The interview comes a month after Reeves’ Mais Lecture, where she called AI “the defining technology of our era” - pledging that Britain would achieve the fastest rate of AI adoption in the G7, backed by a £2.5bn support package.

Reeves isn’t using the same technology she’s staking Britain’s economic future on. It’s like a Health Secretary lauding the NHS while never having been 56th in the GP phone queue.

Liz Kendall, the Science, Innovation and Technology Secretary, was no more reassuring. In the run-up to last week’s launch of the government’s new £500m Sovereign AI Fund, she was interviewed by the BBC’s Matt Chorley.

Riding in the back of an autonomous taxi, she said:

“Uh well, I use AI personally rather than at work. I’ve got to be honest. I’m much more likely to to use it in my my personal life.”
Liz Kendall, Science, Innovation and Technology Secretary

Kendall’s best example use case was turning to the technology to help decipher the ingredients list on the back of a cosmetics bottle to treat an allergic reaction. A good application, in a pinch. Hardly a blueprint for the Fourth Industrial Revolution. An irony that Chorley himself couldn’t help picking up on:

“You’re the government advocate for AI and you’re saying that you don’t use it at work.”
Matt Chorley, BBC

There is a counterargument: that AI is cognitively corrosive and by avoiding it, Reeves, Kendall and other government ministers are preserving their independence of thought.

As a personal stance, it is defensible. In the Chancellor’s case, who believes AI has the “potential to transform productivity across the entire economy”, I’m not sure it passes muster. The same could be said for historian-turned-innovation-chief, Kendall.

Freedom of information (FOI) exposure is likely the main fear holding politicians back.

This follows the precedent set in the case of Peter Kyle - Kendall’s predecessor who was the subject of a request filed by the New Scientist. Despite initially resisting, a transcript was released, establishing that these interactions are subject to the same transparency laws as emails or WhatsApp messages if used for government business.

Kyle remains the only politician to have had their AI interaction logs released through FOI. The government has since successfully blocked similar requests by arguing that they would place a “grossly oppressive burden” on staff to find and redact the data.

As I’ve said previously, conversations with AI systems should be afforded the same privilege as speaking with a doctor or lawyer. It is on these grounds that I understand the trepidation those in government feel; they should have the freedom to privately use these systems.

This fear should not outweigh our politicians adopting the technology, especially when it is increasingly the cornerstone of government policy. They cannot escape the fact that AI is already altering how we live and work, and in time how we govern.

Government advisers will have been tasked with preparing reports, bringing in speakers, and modelling its impact to educate ministers. But no number of briefings, looking from the outside in, can substitute spending time using the technology.

They are missing what these systems now are becoming: not just models that answer questions, but tools that can search, analyse, write, code and, within bounds, act on a user’s behalf across the web, in software, and through the computer interface itself.

You must use it, to understand it.

Working with it, they would also find its edges: where it still hallucinates, trips up, and where it simply stops. They would hit its limits. A Chancellor who has never been cut off by a Claude usage cap has no instinct for what compute scarcity means - and she is the one allocating public funding for how much of it Britain should build.

I find it odd that our political leaders, like Reeves, aren’t the least bit inquisitive. Not only to be personally behind the technology curve, but to have barely a sliver of experience of what it feels like to be on it. It’s even more jarring given their policy statements, let alone how exposed the economy they steward is to its effects.

By insulating themselves from AI, they are avoiding an experience that would make their advocacy more honest. Their words instead ring hollow, doing a disservice to what is being built in the UK. The government’s £500m Sovereign AI Fund. Commitments from Anthropic and OpenAI to expand their UK presence. DeepMind - one of the world’s frontier labs - headquartered twenty minutes from Westminster, choosing London as their base rather than relocating to the Valley.

”We’re a little bit out of it here, but I think it’s very conducive to thinking deeply about things, being more original about how you think.”
Demis Hassabis, CEO of Google’s DeepMind

Hassabis gets to the crux of what could define Britain’s role in the AI transition.

We do not have the financial or operational might of the US, the current epicentre of AI. Our strength must be in our intellectual independence: the confidence to be a little off-centre, to be curious, to have the licence to be contrarian, and to follow a thought without knowing immediately where it leads.

Our political leaders must channel this same disposition. Applying this to how they govern, but also how they engage with the tools reshaping the country they lead.

