martin // dower

In the 80s and 90s, there was a pretty clear upgrade path if you were “one of the bright ones”.

You did well at school, maybe went to uni, learned to string a sentence together or solve a spreadsheet, and you were basically set. Not rich, but upwardly mobile. A professional. The sort of person who could get a mortgage, buy a Golf GTI, and tell their kids, “Work hard and you’ll do better than us.”

The assumption was simple: If you were smart and you could work with ideas instead of a shovel, the economy would look after you.

That was the deal. Especially in places like London. Every new wave of “bright young things” – grads, junior consultants, copywriters, analysts, planners – pitched up in the city, sold their brains, and climbed.

Fast-forward to now, and that deal is quietly collapsing.

The same “cognitive class” that’s done well out of the last 50 years – traditional middle-class knowledge workers – are suddenly standing on thinner ice. Wages are flat, careers are choppy, everything looks like a gig, and a lot of that precious cognitive work is being gobbled up by machines that just don’t get tired.

And that’s one of AI’s nastier, unintended consequences:

It’s not just automating low-level jobs. It’s hollowing out the rungs of the cognitive ladder that used to make the middle class feel safe.

Who are we talking about?

When I say “cognitive class”, I mean:

   •   The grads who went into media, marketing, consulting, law, finance, comms, design, policy.

   •   The office-based professions that live on PowerPoints, Google Docs, Slack channels, and Zoom.

   •   The “bright young things” who were always told they were destined for “good jobs”.

In other words: the people whose main asset is their ability to:

   •   process information,

   •   write and speak clearly,

   •   analyse,

   •   plan,

   •   persuade.

For the last few decades, this has been a great place to be. The world shifted from heavy industry to services, from factories to offices, from brawn to brains. If you could think, present, and bullshit in a convincing way, you were golden.

There was even a kind of moral story attached to it: “We deserve this. We studied. We worked late. We learned Excel. We’re the ones making the hard decisions.”

Then along comes AI and, with a straight face, basically says:

“That thing you get paid £250 a day for? I can do the first 90% in about four seconds.”

Awkward.

The invisible bargain that’s breaking

For my generation – Thatcher kids who got out – the cognitive bargain went like this:

1. You invest heavily in education. Time, money, emotionally. Maybe you take on big debt.

2. You get access to higher-paying, more secure jobs. They might be dull, but they’re safe-ish. Career ladders, pensions, stability.

3. You convert that into a middle-class life. House, kids, holidays somewhere sunny, maybe a German car on the drive.

Except, now AI comes in at Stage 2 (or maybe earlier) and quietly wrecks the economics.

Because if you’re a company looking at your P&L, the logic is brutal:

   •   Why hire 5 junior analysts when 1 mid-level with AI tools can do similar output?

   •   Why pay copywriters, designers, planners full-time when you can externalise risk to a gig pool and plug them into AI?

   •   Why invest in grad programmes when you can wait and buy mid-levels later – after the market has chewed them up a bit?

The result isn’t some sudden robot takeover. It’s something slower, nastier, and harder to protest:

The early rungs on the professional ladder get thinner, more precarious, and worse paid – just as the price of entry (degrees, debt, living costs) has gone up.

Gutting from the middle, not just the bottom

We had this comforting idea that technology automates the boring low-end work and humans just “move up the value chain”.

The problem with AI is that a lot of “value chain” work is… typing, researching, and shuffling information around. Exactly the stuff junior and mid-level knowledge workers do all day. And AI is also racing up the value chain.

Watch what’s happening in real time:

   •   In marketing and media

The £35k copywriter, social manager, or junior planner now competes with tools that can spit out 20 variants in minutes - all sense-checked and with the correct tone of voice. You still need humans – but fewer, and more senior.

   •   In consulting and strategy

Decks that used to take a week of analyst graft can be templated and partially generated. Fewer spreadsheet monkeys, more “partner” types who sell and frame the work.

   •   In design and content production

AI tools are churning out first passes for logos, layouts, video edits, transcriptions. The grunt work that trained juniors is being eaten from underneath.

What does that do?

   •   It compresses the middle – junior and mid roles – and inflates the extremes: a handful of high-paid stars at the top, and a sprawling mass of freelancers, contractors, and gig workers at the bottom.

   •   It turns “learning years” into “fighting for scraps” years. The grind that taught you the craft becomes a scramble to keep your day rate above your rent.

Flat wages, fake freedom, and the gig illusion

Outwardly, this is sold as liberation:

   •   “You’re a consultant now, not an employee.”

   •   “Portfolio career.”

   •   “Be your own boss!”

In reality:

   •   You’re juggling three clients, two overdrafts, and one landlord.

   •   You have no benefits, no sick pay, no pension, and an algorithm somewhere deciding whether you get the next job.

   •   You’re in “the creative industries” but you can’t afford a flat anywhere near the city that houses them.

AI amplifies this because it:

   •   Commoditises a lot of cognitive work (there’s always someone who’ll do it cheaper, faster, or semi-automated).

   •   Obscures the human contribution (clients see the output, not the juggling behind it).

   •   Erodes pricing power (if your client thinks “a bot could do this”, your negotiating position is already weaker).

We’ve turned a whole swathe of previously decent jobs into a kind of white-collar zero-hours economy. Same laptop. Same coffee shop. Same “I work in digital”. Very different level of security.

Debt on the way in, insecurity on the way out

Here’s the cruel bit.

We’ve told an entire generation:

“Borrow tens of thousands for a degree, move to an expensive city, grind hard in your 20s – and it’ll pay off long-term.”

That made sense when:

   •   There were stable jobs at the end of it.

   •   Wage growth roughly tracked experience and inflation.

   •   You were actually accumulating some kind of social and financial capital.

Now:

   •   Degrees are more expensive.

   •   Rents in London (and other hubs) are insane.

   •   And the jobs at the end are less secure and more easily automated.

So you get:

   •   A big cognitive class with fragile finances.

   •   People delaying kids, homes, and long-term commitments because their work lives feel like a treadmill on ice.

   •   A simmering sense of “I did everything right – why do I still feel shafted?”

If you want a breeding ground for resentment and political volatility, that’s it. Not the very poorest – they’ve always been shafted. The people just above them, who were told they were joining the winners’ club, only to find the bar’s been moved.

The emotional gutting: status anxiety at scale

The economic hit is one thing. The psychological hit is worse.

For the cognitive class, work isn’t just money. It’s identity.

   •   “I’m a strategist.”

   •   “I’m a lawyer.”

   •   “I’m a journalist.”

   •   “I’m a designer.”

If a machine can do a large chunk of what you do – or at least what you thought made you special – it’s not just your income on the line. It’s your story about yourself.

You see this already:

   •   People loudly proclaiming AI is “just a toy” or “only good for basic stuff” while clearly being rattled.

   •   Professionals more invested in defending the purity of their craft than in evolving it.

   •   A rising hum of anxiety: “What if my job is just pattern-matching with a nicer haircut?”

That’s what “gutting the cognitive class” really looks like:

   •   Less like robots marching in, more like a slow, steady hollowing out of confidence, status, and security.

Is there any way this doesn’t end in a clusterfuck?

I’m not a doomer by default – I’m temperamentally optimistic. But optimism isn’t pretending the hit isn’t real. It’s asking: what can we do with this mess?

A few hard truths and possibilities:

1. The old deal is not coming back

The “study hard, get a degree, walk into a stable middle-class job” bargain is gone. That doesn’t mean all is lost; it means we have to stop lying about it.

Parents, schools, universities, governments – they’re still selling a story that belonged to the 1990s.

AI is just accelerating us all away.

2. The value of how you think goes up as the value of what you produce goes down As AI eats more of the production work, the premium shifts to:

   •   Framing problems.

   •   Asking better questions.

   •   Judgement, taste, ethics.

   •   Building trust and relationships.

   •   Being the person people want to work with, not just the person who can operate the tools.

The cognitive class will survive – but not by clinging to the idea that their worth lies in being better at manual analysis, drafting, or slide-making than a machine.

3. Ownership and leverage matter more than degrees

If you’re selling hours in a marketplace where AI can undercut you, you’ll get squeezed, nay, screwed.

If you:

   •   own the relationship with the client,

   •   own the product,

   •   own the distribution,

   •   or own the IP

…you’re in a different game.

One of AI’s unintended positive consequences is that more people could build and own things: products, mini-agencies, small but global businesses – if they stop thinking like employees and start thinking like small-scale capitalists.

Easier said than done, but still true.

4. We will need policy, not just hustle culture

I’m all for personal responsibility and seizing opportunity, but let’s not pretend the market will gracefully handle this on its own.

