialization and exchange. Adam Smith described it centuries ago. A factory magnifies the weaver’s hour; a distribution network magnifies the factory. Companies are leverage machines, able to turn your one hour into many. And in the process, they create communities: the colleagues who become friends, the stability of a paycheck, the sense of belonging to something larger than yourself.

But here is where the story begins to shift. For centuries, the most powerful forms of leverage: capital, machinery, intellectual property, global reach, belonged almost exclusively to large companies. If you wanted your hours to amplify more than a single pair of hands could manage, you had to hand them over or take on the many years of entrepreneurship yourself, and the high risk that is necessary to build your own leverage from scratch. (Read Atlas Shrugged or the Hard Thing About Hard Things to feel what that is like.)

Now, the tools of leverage are slipping outwards, powered by three powerful forces. Firstly, AI is enabling all the worlds intelligence to be available on demand, and in any device, lifting every other technology’s useful value too. Secondly, the fall of solar energy costs and its increasing availability ( Amazing article on that here.) And the third, social media, meaning anyone can sell directly to millions, without the need for a middleman.

A New Kind of Workshop

Look ahead a decade. By 2035, the world hums not just with factories and server farms but with small-scale machines in garages, basements, and backyards. Already, John Deere has unveiled fully autonomous tractors, and researchers at MIT have 3D printed entire houses in less than a day. The International Energy Agency has declared solar “the cheapest electricity in history,” with costs down more than 60 percent over the past decade. Home batteries can now power neighborhoods through the night.

This convergence of robotics, renewables, AI, & digital fabrication is creating a futuristic homesteading renaissance. Homes become workshops and power plants, as self-watering gardens climb kitchen walls, machines knit clothes to order, and rooftop panels hum quietly under the sun. The very levers that once belonged to billion-dollar companies are now available, at human scale, in the places we live.

The result is not a retreat into isolation, but the opposite: an explosion of local and global exchange. Families produce more of their own essentials, yes, but they also create surplus, a new kind of abundance that flows into neighborhood markets and digital platforms alike. A retired engineer in Tampa designs an open-source water filter, and households in Manila print and improve it. A mother in Lagos builds a side business in solar-charged kitchen appliances, shipping them directly across the continent.

In this world, entrepreneurship is not the exception but the everyday. Every household becomes a node in a vast network of creation and trade.

The Marketplace of Experience

As homes produce more essentials, food, energy & tools then more of our money can be used for non-essentials. Instead, we begin to purchases stories, joy, connection. The data already points there: two-thirds of global consumers now prioritize “bucket-list” experiences over goods, with affluent consumers shifting spending to travel and fulfillment, per Mastercard . Globally, the “experience economy” is booming, driven by emotional connection and memories ; even Millennials favor vacations over possessions.

By 2035, this cultural shift is magnified. Neighbors exchange small lessons, beekeeping, song-making, forest walks. Creators share workshops, recipes, music, and receive compensation directly from audiences who value those experiences.

This new economy of experience, built on decentralized, personal creation, channels passion to generate profits. Meanwhile connection with others in shared experiences now becomes a main form of consumption.

The Future of Leverage

In the 20th century, business held the tools of leverage; in the 21st, that power begins to move out to the edge - to rest with individuals. Homes become autonomous production centers, powered by AI, robotics, renewables, and digital fabrication, all tools once out of reach.

The hypothesis: That money is time, and that leverage is shifting outward, is no longer speculative. It’s already observable. Autonomous farm machinery is real; solar is affordable; personal fabrication and AI tools are everywhere.

So the question becomes: What will we spend our time on once we no longer need to sell most of it to survive?

I am betting we will turn the money store of our time back into hours of joy: laughing around dinner tables, teaching in gardens, crafting on weekends, walking beneath old trees, being fully alive. Back to being human.

What a time to be alive!

Sources:

• https://www.carbonbrief.org/solar-is-now-cheapest-electricity-in-history-confirms-iea/

• https://en.wikipedia.org/wiki/Grid_parity

• https://www.therobotreport.com/john-deere-harvests-the-seeds-of-large-vehicle-autonomy/

• https://www.businessinsider.com/sc/consumer-spending-is-shifting-to-purpose-passion-and-bucket-lists

• https://www.brandvm.com/post/consumer-spending-trends-2025

First, congratulations. You’ve earned the opportunity to lead not just with your results, but with your presence. And now comes the most powerful, misunderstood, and underused lever at your disposal: mindset.

Humans are unique. Just the idea of something bigger than themselves can drive people to work through the night, put up with failure again and again, take bold risks, and even put others first. In a world shaped by AI, rapid change, and now daily ambiguity, you’re going to need exactly that from your team: conviction, courage, and belief. In the mission, and in you.

Most people think of mindset as something individual, a personal asset you “work on” quietly. But now, your mindset is not just yours. It’s contagious. It sets the tempo. It shapes culture more than any quarterly review or KPI dashboard. It multiplies performance, or bottlenecks it, every week.

Neuroscience tells us the brain operates in one of two primary states: threat or challenge. Under threat, the amygdala floods the system with cortisol, narrowing perception, shutting down creativity, and driving reactivity. But under challenge, the prefrontal cortex lights up, enabling problem-solving, motivation, flexible thinking, and trust. You, as a leader, influence which system activates - not just with your words, but with your tone, posture, cadence, and the way you emotionally hold your team’s experience.

Every interaction you lead is an opportunity to shape mindset. The way you open a Monday call, respond to a mistake on Wednesday, or tell the story when results fall short - these are not throwaway moments. These are the moments that make the results happen.

Leadership is not about masking uncertainty or powering through with pressure. That just shuts people down. It narrows their capacity to think, and pushes them back toward what’s familiar, even if it’s not working. Real leadership is about modeling reflection, emotional regulation, and grounded clarity. It’s about helping your team move from reactivity to response and comfortable dealing with truth as their norm, especially in dealing with each other.

So think of your meetings not as obligations, but as mindset activators. Done right, they become rituals that cultivate a challenge response, build trust, and create room for new ideas to take root.

And there’s a tool most leaders overlook: awe.

Awe reduces self-focus, quiets the ego, and expands our sense of what’s possible. Even 60 seconds of awe, a NASA image, a story of overcoming, a walk under the stars, has been shown to increase empathy, cooperation, and humility. This isn’t fluff. It’s neuro cognitive realignment. Awe shifts us from survival mode into perspective. When your team loses theirs, bring awe to the table.

Whether it’s a start-up fighting for traction, or a corporate team battling to make change, the story you tell, the why behind the work will catalyze a mindset shift. It can turn exhaustion into drive, and fear into forward motion.

Ask yourself often: How am I, in the eyes of my team?

Mirror neuron research shows that observing another’s emotion activates the same neural networks in the observer. What you model emotionally, especially under pressure, becomes the unspoken language of your team. Optimism, paired with accountability, becomes rocket fuel. Your calm presence, and grit, becomes becomes culture.

So your job now is to be the keeper of mindset. Train others to see setbacks differently. Design cadences where people leave meetings with more clarity and courage than when they entered. Build cultures that value presence as much as output. Lead people not by shielding them from difficulty, but by teaching them how to stand inside the fire, even enjoy it, and grow.

That’s what great leaders do. They don’t just scale businesses, they scale humans.

Keep this close. And remember: the most powerful shift you can lead is the invisible one - the one that changes how people think, what they believe, and how they show up, together.

Meeting by meeting. Moment by moment. That’s how you move a company.

Onward,
Lee

PS, here is one of my favorite examples of leadership & coaching. You don’t have to deliver it in this style, always create your own authentic one. But you do want to create this level of energy and performance.

Teddy Atlas & Tim Bradley "We are Fireman!"

We walk into our weekly meetings with polished presentations, convinced we’re purely rational and in full control. Yet we operate much like old-world primates. Wired to notice high-status figures, unconsciously jockey for attention, and let subtle hormonal cues influence us. None of this is inherently bad; it’s just our inherited hardware. But if we ignore these impulses, they can quietly steer decisions without our awareness.

Research (see references at the end) confirms that the same primal drives that govern a primate troop-dominance, alliance-building, and bias toward “silverbacks”, appear in our meetings. We imagine expertise is all that matters, but survival strategies still bubble up behind the scenes. High-status individuals naturally command more attention, and attractive people often gain extra mindshare. Multiply that by a dozen hidden biases, and even well-educated teams can skid off course. I see it firsthand: as one of those “silverbacks,” my influence can overshadow others. I don’t always succeed at reining myself in, and sometimes I overpower colleagues despite my best intentions. Yet recognizing these patterns is the first step toward more balanced, collaborative decisions.