Try it. Then speak openly about the experience - the surprises, the limitations, and the moments it changed how you thought about something. Because everyone else is already doing exactly that: finding their way with an intelligence none of us fully understand yet. Whether you’re a receptionist in the back office of a Stoke law firm, or a researcher on the DeepMind team building it at source.

We are all, in our different ways, figuring this out together. Our politicians should be too.

“Maybe that’s where I’m going wrong.”
Rachel Reeves, Chancellor of the Exchequer

Written by Lewis Thomas

20,000 real estate professionals will be back behind their desks or on construction sites this week. Their faces still flushed from the Cannes sunshine.

The biggest players in the sector will have spent MIPIM sauntering from the Palais to Caffè Roma for a glass of Provençal wine. Some might have escaped to the hills or enjoyed a networking dinner on Rue du Suquet, in the old town, away from the overpriced menus down on the Croisette.

Looking over the 2026 conference programme, the expected themes are there: decarbonisation, housing supply, ESG and regional showcases. All important topics. But reading over the session descriptions, you wouldn’t know the ground is moving beneath the industry.

The $393 trillion global real estate market could be one of the biggest beneficiaries of the AI revolution. In terms of the data centre build-out, it already is. The sector and all those in it also have the most to lose. No one can escape what’s coming, whether funding, investing or building.

MIPIM did introduce a data centre summit this year. Sessions included: From Bits to Bricks - Securing Power, Sites, and Capital in the AI-Driven Investment Boom.

Three years late? Maybe.

The agenda still treated AI largely as a scaling story: more compute, more power, more capital allocated to data centres. What it did not ask was what comes after. Nor did it properly confront the parallel risk: that AI may start eroding demand for space before creating entirely new forms of it.

Cushman & Wakefield has recognised this. It launched an AI Impact Barometer in February that measures the technology’s momentum and its impact - positive and negative - on employment, economic growth and key real estate asset classes.

The Barometer only reaches Q3 2025 - missing the recent acceleration in AI capability and the change in market sentiment that followed.

The industry’s dominant AI narrative up to now has been opportunity: data centres, capital flows and efficiency gains. A digital boom driving real estate on. But the Barometer begins a different conversation. It positions AI as a sliding scale, capable of inflicting structural damage to parts of the market and those operating in them, not just a tailwind to the sector.

Listed real estate services firms have already experienced corrections in their stock prices. This is despite strong financials. CBRE dropped in the same week it reported double-digit growth.

The sell-off is an early signal: a sign that AI risk is moving from the abstraction stage.

The risk is twofold.

First, AI may disrupt real estate businesses directly. Unlike software, however, these firms are in the business of physical assets. This points to more pervasive fears that parts of the real estate market are vulnerable to AI’s secondary effects.

The office market in particular may be approaching its second demand crisis within a decade, with AI’s impact on jobs threatening lettings and occupancy.

In Birmingham, my home city, current office vacancy is between 9.6% and 11.3%. It has proven to be resilient, but concentrated, with headline rents rising in prime buildings even as overall vacancy exceeds its pandemic peak - bifurcating before AI’s effects have fully arrived.

It is a precarious market, and what is not being sufficiently stress-tested is what happens to global office markets if unemployment rises materially.

CBRE IM’s report, Gen AI’s Impact on U.S. Employment and Office Space, states a 10-year scenario where 60% of jobs with “higher potential for automation” could be displaced.

The report’s findings are that the AI scenario produces results similar to its existing base case for offices, with vacancy falling from 22% to 18.5% by 2035. In other words, AI displacement, even at scale, lands offices in roughly the same place they were heading anyway.

This early analysis is U.S.-focused, including technology clusters - the epicentres of AI - where hiring offsets displacement. Apply the same logic to a regional UK market without that countervailing demand, and it could be a very different outcome.

Antony Slumbers’ analysis shows the range of possibilities. He ran a firm through four scenarios across a five-year horizon. The results range from a 22% office space reduction to a 43% expansion - a 65-percentage-point spread showing the difficulty of predicting this accurately. It is worth reading precisely because it refuses to collapse uncertainty into a single number.

If employment falls, the consequences are stark not just for office owners and operators, but for the lenders and investors exposed to them.

Office debt is robustly modelled. Lenders stress higher rates, slower leasing, weaker values against their internal metrics. All of which would come under duress in a non-linear, AI-led labour-market shock that pushes several assumptions the wrong way at once.

The obvious rebuttal is that offices survived Covid. The next disturbance may look different. Not an immediate collapse and recovery in occupancy, but a more persistent deterioration.