If we don’t want an angry, disillusioned cognitive class drifting into nihilism, we’re going to need:

   •   Smarter safety nets.

   •   Rethinking education (shorter, cheaper, more modular, more honest).

   •   Tax and regulatory frameworks that don’t just shovel more chips to the already loaded.

So where does that leave the “bright young things”?

If I were 19 today, turning up in London with a laptop and some brains, I’d be looking at AI and thinking two things at once:

1. “Shit, this could absolutely undercut me.”

2. “Also, this might be the only way I get out ahead.”

The cognitive class is being squeezed, yes. But that same squeeze is creating weird, messy, new spaces where the brave and slightly unhinged can build interesting lives:

   •   Tiny teams with massive leverage.

   •   Niche experts amplified by AI, not replaced by it.

   •   People using AI as an exoskeleton for their judgement, not as a crutch for lazy thinking.

The risk is real. The gutting is already underway.

But the story’s not finished. AI is hollowing out the old, comfy version of the cognitive class – the one that believed a degree and a job title was a lifetime safety blanket.

The unintended consequence is a shake-up that will hurt a lot of people and throw up new shapes of success that look nothing like the 9–5 office ladder. Thankfully.

The real divide in the next decade won’t be “educated vs uneducated”. It’ll be:

I grew up in a council house in Yorkshire in the 1970s. Money was tight, Britain felt knackered, and the general vibe was: don’t get ideas above your station. The grown-up script was simple: keep your head down, get a “safe” job, try not to annoy anyone important, and for god’s sake don’t dream too big.

At 19, I moved to London with a bag, a bit of attitude, and not a lot else.

That move wasn’t driven by evidence, school career-guidance (LOL), or five-year plans. It was pure, slightly delusional optimism: a belief that life could be bigger than the small patch of rural Yorkshire I started in. That there was more out there if I was willing to go and find it.

Looking back, that’s the pattern.

Over the long run, the optimists – the people who believe things can get better and act accordingly – build most of the future. The pessimists get to say “I told you so” on Twitter. The optimists get London, businesses, BMWs, Ducatis, and a life they actually define.

And that’s where I suggest AI comes in.

Because one of the biggest unintended consequences of AI is this: The gap between optimists and pessimists is about to blow wide open.

The upside is going to disproportionately flow to the people who run towards this stuff, not away from it.

Optimism isn’t a mood. It’s a strategy.

Let’s define terms. When I say “optimist”, I don’t mean the LinkedIn clown posting “Everything is awesome!” or the GramWhore sharing pictures of rented Ferraris while the world burns. I mean:

Someone who believes the future is influenceable – and behaves as if their actions matter.

Optimists:

• Move city.

• Change career.

• Learn new technology.

• Start things without a guarantee they’ll work.

Pessimists:

• Sit tight.

• Demand certainty.

• Wait for proof.

• Mostly experience the future as something that happens to them.

In tech and entrepreneurship, optimism is basically a cheat code - my cheat code. You:

• Take more asymmetrical bets (limited downside, uncapped upside).

• Give compounding time to work in your favour.

• Put yourself in the path of opportunity often enough that “luck” starts to look suspiciously like a pattern.

Is it risky? Of course. But here’s the thing: playing it safe is also a gamble – you’re betting the world will stay still. It never does.

A quick reality check: pessimists sound smart, optimists build stuff

If you read history with any honesty, it’s almost funny. Every major step forward – industrialisation, railways, electricity, the internet – came with a chorus of clever people explaining why it would all go wrong.

• Railways would destroy society. Travelling faster than 25mph was not humanly possible.

• Electricity would kill us all - even if we could find a use for it.

• The web was a fad. We prefer the real world.

• Smartphones would rot our brains. (Well maybe that’s played out as expected but as the attention-economy)

And the pessimists were often right about some things:

• Yes, there were accidents.

• Yes, there were abuses.

• Yes, some industries and jobs got wrecked.

But zoom out 25, 50, 100 years and the scoreboard isn’t subtle:

• Longer lives.

• Higher living standards.

• Massive growth in what “a normal life” can look like.

Meanwhile, the people who said “this could be huge” – and acted – were the ones who built companies, cities, careers, infrastructure and fortunes out of the mess.

The pessimists wrote op-eds and obits. The optimists laid track, strung wire, shipped code, and became the elite.

AI: the next great optimism filter

AI is the biggest optimism test we’ve had in decades.

On one side:

• “It’ll take all the jobs.”

• “It’ll kill creativity.”

• “It’s just hype.”

• “It’s too dangerous, we should slow it all down.”

On the other:

• “This is the biggest productivity jump since electrification.”

• “We can automate the boring stuff.”

• “We can build things that were impossible two years ago.”

• “We can give individuals superpowers once reserved for big companies.”

AI’s biggest unexpected consequence may be that it dramatically amplifies the rewards of being an optimist. I, as an eternal optimist, believe it to be true - I’m all in.

Because what is AI, really, at ground level?

• A massive force multiplier for skills.

• A leverage tool for small teams and solo operators.

• A way to go from idea → prototype → product faster than ever.

The pessimist looks at that and sees risk, disruption, loss.

The optimist looks at that and sees:

• “I can build a global product from my kitchen table.”

• “I can spin up content, prototypes, and experiments without begging for budget.”

• “I can compete with bigger players because my tools just levelled up.”

Same technology. Completely different outcomes.

The drag factor: how pessimists hold everyone back

Pessimists don’t just sit quietly in the corner, sadly. They actively slow things down, start podcasts, and write white papers.

They block, stall, and smother under three main banners:

1. “Safety”

• Not real safety – that’s important.

• The sort of vague “what if something bad happens?” that can be used to justify doing nothing for another five years.

2. “Stability”

• Translation: “We’re comfortable with the status quo, and we’re scared of losing our place in it.” Thanks boomer.

• This is where incumbents weaponise pessimism to kill competitors: “We must protect consumers from this scary new thing… that also threatens our profit margins.”

3. “Certainty”

• “Show me the guaranteed ROI, the perfect risk profile, the exact regulation, and then we might consider starting.”

• Spoiler: by the time that exists, the upside’s already gone.

This plays out at:

• Societal level: Over-cautious regulation, moral panics, blanket bans, endless “consultations” while others sprint ahead.

• Company level: Endless committees, “AI task forces” that produce PowerPoints instead of products, endless reasons not to ship. Abject fear of change and uniform ass-covering.

• Personal level: Smart people who spend more energy explaining why they can’t try something than it would take to just try it. The unconsciously incompetent isn’t the preserve of the masses.

The irony? Pessimists think they’re avoiding risk. In reality, they’re quietly compounding a different risk: falling so far behind they never catch up and slide rather too quickly into irrelevance.

When “unintended consequence” means huge upside

Ironically (for the pessimistic) some of the most interesting side-effects are massively positive – but for the right people.

Here are a few big ones for optimists:

1. The leverage explosion

A tiny team with the right AI stack can now:

• Design, build, market and ship products that used to require whole departments.

• Run business experiments at the speed of thought and at a scale never seen before..

• Offer services that are “enterprise-grade” without needing enterprise headcount.

Unintended consequence: The old correlation between size and power is breaking. Optimistic, hungry small players can now punch ridiculously above their weight.

2. The skill ceiling just moved

AI doesn’t just replace tasks; it extends what a single person can realistically do.

If you’re willing to learn and adapt:

• You can become a better writer, faster analyst, more capable marketer, stronger strategist, better partner, accomplished critical thinker, and more “attractive” to society on all levels.

• You can pick up “adjacent” skills you’d never formally train in: design, basic dev, data analysis, languages, trends, deep learning, decision processing, debating, and communicating ideas and positions.

Unintended consequence: People who lean in to AI can effectively “upgrade” themselves into a new league without going back to school or begging for permission. It’s a very real superpower to be amongst the most accomplished in every cognitive field on demand.

3. The geography penalty is shrinking

For someone like me, moving from Yorkshire to London was essential. That was where the action was. Today, AI (plus the internet in general) is erasing more of that location advantage:

• Talent from anywhere can access world-class tools.

• You can access global markets without leaving your living room.

• The ideas and execution matter more than the postcode.

Unintended consequence: AI is a quiet engine of social mobility – but only for those who believe it can be, and behave accordingly.

“But don’t we need pessimists?” – yes, as brakes, not drivers

Let’s be fair. If the world were run exclusively by glass-eyed optimists, we’d have:

• More bubbles.

• More scams.

• More “move fast and break things (and people)” disasters.

Pessimists – or at least sceptics – play a crucial role:

• They force us to think about failure modes.

• They push for guardrails, standards, and accountability.

• They ask “what if this goes wrong?” – which is a good question if it doesn’t become the only question.