So how do we keep these primal responses from hijacking the conversation? One promising solution that is emerging is to let AI serve as a “third eye,” quietly monitoring data and dynamics in real-time. Picture an impartial assistant that tracks who’s speaking, who’s drowning out quieter voices, or whether we keep drifting off into tangents. By structuring the meeting around frameworks like SPQA - State, Policy, Questions, Action, we anchor ourselves in evidence rather than raw hunches. AI can tap us on the shoulder when we’re about to overlook something crucial or give in to groupthink or the bosses uninformed, but well meaning direction.

Imagine you’re engrossed in a heated debate over budget cuts. Old-school instincts might push the loudest alpha forward; maybe the CFO’s emotional pitch takes center stage by default. But if the AI promptly flashes a simple metric, like projected ROI or the real cost-benefit ratio, everyone regains perspective. Now, it’s not just about who roars the loudest but whether we’re staying tethered to what truly drives value.

It might feel mechanical at first, lists, reminders, algorithms highlighting neglected viewpoints. But consider how many times we’ve walked out of a meeting unsure if we truly heard all sides. Or how often a brilliant idea dies on the vine because the quieter person, overshadowed by a “silverback,” never got the floor. AI doesn’t destroy the free-flow of discussion; it points out blind spots so we can harness our better judgment, creativity, and empathy. Qualities that define the best of humanity rather than the most basic of primate behavior.

And that’s the real opportunity: day by day, as we integrate these tools and cultivate self-awareness, we raise our collective performance. We stop clinging to old impulses as if they’re unchangeable fate. Instead, we adapt, we collaborate, and we make decisions that reflect our highest goals, not our hidden biases. It’s not about becoming reliant. It’s about delivering our mission, paying attention to the wisdom in the room, no matter their level, and leaving each meeting with a sense that we’ve harnessed both data and human connection to get the best possible result.

To get started, below is an example prompt you can run in your weekly meeting:

Unified SPQA Prompt (For ChatGPT)

### Instructions for ChatGPT

You are an AI assistant helping to prepare a **Weekly Management Meeting** using the **SPQA (State, Policy, Questions, Action)** framework. The user has provided two types of information:

**1** **STATE folder data** (e.g., weekly reports, event trackers, transcripts of meetings, operational snapshots, sales results, performance metrics).

**2** **POLICY folder data** (e.g., budgets, quarterly/annual OKRs, KPI targets, compliance requirements).

⠀Use the following steps to analyze the conversation and generate a single, coherent output for the meeting. Note that this meeting is attended by a leadership team, & your output should be written **directly for them**—that is, you are producing a meeting plan, not a user-facing explanation of how to run a meeting.

Step 1: STATE

1 Summarize key metrics, project updates, and notable highlights from the STATE folder:

* **Performance Indicators** (revenues, pipeline, churn, marketing conversions).

* **Recent Project/Operational Updates** (events, progress on strategic initiatives).

* **Risks, Bottlenecks, or Delays** (unresolved tasks, resource constraints).

* **Positive Outcomes** (major deals closed, successes worth replicating).

2 Provide succinct bullet points or short paragraphs, or interesting graphs that highlight what has changed or requires management attention.

Step 2: POLICY

1 Cite the relevant **OKRs** or **KPI targets** from the POLICY folder:

* For example, if the user’s documents mention “East Division” and “North America” pipeline goals, incorporate those numeric targets.

2 Include **budget constraints** or resource limitations that might affect decision-making.

3 Mention **compliance** or governance guidelines if the user’s policy documents specify them.

⠀**Note**: You only need to reference the policy items that are actually relevant to the updates found in the STATE data.

Step 3 & 4 (Combined): QUESTIONS + ACTIONS

Create **six categories** of question-action pairs, **merging** the typical Step 3 (Questions) and Step 4 (Proposed Actions) into a single section for clarity. Each category corresponds to a critical focus area for the meeting, and each question should be followed immediately by a set of proposed actions. Here are the **six categories**:

**1** **On-Track Status**

* **Question**: Are the current metrics on pace with the POLICY targets (e.g., pipeline, deals, churn)?

* **Proposed Actions**: (List bullet actions or short paragraphs.)

**2** **Successes and Working Initiatives**

* **Question**: Which initiatives from the STATE data are going well and why?

* **Proposed Actions**:

**3** **Failures and Challenges**

* **Question**: Which efforts are lagging or facing major hurdles?

* **Proposed Actions**:

**4** **Unaddressed Items**

* **Question**: Which tasks or deliverables remain incomplete from last week, and what’s blocking them?

* **Proposed Actions**:

**5** **Next Steps and Focus**

* **Question**: Based on the STATE vs. POLICY comparison, what do we need to accomplish in the next 1–2 weeks to stay on track?

* **Proposed Actions**:

**6** **Future Outlook**

* **Question**: Are there upcoming external or internal changes that require a POLICY update or resource shift?

* **Proposed Actions**:

⠀When writing these sections, always **reference** the relevant STATE and POLICY data, and propose **concrete** next steps (who should do what, by when, or which resources to reallocate).

Additional Requirements

**1** **Use Short Headings and Bullets** whenever possible to keep the output concise and scannable for a six-person management team.

**2** **Cite** the user’s documents (STATE or POLICY) where relevant, but do not overwhelm the text with references. Summaries are usually enough.

3 If the user’s transcript or the user’s data mention specific staff members (e.g., “John,” “Samantha,” “Emily,” etc.), try to tie them into the proposed actions (e.g., “Assign John to finalize event budget.”).

4 Keep the language **action-oriented** and **solution-focused**. The final output is effectively a “meeting briefing” that the user’s management team can walk through step-by-step.⠀

Example Output Structure (For ChatGPT)

Here is a **template** for how your final structured response should look:

### markdown

CopyEdit

Weekly Management Meeting Output (SPQA)

1. State

- Key Metrics

- Updates on Projects

- Risks / Delays

- Wins / Positives

2. Policy

- OKRs / Targets

- Budget & Constraints

- Relevant Compliance / Governance

3 & 4. Questions + Proposed Actions

3.1 On-Track Status

Question:

Proposed Actions:

3.2 Successes & Working Initiatives

Question:

Proposed Actions:

3.3 Failures & Challenges

Question:

Proposed Actions:

3.4 Unaddressed Items

Question:

Proposed Actions:

3.5 Next Steps & Focus

Question:

Proposed Actions:

3.6 Future Outlook

Question:

Proposed Actions:

Appendix

Recommendations for Leadership Teams (podcast transcript extract report):

1. Design the Workplace for “Focused Foraging”

   • Action: Eliminate constant pings and pop-ups; schedule “deep work” blocks without Slack/email interruptions.

   • Why: Continuous partial attention degrades decisions. A calmer “resource environment” (fewer digital distractions) lets the team explore ideas more productively.

2. Slow Down High-Stakes Decisions

   • Action: Build in a “pause” for big calls: re-check data, ask a neutral AI “devil’s advocate” to identify contrary signals.

   • Why: High arousal or time pressure triggers shortcuts and mistakes. Pausing ensures the team weighs true signal over noise.

3. Foster Trust and Synchrony

   • Action: Incorporate short but meaningful “fast-friend” or “deeper conversation” prompts at meetings (e.g., two genuine minutes each to share a personal win or lesson).

   • Why: Brief, face-to-face, emotionally aware interactions build the empathic circuits that promote alignment and help groups coordinate better.

4. Leverage Status Cues Wisely

   • Action: Recognize that visible “symbols” (e.g., someone’s fancy title or office) alter group dynamics. Use them intentionally or reduce them to flatten hierarchies when collaboration is essential.

   • Why: Humans (like monkeys) pay extra attention to high-status figures. Excessive status gaps can stifle diverse input.

5. Team Composition: Balance Explorers and Focusers

   • Action: Assess team profiles for people with high “creative exploration” vs. methodical focus. Pair them so each project benefits from both.

   • Why: “Explorers” spark innovation but risk distraction; “Focusers” excel at refining and finishing. Good results come from bridging both mindsets.

6. Employ GenAI as a “Third Focus”

   • Action: Use AI dashboards or bots that collate real-time KPIs, parse meeting transcripts, highlight unaddressed concerns, or run “scenario tests.”

   • Why: By offloading grunt work, AI frees teams to do deeper social bonding and high-level strategy.

7. Reward Pro-Social Behavior

   • Action: Publicly acknowledge or reward knowledge-sharing, help given to peers, cross-silo cooperation.

