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Friends,
Something has shifted. You can feel it even if you can’t name it yet. The person you needed to be twenty years ago and the person you need to be now are different people. And the person your kids will need to be in ten years is different again, in ways that most schools, most companies, and most parents have barely started to reckon with.
Twenty-five years ago, on February 19th, 2001, a worker at an abattoir in Essex, in the UK, noticed some pigs in distress. He called the local vet. The vet suspected “foot and mouth” disease, a condition that hadn’t been seen on British soil in thirty-four years.
What nobody knew was that the virus had already been incubating silently across at least fifty-seven farms. By the time the first case was confirmed, the disease had spread through livestock markets, riding on the hooves of animals that had been shipped across the country. Over the next eight months, more than six million animals were slaughtered. The pyres burned across Cumbria, Devon, and the Welsh hills. The cost to the British economy was eight billion pounds. Tourism collapsed. The general election was delayed. Farmers who had never encountered the disease had no protocols, no muscle memory, no instinct for what to do. A government inquiry later found that contingency plans had been built for the most likely scenario and had assumed no more than ten infected premises at any one time.
There is a word in British farming that most people outside the industry have never heard. Hefting. When livestock are kept on the same land for generations, they develop a deep knowledge of the terrain: the safe paths, the sheltered ground, the rhythms of a particular place. It cannot be taught. It can only be felt and learned, one season at a time, passed from older animals to younger ones over years. When the culls came in 2001, farmers lost more than animals. They lost decades of hefted intelligence that could never be replaced by simply restocking a field.
The lesson that still echoes, twenty-five years on, is this: by the time you can see the problem clearly, it has already spread further than you think. And the systems you assumed would protect you were designed for a smaller crisis.
When I saw the anniversary story of foot and mouth, I see the analogy of AI transformation unfolding. Not because AI is a disease, but because the pattern of invisible, compounding spread is eerily similar. By the time most organisations started paying attention to generative AI, it was already inside their workflows, carried there by employees who had started using it quietly, the way infected animals were moved through markets before anyone knew what was happening.
Microsoft and LinkedIn reported in 2024 that 75 per cent of knowledge workers used AI at work, and 78 per cent brought their own tools because their employers hadn’t caught up. The virus, if you want to call it that, had already moved through fifty-seven farms.
There is a pattern here that deserves a name. Call it algorithmic drift: the slow, imperceptible process by which systems start making choices on your behalf so smoothly that you stop noticing you have stopped making them yourself.
The instinct, when the ground shifts this fast, is to wait and see. To let others go first. To watch the early adopters and decide later.
The foot and mouth inquiry had something to say about that instinct. It found that the single greatest factor in the scale of the disaster was delay. The disease moved at the speed of a livestock market. The response moved at the speed of a bureaucracy. Every day between infection and action, the problem doubled. The farmers who acted fastest, who isolated their herds before the official orders came, lost the least. The ones who waited for instructions, who trusted the system to tell them when to move, were the ones who watched their animals burn.
Waiting for clarity is not caution. It is a decision to let the problem compound while you stand still. And in a crisis that moves faster than your institutions, standing still is the most expensive thing you can do.
This is what I think most commentary gets wrong.
We call people who resist technology “Luddites,” and we mean it as an insult. We picture them as frightened, backward, clinging to a world that has passed. It is one of the most durable misunderstandings in the English language.
The original Luddites were not afraid of machines. They were some of the most skilled textile workers in England. Croppers, weavers, stocking-makers who had spent seven years in apprenticeships earning their craft. They knew machines intimately. Many were skilled operators themselves.
What they opposed was a specific thing: factory owners using new technology to replace skilled work with cheap, unskilled labour, and in doing so destroying the quality of the output and the dignity of the worker. They tried to negotiate first. They proposed minimum wages, taxes on goods to fund displaced workers’ pensions, a more gradual transition that would allow people to learn new skills. Their proposals were rejected. Only then did they start breaking frames.
We remember them as anti-technology. They were actually pro-quality, pro-skill, pro-agency. They were fighting for the right to be good at something in a world that had decided good enough was cheaper.
That fight sounds familiar, doesn’t it?
Because the question at the heart of the AI era is the same one the Luddites were asking two centuries ago: when a new technology makes output cheaper and faster, who decides what happens to the quality and the people? Do the workers get to shape the transition, or does it happen to them?
The Luddites feared they would be forced to stop using their skills. Two hundred years later, our danger is different. We are volunteering to forget them.
The research bears this out, and it is more unsettling than the commentary suggests.
AI makes you faster. That part is real. Studies across customer support, writing, and software engineering all show the same pattern: generative AI cuts the time, and the biggest gains go to the least experienced workers. A young new employee with the right tool can look mid-level on a Tuesday. AI compresses visible differences in skill the way a good suit compresses visible differences in status. It works, until someone asks you to do the job without it.