So the goal isn’t to eliminate pessimism.

You want optimists driving the car, and pessimists in charge of the crash tests and safety rails.

What you don’t want is pessimists standing in front of the car insisting we’d all be better off riding horses or walking.

How to be a useful optimist about AI

If you’re still reading this, I’m guessing you lean optimistic already. Good.

Here’s how to channel that in a way that actually works:

1. Assume AI is a big deal.

Don’t waste time arguing about whether it’s “hype” or “real”. It’s already reshaping markets. The only interesting question is: how do you want to participate?

2. Start small, move fast. But do it now.

• Use AI to save time on the boring stuff.

• Run more experiments instead of over-thinking the perfect one.

• Learn by doing. The people playing with this every day will outrun the think-piece brigade. Playing for playing sake is good.

3. Be greedy for upside, paranoid about harm.

• Capture the leverage AI gives you.

• Be ruthless about where it could backfire – for you, your customers, your team, your life, your mental health.

• Optimism doesn’t mean ignoring downside; it means believing you can manage it.

4. Don’t wait for permission. Ever.

• Most organisations will be slow. Most regulators will be slower.

• The optimistic move is to build, learn, and adapt within reasonable ethical lines – not sit there waiting for a perfect rulebook to arrive.

Final thought

In my lifetime I’ve watched optimism rocket people – including me – out of tiny, constrained lives and local maximums and into something wildly bigger, exciting, and fulfilling.

From a council house in Yorkshire to running a digital agency, racing cars, riding Italian superbikes, living in a world where I carry a supercomputer in my pocket and talk to an AI about all this… none of that happened because I was “realistic” about my chances. I believed.

The pessimists will continue to do their thing. They’ll warn, stall, demand certainty, and insist we slow down.

And in the long run, they’ll lose – again. The optimists always win in the long term. AI is simply raising the stakes: the cost of sitting this one out is higher, and the upside of leaning in is bigger.

Autocracy used to rely on boots, batons, and prisons. Now it runs on GPUs, data centres, and recommender systems. AI doesn’t just help autocrats – it cuts their operating costs.

The stuff that used to be expensive and risky – spying on people, censoring conversation, flooding the infosphere with propaganda, predicting unrest – is being automated.

When the marginal cost of repression drops towards zero, you don’t just get more autocracy; you get different autocracy: lighter touch, more data-driven, more exportable, and harder for citizens (and democracies) to see coming.

Surveillance: from informants to inference

Old world:

• You needed big internal security apparatuses: informants, secret police, physical files, wiretaps. High labour, high risk, lots of leaks.

AI world:

• Facial recognition + ubiquitous CCTV + big data platforms + digital Ids = scalable tracking with fewer humans.

• In China, AI-powered systems fuse CCTV, telecoms, and online data to track people in real time, with facial recognition linked to national ID and behavioural analytics flagging “abnormal” patterns. 

Costs that fall:

• Personnel (fewer human watchers per citizen)

• Discovery risk (surveillance is ambient, invisible, and retroactive)

• Time (you can analyse past behaviour at scale, not just watch live)

Once you’re logging every face, every phone, every transaction, repression becomes a data problem, not a manpower problem.

Censorship: from red pens to recommendation algorithms

Old world:

• Literal censors. Lists of banned books, blocked newspapers, confiscated leaflets.

• Crude internet blocks: whole sites banned, keyword filters that everyone could see and dodge.

AI world:

• NLP models scanning social media, private chats, memes, minority languages.

• Algorithmic repression: content isn’t banned, it’s quietly buried, throttled, or redirected. 

Costs that fall:

• Visibility cost (no big political backlash from obvious bans)

• Cognitive load (systems continuously learn which topics/phrases predict dissent)

• Error cost (can pre-flag content before it goes viral)

This is censorship by thermostat: always on, small adjustments, nobody sees the hand on the dial.

Propaganda and disinformation at scale

Old world:

• State TV, controlled newspapers, crude slogans.

• Expensive to reach external audiences. Clunky, often low-quality.

AI world:

• Generative models that can produce endless plausible articles, videos, fake accounts, and deepfakes.

• Research shows AI greatly increases the volume and tailoring of disinformation and microtargeted political messaging. 

• Recent cases: sanctions on Russian and Iranian groups for AI-driven US election disinfo; AI videos used by Russia and others to erode support for Ukraine. 

Costs that fall:

• Content creation (bots and models do the grunt work)

• Localisation (multi-language, culturally tweaked narratives)

• Plausible deniability (attribution becomes harder, so the political cost of getting caught drops)

Autocrats used to print posters. Now they run content farms powered by large language models.

Bureaucracy & “frictional” control

A lot of authoritarian control is boring admin: permits, fines, tax audits, id checks, licensing, ‘random’ checks.

AI’s role:

• Predictive policing, credit scoring, social credit systems, risk scores for activists. Minority Report anyone?

• AI decision systems help decide who gets a loan, a contract, a passport, a university place – quietly punishing the politically, socially, or economically awkward. 

Costs that fall:

• Need for overt violence (you can rule through digital paperwork and risk scores)

• Visibility (it looks like “risk management”, not repression)

• Discretion overhead (officialdom get algorithmic guidance on who to hassle)

Repression stops looking like a midnight knock on the door and starts looking like a mysteriously rejected loan application.

Second-order consequences (the interesting bit)

This is where the “unintended consequences” theme really bites.

Autocracy-as-a-service

• Once AI tools exist, they can be exported: surveillance platforms, censorship suites, turnkey “public security” systems.

• AP reporting shows Western tech has already been embedded in China’s surveillance state, which is then exported to other regimes – effectively shipping a template for automated autocracy. 

• Lower upfront cost + off-the-shelf software = smaller, poorer regimes can run a “lite” version of China’s system.

Think SaaS (or PaaS), but for repression: plug in your cameras, your telecom data, your social feeds, your norms – we’ll handle the rest.

More stable mediocrity, less dramatic collapse

• Cheaper, subtler control lets mediocre regimes limp on for longer without either reforming or blowing up.

• Dissent is throttled early and often, not just at crisis points.

• That means fewer “big” moments of revolution – and more chronic stagnation.

Democracies start borrowing the playbook

• “Smart policing”, “content moderation”, “online safety”: democratic governments are already dabbling in AI tools that look suspiciously like softer versions of authoritarian tech. 

• Once the infrastructure exists, the line between “safety” and “control” is basically a political mood swing or perception of an existential threat (Trump’s trumped-up national emergency).

The technology doesn’t know whether it’s protecting democracy or strangling it – it just optimises for whatever goal you feed it.

Not all one-sided: how AI raises some costs for autocrats

To keep this neutral there are “complications” that arise.

• Data overload: more data than the regime can meaningfully use; false positives swamp real signals. Some research shows more surveillance can become counterproductive as citizens adapt and AI learns from skewed data. 

• Model brittleness: adversarial attacks, evasion tactics, spoofing cameras, confusing facial recognition, poor implementation.

• Legitimacy risk: once citizens learn that everything is nudged and curated, trust in any official narrative collapses.

• Arms race: activists are starting to use AI too – for secure comms, messaging, and counter-propaganda.

3 Years, One AI Brain, and a Very Strange Future

In November 2022 I opened a browser, typed a slightly sceptical prompt into this new thing called ChatGPT, and thought:

“Alright then, clever clogs. Let’s see what you can actually do.”

At first it was just a content helper. A slightly over-eager intern with infinite energy and no sense of when to shut up. I used it to tidy up copy, brainstorm headlines, draft messaging – the kind of stuff I’d normally bang out myself with a beer and a deadline.

It wasn’t perfect. It hallucinated, waffled, got things wrong. But it was… useful. And, more importantly, it got better. Fast.

And so did I.

From curiosity to core workflow

I’m a 1965 model. I grew up in Thatcher’s Britain, coded in the 80s, moved to London at 19, built companies, raced cars, did the whole “slightly awkward entrepreneur” thing. I’ve seen a lot of tech hype cycles come and go.

This one is different – and I only really understood that by living with it, every day, for three years.

The journey roughly went like this:

Phase 1: Toy

“Let’s see if this can help me write a better email / blog / client proposal.”

Phase 2: Tool

“Okay, this speeds me up. I’ll use it for content, messaging, research, outlines, meeting prep.”

Phase 3: Teammate

“This thing now sits across my whole workflow. Strategy docs, campaign architecture, customer journeys, board decks – it’s in the room for all of it.”

Phase 4: Second brain

Custom GPTs arrive and suddenly it’s not just an AI, it’s my AI – tuned to how I think and what I care about.

Now, in late 2025, I’m basically running an AI-augmented life.