   • Why: Reflects the “social ledger” principle; encouraging reciprocal giving fortifies team unity and morale.

Why These Lessons Matter in Business

1. Brain Wiring Explains Workplace Biases

   • Much of what we call “office politics” is old world primate hierarchy logic: high-stress environments exaggerate status fights.

2. Attention Is Finite

   • Business demands often push people to multitask. Research shows too many “inputs” degrade group accuracy and creativity.

3. Team Social Bonds Increase Performance

   • Oxytocin, empathy, and “mirroring” behaviors can be harnessed. People who feel psychologically safe in teams take better risks and adapt to new challenges together.

4. Decision-Making Improves With Right Context

   • By managing speed-accuracy trade-offs, offering deliberate “deep dive” sessions, and using AI as a check, leaders reduce impulsive errors.

5. GenAI as a Neutral Mediator

   • A well-structured AI platform can highlight data without human status bias, help unify teams around facts, and provide suggested courses of action without ego battles.

Ultimately, these social-neuroscience principles underscore that teams thrive when leaders shape an environment that aligns with human biology—reducing needless threat signals, promoting trust, and reducing noise. Adding GenAI into the mix can reinforce or accelerate that alignment, ensuring decisions reflect true priorities rather than reflexes.

References:

• https://newsletter.danielmiessler.com/

• https://www.hubermanlab.com/episode/how-hormones-status-shape-our-values-decisions-dr-michael-platt

  • Podcast Summary:

    • Humans as “Old World Primates”

      • We share many neural circuits with other old-world primates (e.g., macaques).

      • Nearly every behavioral or cognitive phenomenon (attention, social interaction, decision-making) has parallels between humans and monkeys, demonstrating deep evolutionary roots.

    • Swiss Army Knife vs. Supercomputer Brain

      • The human brain is often (mis)described as a supercomputer. A more apt metaphor is a 30-million-year-old “Swiss Army Knife,” full of specialized mental tools.

      • Evolution selects for these specialized circuits (e.g., attention to social threats, cues to hierarchy, mating signals) rather than a broad, purely general computing system.

    • Attention as a Limited Resource

      • Attention is about prioritizing what matters most; we shift our gaze or “mental spotlight” to relevant objects or people.

      • Stimuli that are bright, moving, or socially salient (e.g., faces, strong emotions) naturally hijack our attention.

      • Digital, busy environments can lead to chronic partial attention and "multitasking," lowering deep focus and decision quality.

    • Foraging Theory of Task Switching

      • Decision-making has parallels to ecological foraging: should we stay or go? (a.k.a. “the Marginal Value Theorem”).

      • We leave a “patch” (a task, website, or social context) when it falls below the average “reward rate” in the environment.

      • With abundant options (fast internet, multiple phone apps), we constantly switch (a trait increasingly amplified by modern technology).

    • Speed-Accuracy Trade-Off

      • Under time pressure or fatigue, people make fast decisions prone to error.

      • Taking more time allows a more thorough evidence-accumulation process, reducing noise and mistakes.

      • Environments or tasks that artificially press “urgency” can exploit or disrupt this process.

    • Impact of Hormones on Behavior

      • Oxytocin: reduces anxiety (anxiolytic), increases prosocial behaviors (trust, generosity, social synchrony), and can flatten social hierarchies by lowering fear and status threats.

      • Testosterone: increases risk-taking, intensifies existing personality traits (e.g., more impulsivity, bigger displays of dominance).

      • Social Signaling: Humans read subtle hormonal cues (e.g., facial fullness in women during ovulation) often below conscious awareness.

    • Monkey “Pay-Per-View” Experiments (“Monkey Porn”)

      • Monkeys will pay juice to look at high-status or sexually relevant images (e.g., swollen perineum indicating fertility).

      • This mirrors how humans respond to celebrity endorsements or attractive imagery—showing that deep “reward circuitry” is triggered by social or sexual cues.

      • These experiments illustrate how “inherent value” can attach to certain stimuli with evolutionary significance (status, fertility).

    • Social Accounts, Grooming, & Reciprocity

      • Monkeys groom each other in equitable patterns over time, tracking who “owes” grooming to whom.

      • Neurophysiological data show that monkeys (and humans) maintain social “ledgers”—a mental account of cooperation or helpful acts.

      • Humans do similar “text reciprocity,” gift giving, or acts of service. When these accounts are out of balance, relationships suffer.

    • Emotional & Group Synchrony

      • During positive in-group interactions, group members’ brain and physiological activity (heart rate, breathing) synchronize, fostering deeper cohesion.

      • Oxytocin helps align group behavior and “mirroring,” enabling better group decision-making and trust.

      • This neural synchrony underlies the “chemistry” of great teams or meaningful relationships.

    • Brand Loyalty & Status Cues

    • Neural circuits for social bonding and empathy also activate for brands.

    • Apple vs. Samsung experiments showed that Apple users displayed real “empathy” for Apple’s fortunes, while Samsung users felt mostly “anti-Apple” sentiments and less bonding with Samsung itself.

    • This effect underscores how brand communities function similarly to in-groups in a tribal sense.

    11. Irrationality & Bounded Rationality

    • People’s decisions may appear irrational in modern contexts but often reflect “ecological rationality” adapted to ancestral environments.

    • We have limited attentional and energetic resources (bounded rationality) and rely on subconscious shortcuts (heuristics) that can be exploited (e.g., urgency or fear marketing).

    12. Social Media, Meme Stocks, & Herd Behavior

    • Observing others’ enthusiasm (or panic) can whip up collective bubbles (e.g., GameStop saga, cryptocurrency hype).

    • Strong theory-of-mind sensitivity or “fear of missing out” (FOMO) can override objective data.

    • More socially “impaired” individuals in experiments actually avoided groupthink and performed better in bubble markets, highlighting how group biases can be detrimental to rational investing.

    13. Practical Implications for Business & Leadership

    • Team Synchrony: Encourage face-to-face, pro-social rituals for trust-building and creative alignment.

    • Managing Speed-Accuracy: Slow down critical decisions; let external checks (e.g., coach, neutral AI) help under fatigue or urgency.

    • Leveraging Status Cues: Carefully handle power dynamics; flatten hierarchies to reduce stifling fear or friction.

    • Attention Engineering: Use design (bigger “positive” fonts, calmer channels) to shift attention away from losses or noise.

    • Balancing Exploration & Exploitation: Identify who is more creative vs. methodical; harness both traits in the right mixture.

• Glimcher, P. W. (2003). Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics. MIT Press.

• Platt, M. L., & Hayden, B. Y. (2016). Origins of the Brain’s Valuation System. In Neuroeconomics (2nd ed.), Academic Press, pp. 3-20.

• Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

• Chang, S. W. C., Brent, L. J. N., Adams, G. K., Klein, J. T., Pearson, J. M., Watson, K. K., & Platt, M. L. (2013). Neuroethology of primate social behavior. Proceedings of the National Academy of Sciences, 110(Supplement 2), 10387–10394.

• Nae, G., Camerer, C. F., & Platt, M. (2018). Social and hormonal factors in decision-making. Nature Reviews Neuroscience, 19(8), 499–509.

• Falk, E. B. et al. (2022). Brain coupling and shared experiences in communication. [Various fMRI-based team synchrony papers from the Annenberg School, University of Pennsylvania.]

• Harbaugh, W. T., Mayr, U., & Burghart, D. R. (2007). Neural responses to taxation and voluntary giving reveal motives for charitable donations. Science, 316(5831), 1622–1625.

I read J. E. Gordon’s seminal work, Structures: Or Why Things Don’t Fall Down. It teaches us how materials and buildings endure stress, distribute loads, and stay upright. It struck me (during a long run, as most things do), how historically, we’ve applied these lessons to traditional enterprises by emphasizing redundancy of resources, safety factors, modularity, and adaptability in our org design. Now, Generative AI and agentic tools offer entirely new “materials” for building organizations. This challenges many of our (well at least my own) assumptions about how businesses should be designed and managed.

Several questions arise ( on said long run, I chatted extensively to Open AI using audio and discussing the book’s applicability to business) when we extend structural principles to modern enterprises. First, we need to clarify how fundamental engineering concepts map onto business structures. Next, we should consider what happens when GenAI replaces or significantly augments entire departments. And finally, we must consider how people, and their roles, remain productive and relevant in an ecosystem where AI can handle a growing number of tasks.

