Marcus Coetzee

I spent 35 years building a consulting career around a brain I didn’t fully understand. Through trial and error I made intuitive career choices and developed a set of compensatory systems without knowing why I needed them.

This essay is my attempt to make sense of it all. I try to describe, in plain language, ten distinctive ways my brain works and how I’ve adapted my environment and methods to accommodate them. I write about minimalism, movement, trance states, pattern recognition, information obsession, and the tendency to question every assumption I encounter. I also write honestly about the costs: the career trade-offs, the financial consequences, the persistent feeling of being on the outside looking in.

I have also written it for people struggling to make sense of their unusual thinking and working preferences, and for people close to them. Someone remarked it would make a good teaching case study for therapists, and I’m happy for it to be used that way, without charge.

The UK voted to leave the European Union in 2016. Ten years later, the Labour government is debating whether to rejoin, citing Brexit as a net economic loss. But from my perspective, Brexit never really happened. The UK left its biggest marketplace and made it harder to travel to Europe. The experiment was never properly conducted, which makes it impossible to evaluate properly.

I examine six areas where Brexit should have delivered economic benefit: trade relationships, people and skills, capital and investment, industrial capacity, business environment, and resilience and self-sufficiency. The first two produced immediate consequences, most of them damaging. The remaining four represent a failure to use the freedoms Brexit theoretically recovered.

My conclusion is that Brexit was one of the most spectacular planning and implementation failures in modern British political history. Britain never found out whether Brexit could work, because it never tried to make it work.

I wrote this essay because I kept encountering two increasingly entrenched and opposing views about rich people, and I found both of them inadequate. One treats wealth as inherently suspect, the other treats markets as a cure-all. Neither asks the more useful question: what kinds of rich people does a country actually want?

This essay sets out a framework for answering that question. I argue that rich people are neither inherently good nor bad, and that the debate about wealth is badly distorted by a fixed-pie view of money that does not reflect how modern economies actually work. I draw upon UK and South African tax statistics to demonstrate just how concentrated the tax base is and how reliant public spending is on rich people paying tax.

From this, I propose a set of principles for the kind of wealthy person a country should actively try to attract and retain, covering how they earn, spend, invest and hold assets.

Alongside the Loch Ness Monster, the disappearance of several great industries is one of Scotland’s most intriguing mysteries. This mystery has puzzled me since I moved to Scotland in 2021. I did not expect this long-form essay to emerge from my investigations, nor did I expect it to reach around 25,000 words. Neither did I expect that the factors behind Scotland’s industrial decline over the past two centuries are still in play today, still undermining any attempts to revitalise industry.

Scotland was an industrial giant during the Industrial Revolution and the early 20th century, but now manufacturing contributes only one-tenth of Scotland’s economic output. The Scottish economy is now built on whisky, hospitality, tourism and other services. Traditional industrial activities seem viewed with suspicion.

Yet everywhere I visit – towns, villages, heritage centres, museums – I find the same thing: the memory of great industries and the nostalgia of people whose parents and grandparents worked in them. The question that kept nagging at me was why Scotland had built something so remarkable and then let it go. This makes no sense from an African perspective, where governments are desperately striving to achieve what Scotland had.

I wrote this essay the week after the Defence Secretary revealed that the Royal Navy had spent over a month tracking three Russian submarines in the North Atlantic, specifically designed to survey undersea infrastructure in peacetime and sabotage it in conflict. This news finally pushed me to write something I had been contemplating since the Nord Stream pipelines were blown up in 2022.

The UK depends on approximately 62 fibre-optic cables, six gas pipelines and ten electricity interconnectors running along the seabed to connect it with the rest of the world. More than 95% of our internet traffic, three-quarters of our gas, and a significant share of our electricity all arrive this way. This essay maps that infrastructure, examines a series of real incidents where cables and pipelines have been damaged or threatened, considers how drone warfare is changing the threat picture, and asks what the UK government is doing in response.

My biggest concern, having done the research, is not the threat itself but the gap between the scale of the risk and the seriousness of the response. The UK owns no cable repair ships. It has one dedicated ocean surveillance vessel. Churchill worried about U-boats. The modern equivalent is already here, and we are not yet taking it seriously enough.