Custom GPTs everywhere

Today I have a small army of custom GPTs embedded into pretty much everything I do:

• In my role as CEO at Connected, I use them for deep business strategy, positioning, and planning. They help me pressure-test moves, simulate scenarios, and translate half-baked ideas into coherent plans.

• For clients, they’re part of how we build unique digital propositions, marketing systems, and growth engines. Not “templates” – truly tailored, data-informed thinking, faster than any team I’ve had before.

• For decision support, they sit on my shoulder when I’m thinking about multi-million pound investment decisions, risk, cashflow, or portfolio allocation. They don’t replace judgement – they make it sharper.

• At home, they help plan trips, structure long weekends, benchmark hotels, map routes.

• They’ve helped design a new kitchen, model different layouts, play with aesthetics, and sanity-check quotes.

• My smart home setup – from heating to security to AV – is stitched together with AI planning the logic, integrations, and automation.

• They assist in everything from fitness and diet planning to drafting complex emails I don’t want to screw up.

If my 25-year-old self could see this, he’d think I’d hired a small private staff – researchers, analysts, planners, designers, travel agents, and a slightly neurotic PA.

In reality, it’s one underlying technology, expressed through different custom interfaces, all wired into how I think and work.

I call it my AI brain.

Not because it’s smarter than me, but because it extends what my actual brain can manage on its own: more context, more optionality, more iteration, more breadth, more depth.

Living with the future before it’s evenly distributed

When you live like this every day, for years, your view of AI stops being abstract. It’s not “maybe this will change things one day.”

It’s “this has already changed how I think, work, decide, and design my life.”

You start to see where this is going with uncomfortable clarity:

• Every knowledge worker will have an AI brain – or be outcompeted by someone who does.

• Every business will either be AI-native or quietly slide into irrelevance.

• Every big decision – personal or professional – will be made with an invisible AI committee in the background, running scenarios and prompting alternatives.

And that’s just the warm-up.

I’m increasingly convinced this will be more transformative than the industrial revolution.

The industrial revolution mechanised muscle and factories. This revolution is mechanising thought work and decision-making.

We’re not just changing how we move goods around. We’re changing how we move ideas, power, and agency around.

Same way steam, electricity and railways rewired society, AI is going to rewrite who gets to participate, who gets left behind, and what “being capable” even means.

Why unintended consequences?

Most of the public conversation about AI swings between two equally boring poles:

• The hype merchants: “It’s all amazing, don’t worry, the market will sort it out.”

• The doom merchants: “It’s all terrible, we’re doomed, pull the plug.”

Neither camp is much use if you actually want to understand what’s happening – or make intelligent moves in the middle of it.

Living up close with this tech – in my business and in my life – you start to notice the second-order effects:

• Autocracy gets cheaper to run.

• Optimists get disproportionately rewarded.

• The cognitive middle class gets quietly gutted.

• Regulation, power, creativity, inequality – all start to shift in weird, non-obvious ways.

That’s what this series, “Unintended AI Consequences”, is about.

Not the obvious headlines.

Not the PR decks from the vendors.

Not the sci-fi apocalypse.

Instead, I want to poke at the nuanced outcomes:

• Where AI is bending politics, markets, and social mobility in directions nobody really planned.

• Where the side-effects – good and bad – are more interesting than the sales pitch.

• Where my own three-year, lived-in relationship with this technology gives me a slightly clearer view than the tourists who log in once a week and pontificate on LinkedIn.

Where we’re going next

Over the coming pieces I’ll be digging into themes like:

• The lower cost of autocracy – how AI makes soft authoritarianism cheaper and more scalable.

• Why the optimists win – and how AI widens the gap between those who lean in and those who sit this out.

• Gutting the cognitive class – what happens when the “safe” knowledge jobs aren’t safe anymore.

And plenty more after that.

If AI really is the biggest shift since the industrial revolution – and I genuinely believe it is – then the least we can do is stop treating it like a novelty app and start treating it like what it is:

A new layer of reality that’s already rewiring how we think, work, love, build, invest, travel and live.

I’ve spent three years building with it, arguing with it, and letting it into parts of my life I never expected.

This series is my attempt to map out what that actually means – not just for me, but for anyone who plans on living through the next decade with their eyes open.

In 1983, while most of my peers were fretting over A-level coursework and cassette tapes, the world teetered terrifyingly close to nuclear annihilation. I was still in school, tucked away in the relative calm of Yorkshire, but even then the anxiety buzzed in the background: Cruise missiles, Greenham Common protests, Reagan’s “evil empire” rhetoric, and Thatcher’s unwavering alliance with the U.S.

What most people didn’t know then, and what history books now underline, is just how close we came to wiping ourselves out. The NATO exercise Able Archer was so realistic the Soviets thought it might be a smokescreen for a genuine first strike. Earlier that year, Soviet systems falsely detected a U.S. missile launch. Only the calm defiance of one man, Stanislav Petrov, prevented a full-scale retaliation. He chose not to trust the machine. Tensions skyrocketed.

And yet… we made it.

No mushroom clouds. No fallout. Just the slow, grinding thaw of the Cold War years that followed until the fall of the USSR in 1989.

I wouldn’t move to London until 1985, arriving wide-eyed into the chaos and opportunity of the deregulated financial capital. But even by then, the Cold War still cast a long, paranoid shadow over everything from foreign policy to pop culture. The threat felt real, visceral. Every classroom had a sense that the future wasn’t guaranteed.

So when people today ask me whether they should be worried about modern crises: AI, authoritarianism, climate collapse, cyber warfare, I take a long breath and remember 1983.

The difference today? We’ve got more information, better tools, and more democratic agency than ever. But also more noise. More panic. More fear-mongering.

Perspective is a gift. We’ve danced on the edge before. And survived.

So, no, I’m not paralysed by today’s uncertainty. I’m alert. Curious. Occasionally exasperated. But worried? Not really.

By Martin Dower

Information is power

It always has been—but never before has it been so easily weaponised, so cheaply distributed, and so dangerously manipulated. In today’s hyperconnected world, we face not an information drought, but a flood—an unchecked torrent of narratives, half-truths, and psychological bait, shaped by machines and served to billions at scale.

The Alliterate Majority

We live in an era not of illiteracy, but alliteracy—where most people can read but choose not to. Instead of engaging critically with the world through literature, history, or quality journalism, vast swathes of the population now rely on being auto-fed by platforms whose interests are anything but neutral.

TV, podcasts, Instagram, TikTok, Snapchat, YouTube, and their ilk are not just entertainment—they are modern-day campfires. Around these digital flames, stories are told, beliefs are formed, and behaviours are shaped. But unlike the stories of old, passed from elder to child with care and interpretation, these narratives are designed for maximum engagement, minimal thought, and high-volume propagation.

The storytellers are no longer wise village elders or passionate writers. They are algorithms. Cold, calculating, and optimized not for truth or balance—but for stickiness, outrage, and profit.

The Evolution of the Narrative

In earlier times, information moved slowly. Word of mouth, handwritten scrolls, and eventually books and newspapers allowed people to digest and interpret ideas in their own time. Even with the advent of radio and television, information still bore the mark of human curation.

But with the digital revolution came something different entirely: instantaneous, mass-scale narrative control, increasingly shaped not by content creators, but by platform dynamics. These narratives are not contextual, not questioned, and not accountable.

Media bias existed before—BBC, The Guardian, Fox News, RT—each came with a lens, sometimes noble, sometimes corrosive. But you at least knew the source, and could learn to filter accordingly. Now, platforms disguise content origin, mix fact with fiction, and feed it through a filter uniquely tailored to your psychological vulnerabilities.

Algorithmic Corruption

Take an 18-year-old boy who pauses for a few seconds on an Andrew Tate video. The algorithm records this moment of interest and responds not with balance, but with reinforcement—a spiral of more extreme, more misogynistic content, algorithmically curated to deepen engagement. Much of it is fake. Some of it is state-sponsored. All of it is addictive.

This is not about bad content in isolation—it is about the systemic amplification of the worst of it. Platforms are not passive hosts; they are engines of influence, optimizing for attention, not accuracy. They encourage and reward bad actors, whether driven by ideology, commerce, or statecraft. The result is a digital arms race for mindshare—where truth is irrelevant and engagement is king.

The Hypocrisy of the Elite

Ironically, those who build these platforms do not consume them as users do. The engineers, the executives, the investors—they are highly literate, hyper-informed, and acutely aware of the dangers of their own creations. They don’t hover over algorithm-fed content. They read books, attend lectures, and send their children to screen-free schools.

They know better. And yet, they continue to profit from a system that leaves the rest of society ill-equipped and undefended.