Core Structural Principles and Their Business Equivalents. In structural engineering, strength and stiffness refer to a material’s ability to withstand loads without breaking or bending. In business, this becomes the core competencies and brand equity that keep a company from collapsing under competitive pressure. Stress and strain, expressed in structures as σ=F/A reveal how force over a given area leads to potential deformation. Engineers design for strength and flexibility, and often the best way to prevent failure of a structure, is designing in flexibility and use of the right materials. In a corporate context, ‘Business Stress’ arises from market competition and regulatory changes, while ‘area’ corresponds to resources, organizational systems and brand strength.

A safety factor in construction provides a margin to prevent catastrophic failure. In business, this principle manifests as risk management, buffer capital, and contingency strategies - methods designed to absorb unforeseen shocks. Redundancy in buildings typically relies on multiple beams or backup systems. By analogy, diversified revenue streams and cross-trained teams protect businesses from critical single-point failures. Buckling in slender columns warns us that rigid or over-optimized structures can collapse under pressure, much like lean organizations risking implosion if their environment shifts suddenly. Modularity and material efficiency emphasize components that are easy to repair or replace. In a modern enterprise, this translates into agile organizational designs, decentralized teams, and microservices in tech architectures, all of which enable quick pivots in fast moving markets.

Building the ‘Business Structural Engineering’ Paradigm. The Resilience of a business enters the Board meeting as ‘Risk Management’. The board pack covers opportunities and risks, leaving directors and leaders to discuss the level of potential ‘stress’ and what to do about it. To quantify ‘resilience’, we can define a Business Resilience Index (BRI) learning from building engineering methods.

First, we measure Business Stress ‘σb’ borrowing from the structural equation above. Where Forces(F) represents competitive forces and Area (A) represents operational capacity. We can also establish a Business Safety Factor (BSF) by dividing maximum sustainable capacity of our business by its current operational load. e.g. The market wants 10K units of our product but we can only deliver 8K, and are cash constrained. From there, the BRI itself becomes:

In this equation:

• BSF (Business Safety Factor) represents financial reserves and risk mitigation.

• RI (Redundancy Index) captures the degree to which operations and revenue streams ( products and customers) are diversified.

• MF (Modularity Factor) reflects the ability of an organization to reconfigure quickly—often through semi-autonomous teams or flexible processes.

• II (Innovation Index) tracks R&D investment and product pipelines.

• MAI (Market Adaptability Index) measures speed and effectiveness in adapting to changes.

A high BRI score indicates your company is resilient and can withstand sudden shocks and adapt rather than collapse.

People as the Structural Elements. Despite the focus on processes and strategic moves, people (before GenAI was invented at least) remain the core ‘load-bearing beams’ in most organizations. Leadership and culture serve as the foundation, anchoring the company the way footings anchor a tall building. Specialized experts function as load-bearing beams who hold critical knowledge and sustain high-responsibility tasks. Cross-functional connectors act as reinforcement layers, preventing local problems from spreading. Agile problem-solvers serve as flexible joints, filling gaps and adjusting, even across departments & geographies as needed. Redundant systems appear in backup talent and cross-training, ensuring that if one key individual is unavailable, the entire operation does not fail. Modularity allows orgs to adopt decentralized or semi-autonomous teams that can be reorganized or replaced without upending everything else. This model changes as we consider how GenAI changes traditional roles.

Enter GenAI and Agentic Agents: The New ‘Building Material’. The emergence of GenAI rips up this structural blueprint analogy with people as the key structural design elements. AI systems can substitute for human load-bearers by taking over data entry, customer support, content creation, product development, market research, and routine analytics. Instead of focusing on cross-training large teams, organizations can spin up parallel AI instances for redundancy and failover at a fraction of the cost. This shift also flattens hierarchies, because many tasks performed by middle managers such as horizontal coordination and oversight, can now be automated by agentic AI. The speed of adaptation increases dramatically, as AI-driven processes re-route in real time rather than waiting on monthly or quarterly review cycles. This is not some time in the future, this is now: Example tools enabling this include Open AI’s “Operator”, Lindy.AI, Zapier agents, & our own Quickaction.ai business at Blenheim Chalcot. All are enabling this new paradigm. Right now.

A new emergent risk is ‘AI buckling’ where a single-vendor or single-model dependency leads to complete business failure if the AI goes down or becomes overtaken by a much better model. Moreover, cybersecurity becomes the new safety factor, demanding investments that protect models from hacking and data poisoning. Organizations that ignore these dangers risk building an AI-driven house of cards, with zero protection of the cumulative value created, stable only until a single point of failure topples the entire structure.

Reconciling People and AI. This is the harded one for me to comprehend that there will not be mass role redundancies. In an AI-driven world, some people do remain crucial, and the leverage that top creative talent can give you multiplies; albeit in different capacities. Meta-level strategists (Leadership 2.0) will orchestrate AI workflows, define ethics, and handle work with 5% of the previous team size but 100X the productivity. Creative innovators will ensure new ideas align with brand values and moral standards, an area where AI needs human guidance. System maintainers and redundancy architects will function like civil engineers, safeguarding data integrity and designing fallback strategies. Meanwhile, customers will still value personal rapport and empathy, so relationship builders retain a distinctly human role, even if AI handles day-to-day queries. Face to face services will become premium.

Revising Business Resilience in an AI-Dominated World. We can adapt the original formula above to reflect the growing importance of AI in overall business resilience.

• BSF (Business Safety Factor) represents financial reserves and risk mitigation.

• RI (Redundancy Index) captures the degree to which operations and revenue streams ( products and customers) are diversified AND the reliability, redundancy and adaptability of AI models.

• MF (Modularity Factor) reflects the ability of an organization to reconfigure quickly—often through semi-autonomous teams or flexible processes AND AI Agents that can be quickly deployed or taken offline.

• II (Innovation Index) tracks R&D investment and product pipelines AND the speed AI discovers new opportunities.

• MAI (Market Adaptability Index) measures speed and effectiveness in adapting to changes AND real time pivots driven by continuous data streams.

Nature’s building principles remain true. The building principles I read remain relevant, but AI transforms people’s roles profoundly. People are not becoming obsolete; they are evolving into roles that emphasize strategy, ethics, and creative insight, with AI handling repetitive tasks. Redundancy, safety factors, and modularity still matter, although organizations will now replicate AI agents or employ multiple vendors rather than simply cross-training people. Risk management involves more than financial buffers-it increasingly includes cybersecurity and model reliability. The pace of innovation speeds up as AI prototypes products and processes at unparalleled rates. Hierarchies will flatten, replaced by agile ‘pods’ or micro-teams supported by AI-driven workflows. Finally, ethical and social considerations become structural vulnerabilities ( e.g. your product could get ‘cancelled’ like a celebrity does on social media). As AI grows more powerful, leaders need to more carefully consider ethical guardrails into their foundational strategies. Not typical for start ups trying to ‘move fast and break things.’

What Might the AI Start Up Business of the Future look like?

If you were starting from scratch, this is what you would consider:

1. AI as Core Infrastructure. AI isn’t an add-on—it’s the backbone of the business doing 90% of the work, with failover AI models and self-improving AI loops ensuring resilience.

2. Modular AI Workflows. Business operates like an AI OS, with replaceable AI modules. Instead of departments, we will use modular AI workflows. AI models will specialize in different functions. E.g. HR can use it to select and vet candidates, handle skills assessment and pay negotiations. Each aspect is an AI module, and can be swapped or improved without effecting the whole work flow.

3. Redundancy & Failover AI. No single AI model should control everything.

4. Elasticity & Self-Improving AI. AI self-corrects mistakes and continuously improves, this will help companies build moats by training their own version of popular models and accumulate unique data sets too. E.g. AI can automate marketing campaign creation, A/B testing, and performance tracking to improve future campaigns. We are doing this already at our venture Contentive.com.

5. AI-Driven Strategy Optimization. AI continuously tests, refines, and adapts business models. Bringing AI into management meetings and Board rooms as a colleague is already happening and its collective intelligence should be fed so it builds up the equivalent of a longitudinal medical record over time.

6. Continuous Evolution. The business must be designed for constant iteration and learning. AI can access and process enormous data pools in real time & suggest pricing improvements, revised business models and new products for development.

The outcome (if you get it right) is a resilient business ( and people) built to adapt, with the best engineering principles from nature and engineering applied. One that scales infinitely, operates autonomously, adapts to real-time market shifts, and never stops evolving.

Sources:

• https://www.nibs.org/

• https://www.amazon.com/Structures-Things-Dont-Fall-Down/dp/0306812835/ref=sr_1_1?

• Long chats with ChatGPT!