I wrote this essay because I kept hearing the same conversation everywhere I went. Charities complaining about local government. Local government complaining about the Scottish Government. The Scottish Government complaining about Westminster. Everyone arguing about their share of the pie, and nobody asking how to make the pie bigger. I wrote the outline one evening at my gym in Paisley, on my phone between exercises, because I couldn’t get the subject out of my head.

This essay is my attempt to explain where government money actually comes from and how the UK might get more of it. I work through the four sources of government income, trace how money cascades through the different tiers from Westminster down to local authorities, and then set out six strategies for growing the overall supply. I also examine the risks that could significantly reduce the money available, from cyberattacks and energy shocks to demographic decline and a loss of investor confidence in UK government bonds.

This is not an essay about balancing the budget. That conversation is already happening elsewhere. This is about the less discussed question: where does the money come from, and what does it take to grow it? My perspective is shaped by 25 years of economic development consulting across the UK and Africa, and by the lived experience of emigrating from a country where these are all very real problems.

In the middle of 2025, facing a career at a standstill and doors closed on all sides, I reached a place of despair and decided to reinvent myself and train as a cybersecurity professional. Over the following months, I completed two qualifications and was well into a third before a family health crisis and an honest conversation with a career counsellor brought me back to my senses.

This essay is my attempt to make sense of that detour. It is not a technical guide, though it contains practical advice. It is an honest account of what motivated a strategy consultant to pivot towards cybersecurity, why that pivot was ultimately misguided, and what I learned along the way that has genuinely stayed with me.

The 10 lessons I describe cover the cybersecurity threat landscape, human vulnerability, online privacy, backups, passwords, safe browsing, external standards, phishing, home network security and the growing role of AI. They are written for anyone who wants to adopt a cybersecurity mindset and implement some practical basics.

Over dinner with some young friends, the conversation turned to a question that has been nagging at me: who will mentor the next generation of professionals if their managers are all using AIs to do the work that junior staff once did?

This essay reflects on the mentors who shaped my career and the younger people I’ve had the privilege of mentoring in return. It explores the types of professional mentorship I received and the contexts where this took place. I also highlight why the consulting model that underpinned my career for decades depends on a two-way exchange between humans – something that AI cannot replicate.

I don’t have answers, but I’m convinced this is one of the more significant and underappreciated consequences of AI in the workplace. I believe it will affect all of us

I wrote this essay over a one-week frenzy in early 2026, in early morning sessions before work and at my local cafe in the afternoons, and in the evenings. Energy policy isn’t my professional speciality, but having lived through almost a decade of scheduled blackouts in South Africa, and paying for expensive energy in the UK, I’ve been paying close attention to how the UK manages its energy.

What follows is an attempt to think through UK energy policy as a systems thinker and strategic-minded observer rather than as a technical expert. I explore the full environmental cost of renewable energy across the entire value chain, the geopolitical risks of depending on China and Russia for critical minerals, why UK energy prices are so high and what drives them, the case for significantly more nuclear power, and why community and state ownership of energy infrastructure matters. I also draw on comparisons with South Africa, France, Norway and South Korea throughout.

This is my honest assessment of the UK’s energy policy and where it needs to invest aggressively before it is too late.

I can’t stand AI writing anymore. I immediately skip over any blog post, LinkedIn post or Substack articles that appears to be written or illustrated by AI. My resolve is much greater if the post shouts, “Look at me. See how clever, wise, successful or virtuous I am.” I quickly skip past these. My strict reading filters no doubt produce false positives, but that’s a risk I’m prepared to take.

This type of AI writing is easy to recognise. There are so many clues. Once it’s seen, it can’t be unseen.

My view is that if I want to read deeply human insights, then I’m going to prioritise those written by humans without the assistance of AI. I’m going to accept the human flaws, knowing that I’ve read something entirely human-made. But if I’m after technical or academic knowledge, then I’ll use AI myself to extract and package that knowledge first-hand. This polarised approach works well for me.