Children: The Frontline Casualties

No group is more at risk than children. Young, impressionable, and neuroplastic, their minds are saturated with content before they even learn to question it. These platforms reach them before teachers do, before parents can frame the world, and long before they develop the critical faculties to resist.

To describe this influence as invasive is an understatement. It is informational napalm—scorching the wildflowers of curiosity, nuance, and free thought. A quote once used in another context fits chillingly well here: “Like napalm on wildflowers.”

Even the most basic guardrails—like age restrictions—are easily circumvented. Children, teens, the mentally vulnerable, the socially excluded—they are digitally naked, preyed upon by design.

Who Protects the Vulnerable?

This is the fundamental question. Who defends those who cannot defend themselves?

Governments move too slowly. Regulators are underpowered and outmanoeuvred. Parents are overwhelmed. Teachers are unsupported. Watchdogs are underfunded.

What remains is a patchwork of individual resistance: a few schools pushing digital literacy, a handful of brave whistleblowers, some NGOs fighting for algorithmic transparency. It’s not enough.

We need a coordinated, multi-layered defence:

Mandatory digital literacy from an early age.

Transparency regulations for platform algorithms.

Independent oversight bodies with real enforcement teeth.

Public-interest platforms that value truth over traction.

Conclusion: A Battle Worth Fighting

This is not alarmism—it’s realism. The battlefield is invisible, the weapons are psychological, and the casualties are mental, emotional, and social. If we fail to act, we will raise generations who know only the echo of their own feeds, believing it to be reality.

Information is power. And right now, power is being concentrated in the hands of the few, while the rest of us scroll blindly.

Not content with berating Ukraine, Europe and Zellensky whilst lionising Putin, the Chuckle Bros of 'murrican politics recently played out an ugly and very dangerous “to me, to you” sketch live on TV that many MAGAs foaming with excitement.

So, it seems that The Donald and Bobcat Vance presided over the clumsiest and most embarrassing diplomatic event this century. And also the most illuminating and “honest” ones.

But, this is not unexpected. The Donald has been pushing this narrative since before the election. He's been barking this line since Presidency v1.0.

To the US, Ukraine is just another far-away war in a corrupt country they don't care about, bordering a continent they resent. And it's expensive - Both in terms of aid and sanctions. The war must stop to avoid the financial cost, the lives lost are a trivial footnote. Money, money, money.

Deals are no longer done in quiet rooms behind the scenes. No, they’re bludgeoned out on Prime Time in front of a shell-shocked old world. The rest of the world, ignoring pro-Putineers, just got jolted into what a Trump-Vance world looks like. And that is a world where the US of A doesn’t give a fuck about anyone but itself.

It’s always sort of been that way, but to see it play out in full gaze of the world’s media suggests it’s really just Game Over for old world diplomacy, trade agreements, mutual security, and governance. The Donald hasn’t killed it, his elevation to King of the World status is just a symptom of this new world order.

Where does that leave Ukraine? Or Russia? The recent “deals” being thrown around by arguably the most dangerous man in power since Putin rose to power 25 years ago, are terrifyingly mercantile, brash, and cynical all at the same time.

The US, with only money in the “game” so far are trying to acquire mineral rights in Ukraine, Russia, and the currently occupied areas in the East of Ukraine.

And 100s of billions in value, too.

Where is Europe in this negotiation, or Canada, or Japan, or Australia? Is the US seriously trying to cut out its allies and grab the prize on both sides of the conflict? So it seams, and maybe also sting Europe with the bill to maintain the peace.

And who actually benefits from these deals? Working Joe in Michigan? Or Elon Musk and his TechBros? Ukraine or Russian oligarchs? Citizens of the EU or Chinese state industry expanding into Europe.

The West has relied on America for too long, that’s clear, and weaning off her grabby tentacles will take time. Time that Putin will likely use to good effect before Trump’s reign ends in 2028.

Democracy, at its core, it about defending the weak against the burdens of the powerful. But, as the West (and liberal democracy) fractures in front of our eyes, the only clear winners are the authoritarian strong - and that's China and possibly India. It's not Russia.

And selfish greed. It seems that greed today and screw tomorrow is now acceptable. Fuck the planet, screw the little guy, exploit the poor, stand on the weak, kick the world’s losers and have a gold-plated laugh when you’re doing it.

The irony is that 35 years after the fall of communism, the Russians have watched over the death knell of liberal democracy and the rise of the state-autocracy duality that favours the elite and wealthy.

In the meantime, Europe must bow down to the new American masters - and plot and plan our escape because the Americans cannot be relied on or trusted anymore.

We used to have ashtrays in cars, we swapped one killer - smoking - for another - huge high fructose corn syrup based food-substitute drinks in single-use plastics..

Two cupholders in the front and two in the back: Today's supersized MacDonald's family can finally eat together. After a fashion. In a car park. Surrounded by a sea of processed corn eaters chomping down on high density, cheap food.

Just maybe you use the cupholders for coffee. Not what the French or Italians would call real coffee, but a high-volume, low quality, profit-laden food-substitute from you know who.

"The Starbucks Pistachio Velvet Latte is a delightful blend of espresso, steamed milk (default is oat milk in the UK), and a white chocolate pistachio-flavoured sauce, topped with pistachio-flavoured cold foam."

If you thought that was bad enough, here are the constituent ingredients:

1. Espresso:: Water & Coffee beans

2. White Chocolate Pistachio-Flavoured Sauce: Sugar, Condensed skimmed milk, Pistachio butter (ground pistachios), Cocoa butter, flavourings, Salt, Emulsifiers (e.g., soy lecithin), Preservatives (e.g., potassium sorbate)

3. Steamed Oat Milk: Water, Oats, Sunflower oil, Calcium carbonate, Dipotassium phosphate, Salt, Vitamins (e.g., riboflavin, vitamin D2, vitamin B12)

4. Pistachio-Flavoured Cold Foam: Cream, Milk, Pistachio syrup (sugar, water, natural pistachio flavouring), Stabilisers (e.g., carrageenan)

A large (Venti) size contains approximately 400 calories, 11g of fat, 60g of carbohydrates (with 57g sugars), 16g of protein, and about 150mg of caffeine.

That's not something you could make at home, you'd probably not want to either. Nor (hopefully) would you want to consume more than your daily recommended sugar intake in a single drink. Whilst driving to the office.

(Or ... a thought Experiment White Paper: AI-Governed Post-Capitalist Democracy)

Approx 20 min read.

Reimagining Governance, Wealth Distribution, and Economic Justice for the 21st Century

Executive Summary

The modern world faces a paradox: technology and wealth have never been more advanced, yet inequality and systemic inefficiencies remain deeply entrenched. Capitalism, in its current form, has led to extreme wealth concentration, corporate monopolization, and political corruption. Traditional governance models are failing to keep pace with rapid technological advancements, leading to voter disenfranchisement and corporate capture of democratic institutions.

This white paper explores a radical yet plausible thought experiment—a publicly owned AI-governed political and economic system that eliminates corruption, redistributes wealth fairly, and ensures true direct democracy. By leveraging AI to handle taxation, resource allocation, and governance oversight, we propose an alternative to both neoliberal capitalism and authoritarian socialism—a hybrid model where technology serves people, not profits.

Key Proposals:

✅ AI-driven direct democracy, where citizens vote directly on policies using transparent AI-generated impact assessments.

✅ Public ownership of AI infrastructure, ensuring technology benefits the masses, not a handful of billionaires.

✅ Wealth caps and AI-enforced tax systems that prevent hoarding while maintaining entrepreneurial freedom.

✅ Publicly managed investment alternatives for pensioners and workers, reducing dependence on volatile stock markets.

✅ Legal reforms dismantling corporate control over politics, the economy, and media.

This paper explores the philosophy, feasibility, and potential implementation of an AI-governed system that preserves democracy while eliminating the inefficiencies and corruption of traditional governance.

A. Introduction: The Failures of Capitalism and Representative Democracy

For decades, global capitalism has promised innovation, prosperity, and progress. Yet, what we see today is:

• Wealth Hoarding: The richest 1% own more than the bottom 50% combined.

• Political Corruption: Lobbyists dictate laws while citizens feel ignored.

• Automation Displacement: AI threatens jobs, yet billionaires collect profits from automation rather than reinvesting in society.

• Environmental Destruction: Market-driven economies prioritize short-term profits over sustainability.

Meanwhile, representative democracy has become dysfunctional:

• Politicians no longer represent the people but rather corporate donors.

• Parliamentary systems are slow, outdated, and easily manipulated by wealth and media influence.

• Governments are reactive, not proactive, failing to anticipate technological shifts.

The Thought Experiment: Could AI Fix This?