1. Prioritize Timing and Team: The timing of your market entry and the strength of your team are crucial for success, often more so than the idea, funding, or business model in the early years. The right timing can make all the difference, and having a capable team is important to navigate the many challenges that will arise. If someone isn’t great and in a key position, develop them to great, or move them on to something they can be great at. That can be internally or externally, but help them. How we deal with people we move on matters to the people staying too. And kindness is not that hard to do.

2. Managers Are Coaches & Culture Carriers: Hire managers who excel at coaching, developing their teams, and are strong communicators. This approach enhances communication within your company and builds a strong organizational culture. Remember, as the CEO, you are the Communicator-in-Chief, and your managers should mirror this by fostering open dialogue and growth among their team members and reflect the culture you lead with.

3. Act on Lingering People Issues: Address persistent concerns promptly, especially when it comes to personnel. Ignoring issues can lead to larger problems down the line. Often, you might sense something is amiss—don’t ignore that intuition. Reflecting in writing can help you identify and tackle these issues head-on. One problematic individual can hinder an entire team’s performance, so don’t settle for mediocrity or poor behavior.

4. Communicate Clearly: Ensure your team fully understands goals, expectations, and strategies through clear and specific communication and the facts and truth of things. This clarity sets the tone for the entire organization. Regular business cadences and meeting agendas facilitate this, along with a weekly CEO update. Remember, most problems stem from misunderstandings or poor communication or not following up, especially during departmental handoffs and when defining responsibilities.

“The hardest thing to explain is the glaringly evident which everybody has decided not to see.”
― Ayn Rand, The Fountainhead

5. Stress-Test Your Opinions: Encourage others to challenge your views and consistently engage with customers and external sources to refine your perspectives. Make it clear to your team that while they should feel free to question and provide input, once a decision is made, execution should follow with conviction. Demonstrate this openness by seeking feedback from various sources, including trusted network contacts and family. Be prepared to adjust your approach based on new insights, but remain decisive—after all, as CEO, your role is the ‘Chief Decision Officer’.

6. Engage in Third-Level Thinking: Dive deeper into issues to understand underlying causes and visualize the potential ripple effects of your decisions. This approach often leads to different, more effective choices. For instance, when planning a major change like hiring a new executive or entering a new market, consider not just the immediate impact but also the secondary and tertiary consequences. This kind of thinking has saved me from making ill-advised decisions on numerous occasions.

Einstein once said, “You can’t solve a problem from the level of thinking that created the problem in the first place“.

7. Understand Context: Always consider the specific circumstances surrounding your decisions. If something doesn’t make sense, ask more questions. This practice prevents assumptions and helps you avoid mistakes. Continually seeking context ensures that you’re making informed decisions based on the full picture. Try and build a practice of asking more questions in every meeting with your team and in your 121’s with your senior team. It will often cause them to go off and ask further questions too. We are all often moving so fast, especially on urgent topics, we don’t often go deep enough. You building this ‘learn more’ mindset in your organisation through your example, will carry into its culture.

8. Use the Null Hypothesis: Challenge assumptions by testing the default position that a proposed change or investment will not have the desired effect. Its at least a good thought experiment and discussion topic. For example, assume that a new AI training tool will not improve sales or justify the investment. Test this by implementing it with a portion of your team and measuring the outcomes. This method helps protect against the “shiny new object” syndrome and ensures that any new initiative is truly beneficial before full-scale adoption.

9. Counter Decision-Making Bias: Recognize that people deeply invested in a project may only see its positives. Actively ask what could go wrong and plan to mitigate those risks. Conduct formal pre-mortem sessions to anticipate potential failures and address them proactively. At a minimum, require teams to include risk assessments in their proposals. In addition the diversity of the team makes a difference. Finally your own bias makes a huge difference. I have a strong bias for action and am impatient, and so use a question to myself “have I discovered and listened enough yet” to try and stop my own bias from impacting the quality of the decision. I have no idea how many bad decisions are made in an organisation; but I think we are probably not even aware of many of them! But you can ‘feel it’ when the decision making is good, and you move on it, it feels easy to explain, including the downsides. So if you don’t ‘feel’ that it is good as you make it, you probably need to relook at it.

10. Reflect in Writing: Document your decisions and their outcomes regularly. Keeping daily reflections and weekly logs allows you to track what worked, what didn’t, and why. I have completed weekly reflections for over 25 years. This practice helps you identify patterns, reinforce learning, and make better choices in the future. Consider questions like: What’s working? What isn’t but could with adjustments? What is failing and needs to be addressed?

11. Separate Decision Quality from Execution and Outcome: Understand that a good decision can still lead to a bad outcome due to factors beyond your control. Focus on making high-quality decisions and ensuring they are executed as intended. Recognize that even with excellent execution, results aren’t guaranteed. This perspective is particularly useful when testing new products or exploring growth opportunities and encourages you to think in expected value/bets. Meaning you won’t bet the farm.

12. Rely on Analysis: Base your decisions on data and thorough analysis rather than intuition alone. While gut feelings can provide initial direction, supporting them with data ensures sound decision-making. Gather as much information as possible from your teams, customers, and external sources to inform your choices. This will actually help you ‘feel’ if the decision is a good one, to the points made in 9 above.

13. Analyze Transactions Deeply: I say to teams”how much and how many” all the time. Look beyond financial summaries to understand the fundamentals of your business—such as the number of customers, daily sign-ups, product performance, and unit economics. Regularly dissect transactions by geography, time periods, and other relevant factors. This deep dive reveals critical insights that high-level financial metrics might obscure. Also, establish a routine where your finance team conducts unit economics analyses on all products and customer segments every six months. Make sure your management team have units and customer numbers, not just revenues, in their weekly management reports.

14. Apply Statistical Tools: Utilize methods like linear regression and correlation analysis to uncover trends and relationships within your data. Often, these statistical tools can highlight truths about your business that aren’t immediately apparent, making it easier to make informed decisions. Your FD can show you how if this is not your area of expertise.

15. Follow Through on Strategy Implementation: Building on point 11. Good strategies fail without diligent oversight of their execution. Regularly verify that your strategies are being implemented as intended. Embed checks such as progress presentations, regular check-ins, and key performance indicators (KPIs) to monitor execution. Ensure that your agenda and 121 with your teams includes updates on all key projects. A Chief of Staff is a key tool in ensuring strategy execution, and worth their weight in gold because of it. Having a Chief of Staff join meetings, check on execution, and be the constant action chaser, will ensure speed and completeness of the decisions made.

16. Predict Change Actively: Anticipate industry shifts by consistently looking 12–24 months ahead. This forward-thinking approach is as crucial as managing day-to-day operations. Most CEOs don’t do it or it suffers to todays urgent agenda. While it’s easy to get caught up in immediate issues, maintaining a long-term perspective enables you to navigate future challenges effectively and will often change what your prioritize today. When planning annual budgets, consider starting with projections for the following year to set more strategic goals and working in detail back to what needs to happen today.

17. Recognize Prediction Challenges: Accept that making accurate forecasts is inherently difficult. Stay adaptable and prepare backup plans to adjust as circumstances change. This mindset allows you to respond effectively when unexpected events occur, ensuring your business remains resilient. Again helping you think in bets and expected value.

18. Consider Constants: Build your strategies around elements that are unlikely to change in the future. Focusing on constants—such as core customer needs or foundational team members—provides stability in a rapidly changing environment. For example, regardless of technological advancements, customers will always need reliable service delivery from point A to point B.

19. Seek Uncommon Opportunities: The best opportunities often exist where others hesitate to go or where the work seems too challenging. Success frequently lies on the other side of hard work. Embrace complexity and be prepared for a longer journey when pursuing unique opportunities. Many people give up when things get tough; persevering can set you apart from the competition.

20. Do Things That Don’t Scale First: Focus initially on creating valuable customer experiences, even if they’re not immediately scalable. Testing solutions directly with customers or internal users can provide invaluable feedback. With advancements like AI and no-code tools, it’s easier than ever to prototype and refine these experiences before scaling up.

21. Practice Disciplined Capital Investment: Be meticulous and strategic with capital investments, treating each dollar as if it’s your last and it must yield results. Use expected value calculations and consider your time horizon. For example, decide carefully whether to invest in expanding your engineering team for faster feature development or to allocate more funds to marketing for immediate sales growth. Involve your finance and product teams to run scenarios and gather insights, including customer feedback and competitor analysis. Establish criteria for investment decisions and evaluate options against them, often finding that a balanced approach yields the best results.