And this is where it gets uncomfortable. A meta-analysis in Nature Human Behaviour examined 106 experiments on human-AI collaboration and found that, on average, the combination performed worse than whichever was best alone. Human plus AI was worse than either working independently. The failures clustered around decision tasks: the very tasks where judgment, accountability, and human skill matter most. A confident machine proposing the wrong answer pulls a tired human towards it. Researchers call it automation bias. In practice, it looks like a bad decision with excellent formatting.
The aviation industry learned this the hard way. In 2009, Air France Flight 447 fell into the Atlantic, killing all 228 people on board. The captain was on a rest break. The two pilots left in the cockpit, one of them relatively junior, had grown so accustomed to the autopilot that when it disconnected at 35,000 feet, they could not recognise a basic aerodynamic stall. Air France later admitted to a widespread erosion of manual flying skills among its long-haul crews. The autopilot was so reliable that nobody noticed the human competence underneath it had quietly disappeared.
The aviation writer William Langewiesche, who investigated the crash for Vanity Fair, captured the paradox: the more reliable the automation, the less capable the human operator when it fails. And the rarer those failures become, the harder it is to stay ready.
Newer studies on AI show the same dynamic in knowledge work. Leaning on AI for judgment-heavy tasks can stunt the development of the very skills you need to use it well. One experiment found that generative AI raised performance while simultaneously reducing intrinsic motivation. People did more. They cared less about how.
So what rises when output gets cheap?
The World Economic Forum’s list of the skills rising fastest answers the question directly: analytical thinking, creative thinking, resilience, leadership, self-awareness, empathy.
Prompt engineering is nowhere on that list.
What is rising is everything that involves judgment, trust, accountability, and the ability to work with other people through ambiguity. I have come to think of these as SuperSkills. And you have already met them in this piece, wearing different clothes.
The Luddite croppers who spent seven years in apprenticeships, building mastery one loom at a time. They were not born skilled. They earned it through the accumulated weight of showing up and paying attention, season after season. The same way a herd hefts to its land. And when the time came to fight, they did not smash machines out of ignorance. They proposed minimum wages, transition plans, taxes to fund displaced workers’ pensions. They insisted that progress should not come at the cost of human dignity. That argument did not win in 1812. It has not gone away.
The farming families who survived 2001 best were the ones who had already diversified. A third of farming households had income from tourism, haulage, or contracting alongside their livestock. When the movement ban hit, the families with the broadest base recovered fastest. The ones who had defined themselves entirely by one activity were the most devastated. There is a lesson in that about the discipline of building yourself wider than your current role, so that when one field is closed, you are not standing in the only one you know.
The hefted herds themselves knew more than one path across the fell. They knew the whole terrain: the safe ground, the sheltered spots, the places where the weather turns. That knowledge was not about any single task. It was a map of the entire system, built over generations. AI can generate options. Only a mind that holds the full picture can decide which ones matter.
When the crisis hit Cumbria, it was the vets, the neighbours, the local radio stations, and the farming families leaning on each other who held the community together. The formal systems were overwhelmed. What remained was people showing up for each other when the institutions could not. One farmer’s wife wrote in her diary that no nursing visit during that period was simple, that every house she entered was carrying grief just below the surface. That kind of human trust does not scale. It does not automate. And it is the thing that holds when everything else fails.
The virus itself had arrived from the other side of the world. The Pan-Asian strain originated in India in 1990, crossed a dozen countries in a decade, and reached Essex through illegally imported meat. You might assume that Britain, with its centuries of global reach, would have been the country best prepared for a threat that crossed borders. It was not. When the same disease hit the Netherlands weeks later, Dutch veterinary teams contained it in a month. They used ring vaccination, a strategy adapted from their recent experience fighting swine fever, deployed through EU coordination frameworks that allowed them to move expertise and resources across borders quickly. Britain, which had not seen foot and mouth since 1967, had no such muscle memory and no such network. Its plan was built for a local crisis in a world that was already global. Not every country needed every capability. But the ones that could draw on experience from different contexts, different crises, and different ways of thinking were the ones that adapted fastest when the ground shifted beneath them.
And the pilots of Flight 447, in the minutes before the aircraft hit the Atlantic. They had the best automation in commercial aviation. They had years of training. What they lacked was the practiced instinct for where the machine ends and the human begins. The people who will stand out in the AI era will not be the ones who use it most. They will be the ones who never forgot how to fly without it.
Recently, I have been writing longer pieces than I usually do. They need to be.
I am not writing this for your next productivity hack. I am writing it because who we need to be has changed, profoundly, in the last few years. Generative AI is releasing us from the shackles of process and routine that used to define professional life. And that release sounds like freedom until you realise the shackles were also the scaffolding. They were the reps. The struggle. The thing that built your competence without you noticing. The friction. It’s my favourite word these days.
The scaffolding is being removed. The question is what you have built underneath it.
I was young when foot and mouth happened. I didn’t understand what it was. I didn’t even know why it was called that. I couldn’t follow the science or the policy debates. But I remember that meat became expensive, and sometimes you couldn’t get it at all. I felt the consequences of something I couldn’t explain.