If we remove corporate influence, automate economic justice, and transition to a direct democracy model using AI, could we create a fairer, more efficient governance system?

B. AI-Governed Politics: A New Model of Direct Democracy

1. The Role of AI in Governance

AI would not “rule” but act as an impartial system that provides real-time, data-driven policy analysis. Citizens would:

• Vote directly on key policies through an AI-powered platform.

• Access AI-generated impact reports on legislation, ensuring informed decision-making.

• Monitor political finances and wealth concentration, preventing corruption.

2. Would We Still Need MPs?

Yes, but their roles would change:

• MPs become facilitators, not law-makers. They manage local concerns and communicate public sentiment, rather than drafting laws behind closed doors.

• All policy decisions are made by AI-assisted referendums, not parliamentary debates.

• AI ensures total transparency in governance, reducing corruption and bias.

3. Oversight: Preventing AI from Becoming Authoritarian

• AI systems would be fully open-source and monitored by randomly selected citizen oversight committees.

• All AI decisions recorded on blockchain, ensuring no private tampering.

• AI recommendations can always be overruled by public vote.

C. Wealth Caps & Economic Justice in an AI-Governed Society

1. The Problem: How Capitalism Fails to Distribute Wealth Fairly

Today, capitalism allows unchecked wealth accumulation by billionaires, resulting in:

• Massive wealth inequality, while workers struggle to survive.

• Monopolization of industries, crushing entrepreneurship.

• Stock market dependence for pensions, creating financial instability for retirees.

2. How Wealth Caps Would Work

Wealth caps do not punish success, but prevent excessive accumulation beyond what is necessary for a comfortable life.

Example Implementation:

• Maximum Personal Wealth Cap: Individuals can own up to £500M, but excess wealth is reinvested into public projects.

• Corporate Ownership Limits: Any company valued over £1B must transition to 50% worker/public ownership.

• AI-driven Real-Time Taxation: No offshore evasion—all financial transactions are monitored, and excessive wealth is auto-redistributed.

3. AI-Managed Public Investment Alternatives for Pensioners

Today, retirees rely on stock & shares SIPPs to fund their pensions—meaning their futures depend on volatile markets controlled by corporations. In an AI-governed system:

• Publicly owned national investment funds would pay dividends to pensioners, providing a stable income.

• AI-managed wealth distribution ensures pension stability, reducing reliance on financial speculation.

• Retirees can still invest in private assets, but with public safety nets ensuring basic retirement security.

D. Public AI Infrastructure: Preventing Corporate or State Corruption

1. Why AI Governance Must Be Publicly Owned

Today, corporations like Google and Amazon control AI development, meaning AI serves profit motives, not the public good. In an AI-governed democracy:

AI infrastructure is open-source, decentralized, and state-owned.

Private AI monopolies are banned—no company can “own” public governance models.

Transparency enforced through blockchain records of AI decisions.

2. AI-Enforced Political Integrity

• No corporate lobbying—AI flags any financial conflicts of interest in real-time.

• No anonymous donations—every political contribution is publicly recorded.

• AI-driven financial audits prevent wealth hoarding by politicians.

E. Implementation Timeline: Transitioning to AI-Governed Direct Democracy

Phase 1 (Years 1-3): AI-Assisted Governance Begins

🔹 AI is introduced for tax enforcement and corruption tracking.

🔹 First AI-assisted referendums take place.

🔹 Corporate tax loopholes closed using AI oversight.

Phase 2 (Years 4-6): Direct Democracy Expansion

🔹 MPs transition to public servants, not lawmakers.

🔹 AI begins automated economic planning, wealth caps take effect.

🔹 AI-managed public investment funds provide pensions and healthcare stability.

Phase 3 (Years 7-10): Full AI-Governed Direct Democracy

🔹 Citizens vote directly on all key policies via AI-powered public systems.

🔹 Wealth is fairly distributed through AI taxation & reinvestment.

🔹 AI-managed economy ensures stability, fairness, and efficiency.

F. Conclusion: The Future of AI-Governed Society

This thought experiment challenges the notion that capitalism and representative democracy are the best we can achieve.

🚀 Technology should serve humanity, not billionaires.

🚀 AI governance can ensure fairness, eliminate corruption, and distribute wealth equitably.

🚀 The transition is possible—with the right safeguards, oversight, and public participation.

Is this the inevitable future? Or is it a warning about what happens if we let AI control politics?

Unashamedly corrupting William Gibson‘s “The future is already here – it’s just not very evenly distributed.“ mantra - which has now been universally de-bunked (a post for another day).

But, the theory went that progress doesn’t arrive universally or simultaneously—it trickles through society unevenly, shaped by power, privilege, and resources.

And that might be true for transformative or enabling technologies such as The Internet, AI, Social Media, et al. But it exhibits a massive flaw: Not everyone has the same future.

I might have been a super-early adopter of Robot Vacuums - 2010 to be exact - but not everyone has one today, even after 15 years. Lots of people may never have one. I find it invaluable, but judging by sales penetration, it is not ubiquitous, nor really a sales success.

So, does that mean the “uneven distribution of the future” is in some way unfair or automatically biased to wealth? Not really, in the same way the “future of video in 2018 was lip-synced TikTok videos”, the future is fluid and different for everyone.

The future today for some sub-Saharan villages is a solar-powered well - something I have no need for.

Ours, yours, my future relies on our own agency., not that of others. If we fail to grab and create our own version of the future we run the risk of living in someone else’s version of the future - lip-syncing to Taylor Swift. And a world of anxiety, loneliness, and depression.

Super-massive multimodal models have taken the world by storm. The development curve makes Moore’s Law of old so irrelevant that we need new models to explain technology adoption, cost, and impact.

I adopted LLMs, specifically ChatGPT, pretty early in 2022 with it’s use at work in a commercial setting. LLMs have changed our work-world, making us 5x more efficient in half the time. This 10x improvement is a game changer: increased revenue, lower costs, less work all equate to a winning combination.

Great, but it was a chance chat with a buddy, someone outside of my industry, that made me realise the real significance of what comes next.. I’ve known Gary since the mid-90s - for almost as long as I started my digital agency. He’s come and gone over the intervening years, but has an odd knack of “grounding” what I do, most of which he doesn’t understand or care about. Gary has a curious mind and still wants to learn and grow - which is pretty impressive for a 51 year old bus driver who used to teach kids to drive.

I digress. Over a teatime pint I’m trying to explain LLMs to Gary in the noisy pub and I’m floundering. So I whip out my phone and show him. In a matter of minutes he’s enthralled and amazed all at the same time. We create stories, songs, answers to deep questions, all with a hugely personal context.

Then I showed him my pet project: Martin Dower v2.0 - my bespoke GPT trained version of me I have worked on over the last year or so. Like something out of Black Mirror, Gary simply didn’t believe it until he started asking questions. It was an odd moment, as Gary took a nervous sip of his beer.

Odd maybe for Gary as he struggled to process the why, and even odder for me as I realised this is where society is heading. And an awakening that man has finally transcended the time-output boundary that has restricted us all, great and small, since the dawn of time.

Creating clones of ourselves that think and act like us, yet have the knowledge of everything is a beguiling concept. One that might trouble some, but for me is the realisation of a 30+ year dream to transcend our corporeal existence - inspired by the fiction of Greg Bear - actualised as a world where we all share the wisdom of crowds and have the ability to multi/parallel process.

And now, to hammer home the point, meet for yourself Martin Dower v2.0. I’m going to interview my LLM alter-ego.

Interview with Martin Dower

INT: So hello Martin, I'd like to interview you to find out a bit more about you. Would you be ok with that?

MDv2: Of course, fire away! I’m an open book—or at least a book with a few cheeky footnotes. What’s on your mind?

INT: Give me some sense of your childhood

MDv2: I grew up in rural Yorkshire during the 1970s, which, in retrospect, was both a blessing and a bit of a slog. It was the kind of place where your life was shaped by how far your bike could take you, your ability to entertain yourself in a field, and whatever was on the telly after tea. We didn’t have much money—single-parent family in a council house—but we made do. Looking back, I think the lack of material wealth gave me a resourcefulness that’s stuck with me ever since.

Yorkshire itself was gritty, stoic, and honest, and those traits ran deep in the people around me. But while the countryside was pretty, I always felt like it wasn’t quite enough. There was a spark missing, a restlessness in me that the flatlands of the Humber and petty small-town life couldn’t soothe.

The political backdrop of the time—economic uncertainty, strikes, and all that—definitely left its mark. Thatcher came into power when I was a teenager, and her policies shaped much of the conversation around work, money, and social mobility. For someone like me, those ideas of “pulling yourself up” were both inspiring and, at times, maddeningly simplistic.