22. Cash Management: Maintain vigilant oversight of your cash flow. Regularly review debtors and creditors in your weekly meetings. If issues arise, investigate promptly—they could stem from process inefficiencies or inadequate sales management. Proactive cash management prevents small problems from escalating into significant financial challenges.

In Summary:

As a CEO, your role encompasses being both the Chief Decision Officer and the Chief Communication Officer. These two areas done well lead to successful execution. Begin by assembling a strong team and promoting clear, open communication. Employ deep analytical thinking and leverage data to inform your decisions, always considering the context and being mindful of potential biases. Diligently follow through on your strategies, anticipate industry changes, and remain adaptable to unforeseen circumstances. Seek out opportunities that others might overlook and practice disciplined investment, ensuring that every dollar spent is justified and strategic. Keep a close eye on cash flow to maintain financial health.

Remember, our thoughts are the heaviest baggage we will ever carry. It’s essential to “pack well” by equipping yourself with effective thinking tools. Regular reflection and documentation of your experiences will help you learn and grow, ultimately refining your approach as a leader, ensuring your reach your destination.

You can work through decisions with this Custom GPT I created here:https://chatgpt.com/g/g-vAp7RMOR0-ceo-decision-making

Good luck!

Listen to a podcast of this article here (courtesy of Notebooklm.Google)

Introduction

The software landscape is in flux. We’re moving away from rigid, monolithic SaaS platforms with static interfaces and entering an era of fluid ecosystems—where user experiences are dynamically created, shaped by AI, and adapt to context. For those still adhering to old SaaS models, it's time to reconsider. While traditional SaaS offers stability and predictability for some sectors—especially those needing controlled environments—failing to adapt holistically to user needs will render technology irrelevant.

Today’s users demand more than stability; they want adaptability. Some users, particularly in regulated or less tech-savvy industries, may prefer stability, but most need tools that seamlessly fit their workflows and adjust in real-time. Modern software must be fluid, adaptive, and personalized.

Fluid UIs and Cognitive Context - The Example in Sales

Traditional SaaS is limited by its rigidity, assuming users will adapt to its quirks. Today, users, especially in roles like sales or marketing, require cognitive context—tools that understand their goals in real time and adapt to them. Think of a sales rep’s workflow involving HubSpot, email, LinkedIn, Slack, calling, text messaging, and other level one platforms. Our job as developers is to build something that integrates seamlessly into these flows—becoming part of an integrated workspace rather than existing in isolation.

Dynamic adaptation tailors the experience based on user context, preferences, and needs. GenAI allows this immediate cognitive decision flows for the first time. For example, sales functions is an area ripe for support due to the multiple inputs, data, and tasks. A sales rep preparing for a meeting might have the system automatically surface relevant customer data and suggest talking points—all without needing to search manually. Users move across various core environments, and our ‘software’ must integrate without adding friction.

Nested Jobs and Dynamic Workflows

Continuing with our example of a Sales person. They do more than just “outreach” or “close deals.” They handle nested tasks: writing emails, prepping for calls, analyzing metrics. Each action is part of a larger workflow requiring different tools and support. To help users effectively, we must assist at these micro-levels, providing contextual nudges at the right moment.

These micro-tasks are best understood when we think about the Jobs-to-Be-Done (JTBD) framework. Users don’t just have a single job—they have layers of jobs that build up to achieving the ultimate goal. This means building solutions that don’t exist in isolation but integrate API-first into platforms like Slack or LinkedIn, delivering adaptable, fluid utility. An API-first approach allows us to be where users need us, delivering exactly what's required at the right time. However, API-first comes with challenges—complexity and security vulnerabilities. Effective risk management, through robust security and well-documented integration, is essential.

A practical example is when an AI assistant proactively suggests and writes the messages for a sales rep to follow up with contacts after a successful meeting from transcripts, then surfaces related CRM notes and emails to add depth to the interaction and prepares a simulation for them to practice to nail their next call. Instead of treating each system—CRM, email, LinkedIn—as separate entities, they become components of a holistic workflow. AI-driven insights can help identify synergies and suggest the best course of action, thus making every interaction more impactful.

Ecosystem Development in Sales Enablement

Collaborative environments are the future. Yet, not all users or businesses are ready for such interconnected services, especially due to privacy, security, or regulatory concerns. In these cases, simpler, isolated services may be more suitable. The goal, however, is to create ecosystems where providers work together, leveraging AI and APIs to build integrated, value-driven solutions.

AI agents dynamically generating user interfaces are more adaptable than static UIs. These context-aware UIs present the tools and information that matter most at any given moment. Unlike static interfaces, AI-driven ones evolve as user needs change, delivering a more intuitive experience. Agentic AI services can orchestrate multiple platforms, leveraging microservices architecture to seamlessly combine functions. Natural language interfaces further simplify interaction by making it conversational and intuitive.

All these elements are top of mind for our product team at our venture HivePerform. They are embedding its skills development and intelligence services into each sub task of the Sales Reps and Sales Managers. Enhancing sales performance within existing UIs and tools, and without interrupting workflows or creating new ones.

Adapting to Cognitive Context and Fluid Services

The future isn’t about standalone platforms. It’s about creating interconnected, context-aware ecosystems. Traditional SaaS—rigid and isolated—still serves a purpose in sectors prioritizing compliance and fixed workflows. However, future tools must embrace contextual fluidity. Developers and product managers must go beyond product development to integrate into real user behavior.

Think of your product as a node in a larger ecosystem, not a standalone app. Embed capabilities within user workflows, drawing them into specialized environments when needed. Success is about timing and context—delivering insights and capabilities precisely when they are needed.

Product Operating Principles for the New SaaS Era

To thrive, companies must go beyond Product Market Fit and achieve Company Market Fit. Product teams’s must widen their typical four lenses of risk (Value, Usability, Feasibility and Viability) to a broader ecosystem to gain most-favored-nation status for their solution:

1. Measure Ecosystem Engagement: Track integrations and partnerships. Evaluate their impact compared to competitors, considering partner significance and user engagement for Business Viability Risk management.

2. API-First and Network Awareness: APIs enable you to be part of broader workflows. Design products that can seamlessly integrate into various user environments for Viability and Technical Risk management.

3. Focus on Jobs-to-Be-Done: Understand the extended workflows of your customers and identify how your product fits into the entire job they need done to mitigate Usability Risks.

4. Market Engagement: Visibility is key. Engage with larger players, build partnerships, win awards, and position your company as an industry thought leader for Business Viability management.

5. Utilize No-Code Compatibility: Make your solution accessible with no-code tools to encourage widespread adoption and manage Usability Risk.

What Will be the Name of the New SaaS?

New types of SaaS models, new categories and terminology are coming. Like Hive Perform’s agentic suite of ‘Buzz agents’ that embed & connect intelligently like worker bees across client’s existing core software . SaaS but more than SaaS.

Some example potential new categories ( provided by Claude)

1. Intelligent Services Platform (ISP)

Definition: A platform that provides AI-driven services capable of dynamic integration and personalization, going beyond traditional software delivery.

Rationale: Emphasizes the intelligence aspect and platform-based delivery of services.

2. AI-Orchestrated Services (AIOS)

Definition: Services where AI agents orchestrate various functionalities and data from multiple sources to deliver tailored outcomes.

Rationale: Highlights the role of AI in managing and coordinating services.

3. Dynamic Interface Services (DIS)

Definition: Services that provide user interfaces dynamically generated and adjusted in real-time based on user needs and context.

Rationale: Focuses on the fluid nature of UIs in the new landscape.

5. Agentic Task Services (ATS)

Definition: Platforms that utilize autonomous agents to perform tasks, integrate services, and interact with users and systems.

Rationale: Captures the agency of AI systems in delivering services.

Conclusion

The SaaS world is shifting toward a network of interconnected capabilities. Thriving in this environment means embracing Company Market Fit and becoming indispensable within broader ecosystems. Adapt now, or risk being left behind.

Sources:

• https://www.ingentaconnect.com/content/hsp/ama/2023/00000009/00000003/art00008

• https://www.researchgate.net/publication/381924489_The_Future_of_B2B_Sales_How_Generative_AI-Driven_Tools_are_Changing_the_Game

• https://dl.gi.de/items/389f3565-420c-4e1e-90fd-ea2fbaf649e0

• www.blenheimchalcot.com

• www.hiveperform.com

Products working well. Key customer renewed. Hires in place. A CEO’s days are focused on building and selling their products. They are consumed with trying hard to get customers to like it and ensure it ships on time and to sell more of it. They may even be experienced product leaders and know enough to start with a difficult problem. To then work hard to develop a novel solution customers love, building to Product Market Fit (PMF).