This does not require the hyperbole of AI eliminating all white-collar jobs, merely unemployment permanently revisiting, or surpassing levels reached after 2008.

Where would that leave offices?

They may bear the brunt of this, but offices will not absorb the shock alone.

A drop in employment will ripple outward. It will dent consumer confidence and spending, which is more than half of UK GDP, harming other real estate asset classes.

The risk doesn’t even require large-scale AI-led redundancies. The fear of job insecurity alone may be sufficient to pull forward the impact on the broader economy.

The situation the real estate industry is currently facing down is different from 2008 or other recessions. It also arrives just as much of commercial real estate can be read as near a cyclical bottom. Thinking that these factors alone insulate the market from AI and its effects is foolish. There is still significant financial and operational risk.

The Cushman & Wakefield Barometer, stock market action, and rising unemployment all point to it. Failing to dedicate time to this discounts the danger - forcing an important conversation out onto the Croisette. Perhaps for fear of an uncomfortable on-stage discussion, and the admission that many in the sector are stumped by the scale of this technological change and what it means.

The same failure of imagination that keeps the full extent of AI’s risk off the agenda also obscures the opportunity - a future where AI isn’t just a tool acting on real estate, but is a vast new consumer of it.

Data centres are the first stage of this journey. The demand for compute will continue to buoy the asset class for years to come, with nearly 100 new developments in the pipeline in the UK.

The move from digital AI to physical AI will bring opportunities for which the real estate industry has no existing framework. The global proliferation of robotics, autonomous vehicles and humanoid systems will reshape the built environment as we currently know it.

I chaired a discussion on AI as an occupier of the future last year. On the panel was Starship Technologies, which is conducting millions of autonomous robot deliveries globally for retailers, as well as moving goods around industrial sites and university campuses.

Last mile logistics is where much of the immediate autonomous innovation is taking place. This relies on charging and maintenance depots, route infrastructure, micro-fulfilment hubs positioned for robotic range and, critically, space designed around non-human transit.

Meanwhile, Waymo has logged over 2,500 vehicles in commercial operation across the US, with its autonomous taxis spotted on London roads doing supervised trialling and mapping.

The real turning point will come with the credible deployment of humanoid robots. This is now a question of when, not if, according to Goldman Sachs, which is projecting hundreds of thousands in operation by 2030 across various applications.

Robotics will require new manufacturing space, supply chains, digital infrastructure and testing environments.

None of these categories have an established vehicle. There is no REIT for autonomous vehicle depots, no standard approach to robotics testing facilities, no asset class for the charging and maintenance infrastructure that physical AI will require at scale.

It is hard to comprehend this next stage of the AI revolution: the new planning uses, developments and investment prospects it may create.

The transition may come at the expense of existing asset classes, no doubt reinventing others, but increasing the non-human demand for real estate. This may be no comfort to the owner of a secondary office building. Disruption and opportunity will not always land on the same balance sheet. But for the industry, the mistake would be to treat this as a demand shock in only one direction.

The industrial revolution emptied the fields. It also led to the creation of factories, railways, warehouses, and industrial cities. The built environment is not a passive bystander to technological transformation. Physical infrastructure will enable AI’s next chapter.

The grand vision of a city with robot storage, drone ports, autonomous road systems - even AI humanoids roaming the streets - still feels a way off. An electric dream.

It’s even more humorous considering the Starship panellist mentioned that among its biggest hurdles was a lack of drop kerbs and its robots not being able to press buttons at crossings.

Physical AI will have its takeoff moment. Building for it will require trillions in real estate investment, development and funding. Those willing to experiment, invest and initially fail will hedge the disruption coming to other parts of their portfolios. They will also capitalise on the lag: the fact that technology arrives first and the ‘official’ real estate asset classes come later.

In previous cycles, that lag has been measured in decades. The pace of this one may not allow for the same institutional patience.

Those who move before the market has a name for it won’t need to be on stage at MIPIM 2035, debating how to fund robotic manufacturing facilities. They’ll have already done it. Sitting in Caffè Roma, sipping rosé served by a humanoid waiter, wondering: where will real estate’s next defining moment emerge?

The answer, it turns out, may not be found on the conference agenda.

I’m not religious, nor politically aligned. I’ve always drifted in my view, open to ideas but never certain on anything.