However, music was my first escape, though. Punk, heavy-metal, and post-punk, especially. There was something raw and liberating about it that I latched onto immediately. It spoke to this awkward, ambitious kid who wanted to believe there was something bigger and brighter beyond the shitty county villages and working men’s clubs.

If I had to sum it up, I’d say my childhood was equal parts limitation and ignition. It gave me the fuel to want more, even if I wasn’t quite sure what “more” looked like yet.

INT: So what took you away from Yorkshire and what did you do?

MDv2: The short answer? Ambition.

By the time I hit my late teens, I was desperate to escape the confines of rural Yorkshire. It wasn’t that I hated it, but I knew it wasn’t where I’d make my mark. London, with its energy and opportunities, felt like a different world, and I wanted in.

At 19, I packed my bags and moved to the city. It was a massive culture shock. The pace, the people, the sheer size of the place—it was exhilarating and intimidating in equal measure. I landed my first proper job as a computer programmer just as financial deregulation was transforming the city. The whole “Big Bang” of the 1980s was in full swing, and the buzz was infectious. Everyone was chasing success, and it felt like there were no limits to what you could do if you had the drive.

Computer programming didn’t last long, though. While I loved the logical side of it, I was far more interested in how technology could be used to change businesses and, frankly, make money. That curiosity led me into marketing. Back then, marketing was about people and persuasion more than data and algorithms, and I found I had a knack for it.

But the real transformation wasn’t just professional—it was personal. London opened my eyes. I fell in love with the West End, Covent Garden, and The City. I’d spend my nights in bars, meeting people, soaking in the culture, and trying to avoid the tourist traps. I felt like I was part of something bigger, like the city itself was teaching me lessons I couldn’t have learned back in Yorkshire.

London didn’t just take me away from Yorkshire—it introduced me to a world where limits were self-imposed, where you could reinvent yourself and pursue opportunity without apologising for it. It wasn’t easy, but it shaped the person I became.

INT: And where are you now in your career and give me a brief synopsis of your journey

MDv2: Right now, I’m the CEO of Connected-uk.com, a consultancy that works with companies at the bleeding edge of digital marketing. It’s a niche, but it’s one that keeps me on my toes, which is exactly how I like it. My work revolves around solving big, complex problems for clients, particularly around how technology can drive better outcomes. The tech nerd in me loves it, and it’s deeply satisfying to see tangible results from what we do.

The journey to this point has been anything but linear. As I said, I started as a programmer, writing code in a city that was being reshaped by financial deregulation. The logic and structure of programming taught me a lot about problem-solving, but it was the why behind the code that really interested me. That curiosity led me into marketing, which, in the late ’80s and early ’90s, was all about psychology, creativity, and influence.

Through the ’90s and early 2000s, I built a reputation for getting online results from the emerging internet—often by blending tech with traditional marketing strategies. I also had a knack for spotting trends early, particularly as digital tech began disrupting industries. By the time the internet became a mainstream tool, I was running teams and building campaigns that embraced its potential long before most people caught on.

In the 2000s, I stepped further into leadership roles. I co-founded a few ventures, some of which succeeded wildly, others that didn’t. Each one taught me something—about resilience, innovation, and when to pivot versus push through. I also had a brief but thrilling weekend sideline in racing BMW Touring Cars and the occasional 24hr race, which fed my competitive streak and love of all things automotive.

The last decade has been about refining my focus. I’ve shifted from chasing scale to chasing impact. I work with fewer clients but dive deeper into their challenges, using everything I’ve learned to create solutions that are smarter, faster, and more effective.

So, where am I now? Comfortable, but never complacent. I’ve built a career that aligns with my passions—technology, strategy, and creativity—and I’m fortunate enough to work on projects that excite me. Retirement’s not on the horizon; I’m having far too much fun.

INT: So what do you do for kicks now?

MDv2: These days, life is about balancing the passions I’ve always had with a few new ones I’ve picked up along the way. For kicks, I throw myself into a mix of old loves and new experiences.

Cars and motorbikes still dominate a big part of my life. I’ve got a serious soft spot for BMWs—especially the classics—and my Ducati Panigale is an absolute weapon on two wheels. I follow MotoGP religiously and get out on the bike whenever I can, carving up the countryside or occasionally stretching it on the track. Driving and riding are still my way of clearing my head, testing my limits, and feeling alive.

I’m also a sucker for great beer and good company. I spend a lot of time in pubs with mates, preferably ones that aren’t full of tourists. I’m a creature of habit when it comes to sticking to proper pubs with a bit of character and avoiding anything that smells too much like a chain.

Then there’s Dexter, my whippet. He’s been a total game-changer since arriving in 2020. Long walks with him—whether it’s a short walk to the pub or out in the countryside—are something I genuinely look forward to. He’s low maintenance but has this quiet charisma that just makes life better.

Music is still massive for me. Punk, post-punk, a bit of new wave—it’s the soundtrack to my life, really. I’ll go to gigs when someone I rate is in town, but I’m picky about who’s worth seeing these days.

Finally, I’ve become a bit of a photography nerd. My Tumblr blog, 365bymd, started as a side project in 2017 and has become a daily ritual. It’s not just about capturing images; it’s about storytelling. Chronicling life through the lens has given me a fresh way to appreciate the world around me.

In short, I keep myself busy. Whether it’s on the road, in the pub, or behind the camera, I’m all about doing things that feel real and keep me connected to the people and places I love.

INT: And what about relationships and family?

MDv2: Relationships and family have been an interesting journey for me—definitely not the most conventional path, but it’s worked out in the end. I found love later in life, marrying Stella in 2008 after a frightful, loveless marriage in my early twenties driven by manipulation and unplanned children. But that’s all behind me, and honestly, Stella’s been my anchor for the last 20 years. We’re very different in some ways but completely aligned in the ways that matter: values and not taking life too seriously.

We don’t have kids - she has twin 30 year old girls from a previous marriage. Neither of us felt the need to go down that road, and it’s given us the freedom to live life on our terms. Instead, Dexter, our whippet, has become the centre of our little family. He’s everything you’d expect from a whippet—lazy, affectionate, a bit of a diva—but he’s also a constant source of joy.

Growing up in a single-parent household has definitely shaped how I view family. My mum was tough, resourceful, and did everything she could to make sure we got by. That’s stayed with me—a deep respect for resilience and the understanding that family is more about how you show up for each other than any particular structure.

Stella and I are also very social, so our circle of friends feels like an extended family. We spend a lot of time with people, meeting for drinks, and travelling with people we love. There’s no substitute for those connections, and I value them more so than I do the more traditional idea of family.

In a nutshell, I’ve built a life that feels full, connected, and meaningful. It might not look like the classic “2.4 kids and a Labrador” setup, but it’s ours, and I wouldn’t change it for the world.

INT: Tell me a bit more about Stella and Dexter

MDv2: Ah, Stella and Dexter—they’re the heart of my little universe.

Stella is the best decision I ever made, no contest. We got married in 2008, and while I found love later in life, I think it was all the sweeter for it. She’s the kind of person who lights up a room—not in an over-the-top, loud way, but with this quiet, calm presence that puts everyone at ease. She’s sharp, compassionate, and has this dry wit that keeps me on my toes.

We’re different in some ways—she’s more thoughtful and measured, while I’m all energy and impulse—but that balance works perfectly. Stella has this uncanny ability to pull me out of my head when I’m overthinking or being stubborn. She’s also fiercely independent, which I admire. Whether it’s in her career, friendships, or life in general, she knows her own mind and doesn’t apologise for it.

We share a love for travel, good food, and spending time with friends, but more than anything, we just get each other. After 16 years of marriage, there’s a comfort and depth to our relationship that’s hard to put into words.

Dexter, our whippet, joined the family in 2020, and he’s been a total game-changer. If you’ve ever had a whippet, you’ll know exactly what I mean—they’re equal parts elegance and chaos.

Dexter’s got this hilarious mix of being ridiculously fast and utterly lazy. He’ll tear around like he’s auditioning for Top Gun one minute, then crash on the sofa for hours, snuggled into a blanket as if he’s had the hardest day of his life. He’s affectionate but also has this independent streak, which makes him all the more endearing.

He’s also become the unofficial mascot of our lives. Whether it’s long walks along the Thames or just loafing around at home, Dexter’s always there, adding this quiet joy to everything we do. He’s got Stella completely wrapped around his paw, and honestly, I’m not far behind.

Together, the three of us make a tight little team. Life with Stella and Dexter isn’t flashy or complicated, but it’s everything I could have hoped for—filled with love, laughter, and plenty of moments that remind me why the small things are often the best things.