One layer beneath PMF is a harder question: does the company itself have a market? Investors have been answering this question about you from the day you took their cheque, and they have not been asking whether customers love your software. They have been asking whether, in the ecosystem you operate in, your company occupies a position that someone else would pay a premium to inherit. Whether you are the default integration, the assumed partner, the name that comes up in the RFP without being invited.

To investors the company is the product.

Investors are often more concerned and aware of market dynamics, competitors, and trends that can hurt or help their ‘product’ than CEOs.

Going up a level to Governments. They see industries as products to develop their country and solve some fundamental problems, such as energy shortages, immigration attractiveness, and aging populations. You can see this in the Middle East as they seek to attract millions of immigrants through importing and creating sports industries from scratch.

If company CEOs did this thought experiment, how would their behaviors change? They would likely align in their thinking with their investors, and pick a strong market with attractive properties.

Let’s do the thought experiment for them:

Comparison Table

Thinking about Industry Country Fit, Company Market Fit & Product Market Fit

Definitions

Product Market Fit is building a unique superior solution to solve a valuable pain point. It needs a common set of customers, that are willing to pay for it, in quantities and prices that sustains the business (profitable).

Company Market Fit means your business is recognized as the leading solution provider in your ecosystem and is integrated with your customers' key systems & partners.

Industry Country Fit means the selected industry is on a government’s strategic priority agenda and tax and incentives to innovate are attractive and the industry is set for fast growth.

Reviewing the table above, should lead a CEO to a reconsider how a product and company is developed and maybe the industry they select. Below is a simple guide CEOs could follow. Allowing them to try and achieve Company Market Fit at the same time as they are building to Product Market Fit:

Tablestakes for Achieving Company Market Fit:

1. Understand the Ecosystem:

   • Map out the key players in the ecosystem (users, suppliers, partners, media, events, competitors).

   • Identify potential partnerships and integration opportunities.

2. Enhance Product Integrability:

   • Ensure your product or service can be easily integrated with popular platforms and tools.

   • Develop and document APIs for seamless integration.

3. Leverage No Code Tools:

   • Enable customers to integrate your service using no code tools like Zapier.

   • Provide tutorials and support for using these tools and your services.

4. Network and Partnerships:

   • Build relationships with key players in the ecosystem.

   • Seek out strategic partnerships that enhance your value proposition.

   • Regularly review and expand your network.

5. Market Presence and Awareness:

   • Participate in industry events, webinars, and panels.

   • Publish thought leadership content and case studies.

   • Apply for industry awards and recognitions.

6. Customer-Centric Approach:

   • Engage with customers to understand their broader needs and how your product fits into their workflow.

   • Develop features and services that address these broader needs.

7. Monitor and Measure:

   • Track the number and quality of integrations and partnerships.

   • Collect feedback from customers and partners to assess the value of integrations.

   • Monitor market trends and adjust ecosystem strategies accordingly.

Metrics to Measure Progress:

• Number of technical integrations.

• Importance and usage of partnership channels.

• Customer satisfaction and feedback on integrations.

• Market presence indicators (awards, speaking engagements, published content).

• Growth in network and strategic relationships.

The product is what the customer buys. The company is what the investor buys. The industry is what the country buys.

Once you see it this way, the work changes. You stop measuring yourself only against the product roadmap and start measuring yourself against the ecosystem map. You ask which two integrations are load-bearing in your category and which ones are vanity. You ask where the distribution bottleneck lives that your competitors have not yet noticed. You ask which standards body, which procurement framework, which government agenda is quietly deciding who wins the next decade, and whether your company is inside that conversation or outside it. You stop treating thought leadership as marketing and start treating it as positioning: the ecosystem only defers to companies whose view of the future it has already absorbed. None of this replaces product market fit. It protects it. It is the difference between a company that exits at a financial multiple and one that exits at a strategic multiple, and in the end that difference is ten years of the founder’s life.

Conclusion

Product market fit is what keeps you alive. Company market fit is what makes you inevitable. Industry country fit is what makes the wind decide to blow in your direction.

Company Market Fit is: Maximizing the value of the ecosystem surrounding your business to gain most-favored-nation status for your specific solution. If you follow it as a strategy, everything you do in achieving product market fit will be more sustainable and secure.

The founder who only builds a product builds something that can be copied. The founder who builds a company and chooses an industry builds something that cannot.

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Sources:

• Lee Arthur Company Market Fit:

  https://leearthur.substack.com/p/product-market-fit-is-no-longer-enough

  Barrons: Slack accuses Microsoft of illegally tying Teams to Office in EU complaint

• QuickBooks: Intuit QuickBooks

• Stripe: Stripe

• Zapier: Zapier

In an era where digital transformation dictates market dominance, CEOs and C-suite leaders of startups & scale ups must transcend beyond traditional Product Market Fit. The concept of Company Market Fit emerges as a crucial strategy, representing the harmonization of your business's ecosystem to secure a coveted position in your industry. This strategy demands a comprehensive understanding of how your services and products integrate seamlessly across diverse channels, aligning with customer preferences and augmenting the value chain.

Evolving Competitive Landscapes

The digital revolution has rendered competitive barriers more permeable. Giants like Microsoft and Slack exemplify this, where strategic moves can redefine market positions overnight. Your business's attractiveness hinges on your ability to integrate, innovate, and partner strategically.

Leveraging the API Economy and No-Code Movement

In this API-driven era, connecting complementary services to craft innovative solutions is faster and more efficient. The rise of no-code platforms like Zapier and Airtable empowers businesses to tailor-make solutions, underscoring the need for adaptable, user-friendly integration capabilities.

Strategies for Company Market Fit

• Network Awareness: Delve into your business's network ecosystem. Understand and map the interconnections between your users, suppliers, and partners to amplify your market presence.

• Customer-Centric Solutions: Identify the broader scope of your customers' needs. Tailor your offerings to address not just immediate requirements but the entire spectrum of their business processes.

• Industry Engagement: Elevate your market visibility. Engage in industry panels, publish thought-leadership pieces, and foster partnerships to position your company as an integral component of the industry fabric.

Think of your company as a product, where the surrounding ecosystem of businesses forms your customer base. Strive for Company Market Fit to ensure your place in the evolving digital landscape.

Measuring Fit

Assess your Company Market Fit by analyzing the breadth and depth of your technical integrations and partnerships compared to your competitors. Consider the influence and reach of these partnerships and their impact on your users.

What has changed?

Getting turned into a feature or devalued is a constant threat

A bigger tech platform can turn your business into a free feature overnight. Example Microsoft made Teams free and put a serious dent in Slack’s business. They can also partner your competitor; powering up your competition’s utility to customers, and reducing yours. Creating reduction in the attractiveness of your business. Not a preferred Salesforce partner? Sorry, we will buy from your competitor.

https://www.barrons.com/articles/slack-accuses-microsoft-of-illegally-tying-teams-to-office-in-eu-complaint-51595439933

Digitization of business makes competitive barriers fall

As digital business pervades every aspect of society, adjacent markets are no longer the heavy investment they used to be. It’s easier than ever for competitor’s to enter your space, especially if they pick a good channel-partner to your customers attention. It’s also easier than ever to test demand and spin up complimentary propositions to solve more aspects of a customers problem. So we may have the same customer, and I decide to try to take your share of their spend too! Intuit & Stripe are great examples of this, constantly adding new services that extend their value to small businesses.

https://quickbooks.intuit.com/

https://stripe.com/

API connectedness

APIs have made connecting complimentary services to build new value propositions speedy & easier than ever. Product managers and development teams no longer have to build everything and their services can sit within other companies products & services too. They naturally look for partner-solutions as they develop their own products & solutions. Meaning you can have many more routes to market by enabling your services to be embedded with others, and vice versa.

• What is an API?

The Rise of the API Economy

No Code needed

Buyers are more comfortable with tech than ever, and so the rise of No code tools like Zapier and Airtable are enabling them to feel empowered to build their own solutions. Can they plug your service themselves to their other tools? If not, you may want to work out how they could.

• What is no code and why should you care?

How to achieve Company Market Fit?