I think about that when I watch people encounter AI for the first time. Most of them can’t articulate exactly what is changing or why. But they can feel the price shifting around them. The cost of producing a draft has collapsed. The cost of judgment, taste, trust, and human connection is rising. Something significant is happening, and you don’t need to understand the virology to know you’re affected.
If you have kids, you feel it twice. They are growing up in a world where autopilot is the default, where the path of least resistance is to let systems think for you, draft for you, decide for you. The word for what gets lost in that process is agency. And agency, once surrendered quietly, is not easily reclaimed. The most important thing you can teach them is not how to use AI. It is how to remain the kind of person who can function when the AI stops. Curiosity. Adaptability. Empathy. Judgment. The willingness to sit with difficulty instead of outsourcing it.
That willingness is not a personality trait. It is hefted. It is built one season at a time, through years of doing the work on the same ground, learning the terrain by walking it, not by having it described to you. And like the herds that were lost in 2001, once it is gone, you cannot simply restock.
The autopilot is very good. Fly the plane anyway.
Stay Curious - and don’t forget to be amazing,
PS. If your organisation is grappling with how AI is reshaping work and leadership, I speak and advise on this.
Rahim Hirji Author, SuperSkills (2026) | Keynote Speaker | Advisor
Building human capability for the AI era.
Tools I Use:
Jamie: AI Note taker without a bot. You join the meeting. The Bot doesnt.
Wispr Flow: Just dictate everything to your laptop and phone. Game Changer
Refind: AI-curated Brain Food delivered daily. Pick your intelligence.
Meco: Newsletter reader outside your inbox. Organise your intelligence.
Prompt Cowboy: Prompt Generator. Extract intelligence.
Manus: Best AI agent to do things for you. Agentise your intelligence.
Chat Hub: Multi-model intelligence
SuperSkills Intelligence: Ramp up your human intelligence
Recommend Reading:
Now
Before Kids Learn to Think, They’re Learning to Prompt - What does AI mean for kids? Recommend this piece which goes beyond the regular - are we getting dumb because of AI. as it enters classrooms and homes, the real risk isn’t misinformation but the quiet erosion of developing thinking skills. Oh and BTW: Bosses are firing Gen Z grads just months after hiring them—here’s what they say needs to change
THE 2028 GLOBAL INTELLIGENCE CRISIS: A Thought Exercise in Financial History, from the Future. This was the research paper from Citrini Research that sent markets into disarray this week. I’ve given my summary and take, but you can also read the full piece.
What AI Executives Tell Their Own Kids About the Jobs of the Future: Anthropic’s Daniela Amodei and other AI luminaries about what they advise their own children on education and careers in an AI-driven world. Also, a page from a book predicting the end of jobs, career by career is going viral.
You have about 24 months left before your skills expire But what happens in 24 months isn’t a total collapse of the economy and everything we know. What happens isn’t that robots will do all manual labor and AI bots will do every office worker job there is. This is a doomer’s view of the world. What happens in 24 months is that whatever career you have right now WILL be disrupted. The BS work will be gone. Automation will replace admin. Low-level jobs will mostly be nonexistent. But this doesn’t create mass unemployment and force some dystopian view of the world to become the new norm. No, it’s far simpler than that. AI will force every one of us to be high agency by default.
How to prepare for the next decade: A guide to preparing for the most destabilizing chapter in human history. MUST READ and then when you have finished, watch this 1 minute clip
Next
Agents of Chaos: researchers gave AI agents real email accounts, Discord servers, file systems, and shell access with admin privileges. Built on OpenClaw, the open-source framework already being used for personal AI assistants.
The Country That’s Madly in Love With AI - Who’s afraid of AI? Not South Korea.
Trump orders government to stop using Anthropic in battle over AI use. According to Zoe Kleinman: “Whether Amodei is genuinely about to become the patron saint of AI ethics or whether there’s another game plan behind it remains to be seen but what’s unfolding is an unusual and very public fracture in the US government-big tech united front. I wonder what China makes of it all”
Tomorrow’s Smart Pills Will Deliver Drugs and Take Biopsies - Ingestible electronics can sense and act inside the gut
Jack Dorsey’s Block to Lay Off 40% of Its Workforce in AI Remake - Parent of Square and Cash App says intelligence tools have changed how to run a company
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Hefting may be my new favorite word. I think half the colleagues I work with are valuable for their ability to heft across the corporate landscape. Unfortunately, AI may crack the ground beneath us making lots of that less valuable. The catch is that it takes a forward thinking leader to implement it for that to happen and we don’t have much to worry about in that department.
The foot and mouth analogy reminds me of the articles I’d been reading about doctors struggling to treat diseases that had previously been eradicated in America like measles now that they’re rising again in this anti-vax world. I think you’re onto something when it comes to keeping the brain sharp just as we still go for a job when we could drive anywhere faster. Gotta keep yourself sharp enough to take advantage of the tools.
Thanks for sharing this!