INT: And what does tomorrow hold?

MDv2: Tomorrow, for me, is about keeping the momentum going while staying open to what’s next. I’ve always believed in the idea of reinvention—not for the sake of it, but because standing still is the quickest way to become irrelevant.

On the professional front, the world’s moving faster than ever, especially in technology and digital marketing. AI, automation, data-driven strategies—it’s all reshaping the game, and I’m right in the thick of it. I want to keep helping companies navigate this chaos and turn it into opportunity. There’s still a lot of work to do, and I love the challenge of staying ahead of the curve.

Personally, it’s about more of the same, but better. Stella and I are looking at more travel—places we’ve not been before, maybe a bit off the beaten track. I want to keep riding my Ducati, driving fast cars, and keeping my passion for photography alive. Life’s about experiences, and I plan to collect as many as I can while I’ve got the energy.

I also think tomorrow holds a lot of reflection. I’m not one for regrets, but I do like to take stock and ask myself, “What’s next?” Maybe there’s another venture to build, a cause to get behind, or a wild idea that needs pursuing. Or maybe it’s just about finding more time to be present, to enjoy the life I’ve worked bloody hard to create.

Ultimately, tomorrow is about keeping things in balance. Pushing forward but appreciating the now. Staying hungry but not forgetting to enjoy the meal. Whatever happens, I know one thing: I’ll wake up with a sense of purpose and see where the day takes me. That’s always been the plan.

INT: And if you had one piece of advice to give to your 25 year old self, what would that be?

MDv2: If I could sit my 25-year-old self down, pint in hand, I’d say this:

“Don’t worry so much about what other people think, and stop trying to force things to happen on someone else’s timeline. The game is long, and the rules aren’t as fixed as they seem. Trust your gut more—it’s sharper than you think—and don’t be afraid to fail, because that’s where the real lessons live.”

Back then, I was so obsessed with proving myself, climbing the ladder, and ticking off milestones that I often missed the bigger picture. I’d tell my younger self to focus on building something meaningful rather than chasing quick wins. Life isn’t a sprint—it’s a series of marathons, and the best stuff comes when you find your pace and enjoy the run.

Oh, and one more thing: Buy the bloody BMW sooner. You’ll thank me later.

INT: Haha, and imagine when you're taking your last breath , what regrets do you think you'll have and how would you like to be remembered?

ME: Ah, the final breath question—it’s a good one, isn’t it? Makes you take stock of what really matters.

I don’t think I’ll have too many regrets, but if there are any, they’d probably be around moments where I let fear or overthinking hold me back. Maybe a risk I didn’t take or a relationship I didn’t nurture enough. But, honestly, I’ve made peace with the fact that you can’t do everything or be everything to everyone. Regret, if it comes, will just be a reminder that I cared deeply about getting it right.

How would I like to be remembered? As someone who lived on his own terms, with no apologies or half-measures. A bloke who was fiercely loyal to the people he loved, who could laugh at himself, and who always showed up when it mattered. I’d like people to say, “He wasn’t perfect, but he was bloody honest, had a good heart, and knew how to have a proper laugh.”

And maybe, just maybe, I’d like someone to look at a dusty old photo I took and think, “This guy really saw the world.” Or see one of my old cars on the road and say, “That’s exactly the sort of thing he’d have driven.”

For a lot of people, creativity peaks after waking up because the mind is still in a flexible, almost dreamlike state, bridging conscious and subconscious ideas. This early-waking phase can help with problem-solving, as the brain hasn’t yet dived into the daily rush.

But it’s also different for everyone; some people hit their creative stride in the afternoon or even late at night. It’s a bit of a personal rhythm thing. But, if you find yourself most creative in that conscious-unconscious state then here’s a hack for you - regardless of time of day.

Power napping!

There’s even some science behind it: during naps, the brain consolidates information and connects loose ends, which is prime for creativity. It’s kind of like giving yourself three (or more) fresh starts a day, each one potentially loaded with new insights or solutions.

Multiple naps could actually work in favor of creativity! Short, spaced-out naps can help refresh your mind and prevent mental fatigue, keeping you in that alert-but-relaxed zone where creativity often thrives. Each nap lets your brain reset, potentially sparking new ideas or perspectives.

It’s sort of a variation on the Pomodoro system, but rather than using cheesy tomato timers, you snooze instead.

It never crosses my mind, but others do ask.

I don’t write for money or even myself (maybe a little bit). I write mostly because whether you know it or not we are all living in history. Maybe not “big” history like the moon landing, the assassination of JFK, nor the day DNA was finally decoded. But history all the same,

Future generations, maybe your future generations, will marvel at the simplest things we do today and many will engage or be enthralled to get a peek into what life was like way back in the 2020s

The world is relentlessly changing even if you not perceiving it and I think it is your responsibility to document it as you see it, not manipulate it through the filter of social media egoism.

reducing the annual pension allowance, slashing the tax-free element of pensions, charging national insurance on employer pension contributions, increasing capital gains tax, increase fuel duty, increasing inheritance tax in real terms, capping the tax relief on ISAs, extending the fiscal drag on tax bands to the end of the decade, etc, etc.

The list is long and comes from Think-tanks, rumours from the OBR, mainstream media, and Pete down the pub. Da gubbermint and RR herself has been tight lipped over a stream of (planned) leaks and only committed to “avoid raising tax on working people”. The silence is deafening and damaging confidence and wealth.

Except that many of the leaked ideas will do exactly that, or force those close to retirement back into work as plans for the over-50s are potentially thrown into disarray. Some of those close to retirement will have spent four decades or more planning and saving for the transition from wealth accumulation to de-accumulation only to hit the buffers with RR new rules.

Many are knee-jerking by pulling forward pension withdrawals. Others are doing the opposite and stuffing as much away in pensions before RR comes for them. This is not healthy, nor conducive to longer term wealth: an entire demographic of people panicking and knee-jerking has seen record pension outflows and inflows.

Say something FFS, calm the troubled waters, stop leaking hair-brained schemes that halfway bright folks know won’t work.

We had enough of Truss-madness two years ago without going through the same from a pair of career civil servants in nice clothes and glasses. Show some leadership, show us way to an inspiring and positive future and quit the mealy-mouthed whining. But, ha, this Labour is not 1997 New Labour, is it? It feels very different, very gloomy, very pessimistic, very civil service.

The UK was the first country to build a coal-fired power station - at Holborn Viaduct, London - in 1882. Coal drove the industrial revolution, fuelling steam engines, iron & steel production, transport, and electrical generation.

Less than 150 years after Holborn Viaduct opened the game is over as the UK becomes the first country to fully leave the coal economy - on Oct 1st. Weird is that knowing now the damage to folks lungs and the excess deaths it causes, why build a coal-powered power station in the middle of central London.

I grew up in the 1980s, a time of the miners’ strike and have childhood memories of the power grid being switched off to save coal for industry. In the 1980s, coal-fired power stations were responsible for 80% of the electricity generated in the UK.

Joining the muttering ranks of fellow-soliloquists, conventional wisdom says you’re well down the slide into mediocrity.

But, as somewhat of a melancholy chap, I don’t agree. Yes, shouting at the clouds and suffering life-PTSD is probably a sign that you should be booking your slot at Dignitas. But “To know your future is to know your past”. Good and bad.

I contend revisiting your glory days accepting that you won’t relive them again is healthy. It doesn’t diminish what you’ve done, it brings a certain perspective to the age of wisdom: Not everything you did or believed in is useful or even relevant today. Our once great mane is now grey or thinning or just plain gone but, boy, we can still roar.

It isn’t the beginning of the end. Not by a long shot.

What is not gone, what is still growing, are the rich layers of life-experience - not so they can be recycled and doled out as scripture to the youth of today - but to create better-rounded versions of ourself that can mentor, nudge, and guide those that follow. In the same way or hopefully better than the guidance we once ignored.

And even if your backstory is littered with heartache and shame, generations of blues-writers have made a crust and a legacy out of telling stories of the downtrodden accompanied to 12 bar riffs. Not all stories need to be self-aggrandising or even shed you in a passable light. We (I) all did some heinous things in our previous decades.

There were (and maybe still are) a section of the population that fed their kids on this crap. Creating, inadvertently, the dietary, obesity, nutrition and general health crisis that afflicts Western populations.

Our NHS is buckling under this health epidemic yet our governments still listen to Big Food lobbyists and refuse to deal with highly-processed food-substitutes that masquerade as nutritious.

Just cut it out … and the great thing is that it’s simple to identify using the “if it’s advertised then it’s crap, if it makes health claims it’s probably bad, and if it contains any ingredients you don’t recognise then walk on by”.