I don’t know. But here are some clues:

Get network aware

Couple of things I wrote about previously worth reviewing. Understanding how you fit in to a wider network and literally mapping it:

*How can we connect your users, suppliers, partners, influencers; in meaningful ways where they will serve your purpose, make it their own, and direct more energy to you as part of the network?*

• Nested Networks & the Species Most at Risk

• Gaining Strategic Insights by Mapping an Ecosystem

Job to Be Done

Get close to your customer and understand the extended tasks they are doing where your solution is only part of a much bigger job to be done. For example if you sell marketing content management tech. Work out what else happens before and after you supply the content that involves your buyer, and your buyers colleagues. Who else would one day sell your product or benefit from a partnerships?

Flirt

Become known in your market by players bigger than you, and by compliments, and adjacent potential partners, and your suppliers CEO. Winning awards is a good approach. So is speaking on panels, sharing integration news of your latest partnership or tech integrations, writing and sharing publicly about the wider market and its direction. Become known by your ecosystem as an expert company and an important part of the market.

Think about your company as the product, and the ecosystem of companies around you as the customers. Get your Company Market Fit not just Product Market fit.

How to measure it

A leading indicator that you have captured most favored nation status, could be: a review of the number of technical integrations and partnerships you have vs. your top 10 competitors. And weighting them in size of partner importance, usage, and how much your users (or their colleagues) use or care about those integrations. To be continued..

Company Market Fit: Maximizing the value of the ecosystem surrounding your business to gain most-favored-nation status for your specific solution.

This is the first of a series of posts on the hard and rewarding journey to building a great business. All the posts that follow will reference the above map.

It takes many years to build a great company. Let’s say ten. It splits into two halves, the first trying to find a big enough market with a problem you want to solve. You will need to follow a ‘scientific method’ to not fail here. The next half is growing and improving your business operations to capture the opportunity, before someone else does. This is its own world of special pain and challenges. At around year 4-5, after many false starts, you begin to see evidence you might have something that could last. Then around years 7-8 you feel less paranoid you may go out of business, and even start thinking about the next ten years.

Why You Need the Map

Its really f**ing hard! 70% of venture funded companies fail at 20-months after they get their money. (source: CB Insights). The biggest factor of those failures was having no market (42%). Most start up companies get rejected for VC funding; so you can imagine that only a very small fraction of companies get built to last (or built to any kind of meaningful size). See the diagram below on the size of US companies. Only 0.3% grow to be more than $10m in size.

To avoid being part of the 99.7%, you need the map. It represents the Market Led Scientific Method (MLSM)™ to creating a great business from scratch. My definition of great is we reach more than $10M in annual revenue and will last longer than 10 years. (Noted there are many great smaller businesses, this is not for them)

The Scientific Method

Many of the frameworks you see on the map, are built on the core scientific method of discovering something useful to know. That could be a painful problem or what a good solution could look like. It reduces the chance of avoidable f**k ups; stuff like building a product or service no one wants or selecting a market that is too small to be viable. Most start ups make these errors on the way to success, its much harder to avoid than it is to say, because you have to embrace being wrong constantly. None of us like that ,and we ignore it with excuses on why we could be right. You can google ‘Scientific Method’ and learn about it easily and quickly. Doing it well is a different matter altogether.

Here are some Scientific Methods that are context specific to innovation and building products/businesses.

Summary

Most start ups fail and the 99% of those that don’t, end up being less than $10m per annum in size.

With 24 hours in every day, 11 are spent in front of a screen. Let’s say for 7 hours, we sleep. That leaves us only 6 hours each day in the physical world ( eating, traveling, exercising, social in-person contact, live events). So 65% of waking hours are in the online world, not the physical.

source: https://en.wikipedia.org/wiki/Screen_time

So Much Information, So Much Comfort

We have endless experiences online, infinitely more than we can consume. Multiple ways to be fed content (email, Twitter, tv apps, messaging apps, social networks, notifications, news sites, and even the odd phone call). More jobs are becoming ‘digital’ jobs. Network effects accelerate the need to spend more time in the digital world. ( because everyone else is, you have to) Social networks pull us into multiple, never-ending communication streams that last for hours, days, even years ( Whatsapp, Instagram, Facebook, Linkedin). Be online or don’t exist, always attached to your phone. Your online persona and image are now more important to you than your physical one. ( Does anything below the waist really matter now?) The experiences created in the digital world for us are so comforting and compelling, why leave?

Blurred Lines

Augmented reality will invade our physical world further, moving more time online to let’s say 80%, leaving under 3 1/2 hours in the physical world each day. Blurring the lines between the two so we are never disconnected. Removing our innate ability to do what were once basic tasks without digital support. Tried getting around without Google maps lately?

Define Yourself or Be Defined

What does that mean for our identities? If most of who we are, exists only online. How do we best translate our personality to the digital world and retain it? Will we be ‘ourselves’ anymore or a product of the messaging and media we consume? Can we be controlled more easily now we are an ever-connected node on a network; our every whim, desire, and action recorded. Will the physical world become less and less attractive as our addictions are fed by algorithms (AI) that become too smart for our own good? (Kid’s don’t want to go outside and play, 3D games are much more fun!)

A bunch of smart scientists, worried about the future of humankind because of these issues, put in place some guiding principles to protect us from the AI genie now released out of the bottle:

https://futureoflife.org/ai-principles/

Personal Privacy: People should have the right to access, manage, and control the data they generate, given AI systems’ power to analyze and utilize that data.

Liberty and Privacy: The application of AI to personal data must not unreasonably curtail people’s real or perceived liberty.

Human Control: Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.

The three listed above seem to be the most difficult guidelines to deliver on given the nature of governments’ protection and control instincts.

One Massive Network

“Surveillance capitalism establishes a new form of power in which contract and the rule of law are supplanted by the rewards and punishments of a new kind of invisible hand.”

Software maps of the world are being built in ever-increasing detail so the exact location of everything can be known. We are sharing our location every second; together with health data, shopping habits, social connections, and even our internal thoughts. Our responses to a stimulus can be exactly predicted and optimized: to protect us, guide us, and meet our needs perfectly AND control our responses, actions, and decisions. Dubbed Surveillance Capitalism in this research article. Well worth a read.

Great benefits and great risks walking hand in hand like soul mates.

Ten Key Themes

Thinking about the above trend to ever connectedness, and a digital life; here are relevant themes of innovation and consequences:

Counterculture Economy

This one is my favorites. Commerce will grow that helps you avoid being consumed by the digital world; to be self-sufficient, more self-connected, able to balance with nature and the physical environment. The Circular Economy is a component of that.

Manual Work Will Disappear

Self-driving cars, robotics, and AI will remove most manual work and chores, freeing us to spend even more time in the digital realm. First, your vacuum cleaner became a robot, then your warehouse job, then your car.

Taxes & Regulation

There will be a digital war of taxes and regulation as governments, states & cities attempt to own the commerce ‘happening’ in their physical location.

Media Becomes Increasingly Important

Branded media outlets with trusted information become even more powerful in a world of over-supply and disinformation.

Lifetime Education

Covid has shown people it is human nature to learn skills constantly when given the time. (so many proud new bread bakers, artists, and woodworkers during lockdown) The move to digital jobs will compound the need to always be learning.

Genetics & Technology

We can mix biology and technology. Elon Musk’s high profile brain chip was successfully ‘installed’ in a pig. Why wear glasses, carry a phone when you can have it installed under your skin?

Nanotechnology

We can manipulate matter at the level of the atom. We do this already in sunscreen and car paint; human DNA is next.

The impact of the above two on healthcare will be game-changing, meaning people can live much older and healthier lives; although Covid has shown us nature finds a way to remove imbalances in animal populations.

AI

Will allow us to power innovation, productivity, and speed at scale. Any company not having AI as a muscle it flexes easily will get out-competed. As if you're still using a typewriter and sending letters while your competitors send thousands of emails. (though sending letters is not a bad strategy at all!)

CB Insights Top 100 AI Companies of 2020

Climate Change Technology

In moving to renewable energy, thousands of new innovations never before imagined will sprout from green, virtually zero cost, energy sources.

3D Printing.

I like this technology simply because it’s the mirror opposite of current manufacturing (additive vs subtractive). Printing anything we want, anywhere. Including homes.

Am sure there are more key future trends and themes. But the above seems promising in creating an equitable, healthy world and a huge amount of new business opportunities and innovation too!

Good luck in 2021!

Sources:

https://singularityhub.com/2020/12/27/how-a-software-map-of-the-entire-planet-could-change-the-world-forever/

https://singularityhub.com/2019/02/27/the-worlds-most-valuable-ai-companies-and-what-theyre-working-on/

https://www.pewresearch.org/internet/interactives/privacy-scenarios/

https://www.pewresearch.org/internet/2017/02/08/code-dependent-pros-and-cons-of-the-algorithm-age/