At university I read Marx and Klein, fancying myself an anti-capitalist: against consumerism and corporations, for the proletariat and the working man. I didn’t have a clue. It sounded correct. Surrounded by people much smarter than me, it was easy to regurgitate. Pass it off as my own.

Years later, I’d swung hard the other way. I remember announcing to colleagues that I’d be happy to do PR for a defence or tobacco company. No questions asked.

My 25th birthday, furthering my career at a corporate law firm, buying my first home — in my head, these were all moments that I thought would bring direction.

Instead, I was unmoored.

I was the heaviest I’d ever been. Never checking out professionally — still hauling myself to the office and trying my best, but only because of personal pride and a pay cheque. Something was wrong. An uneasiness that I hadn’t questioned before.

The pandemic and the cost-of-living crisis that followed made it impossible to ignore.

For my girlfriend and me, our electric and gas bill doubled. Our weekly food-shop followed a similar trajectory. So did the car insurance, house insurance, Netflix subscription, internet — leaving the monthly budget we pored over on the dining table blown up within 12 months of moving in.

We were both professionals, with great jobs and the finances to shoulder it. But if we felt squeezed, I couldn’t understand how others were getting by.

I worked at Asda from school until the end of university. Plenty of other students worked there too, but many of my colleagues did it full time. Simon, an older gentleman, worked the freezer. He hauled ice-white cages to and from the shop floor. Ubi manned the fruit and veg, always a wry smile and a compliment up his sleeve ready for the next older lady walking by.

Most of my colleagues were paid hourly — a sliver above minimum wage. How were they supposed to stomach these increases? A 10% employee discount card on their groceries doing little to offset the fact that food prices are 40% higher now than the early-pandemic.

Inflation never mattered much to me, until it did.

A clearer realisation came in late 2022 when our next door neighbours sold up and moved. The buyers paid £25k more than we did 12 months prior — for a house two-thirds the size. Meanwhile, stock markets, gold and a multitude of other assets would double or triple from the COVID lows.

My neighbours’ house wasn’t worth more because it was better. What I came to understand was that it was worth more largely because the money used to buy it was worth less.

Eat Out to Help Out. Furlough. The evidence was right in my face. During the pandemic, governments spent at a scale not seen outside wartime. This money had to come from somewhere, so trillions were created. More money in the system meant more competing for housing or groceries. Because it was worth less, you needed more to pay for the same items.

When I say ‘created’, the Bank of England purchased government debt using money that didn’t previously exist. This flowed into financial markets, buoying asset prices like my neighbours’ house, and in time into everyday items too.

I stopped thinking money was mismanaged and started suspecting that it was broken.

We don’t build enough housing in the UK. It’s a scarce asset, which is why, when the money supply expands, it shows up on Rightmove, and in how hard it is to get a foot on the ladder.

Bitcoin emerged as my answer to that.

Unlike the pound in your pocket, there will only ever be 21 million Bitcoin. I discovered it in late 2023. At the time, I saw it as a financial hedge — a scarcer asset repricing in a world of expanding money. Over the following two years, it moved sharply higher.

During this time, I lived on a ‘Bitcoin standard’. Each month as I was paid, I’d meet my proportion of the monthly budget, clear my credit card and convert the remainder of any savings into Bitcoin.

My bank account read £0 most days of the month.

It sounds crazy, operating like that. But it had the opposite effect: anchoring me.

Having a fixed point to organise my finances around, and in time, my life, brought a focus that I didn’t have before. Learning more about it opened me up. I started seeing things differently.

My girlfriend and I could pay more for our food shop, or to have the heating on. I thought about the predicament for people like Ubi, or Simon, working honestly and just as hard, for less. It made me feel resentful. Gutted. Knowing that money is created, benefiting those with assets, while widening the gap for those without that to fall back on.

I stopped viewing Bitcoin as a financial bet and started treating it as a principle to live by. For the first time, something to believe in.

This is all quite easy to say when you’ve got a decent job and the certainty of being paid at the end of the month. I resigned from that job in October 2025, and in the three months of my notice period, Bitcoin lost 20% of its value. A further 25% in the January and February that followed.

I’d built a buffer to start this next chapter — never enough to watch it happen without feeling it.

It’s why I’m writing this at a Bitcoin price of $67k, not $120k. Because I could be wrong. I don’t think I am, but there’s no falling back on a corporate job now. I’m onwards or bust.

It’s uncertain, like the world. I do, however, have conviction in something finally. And there’s a steadiness in that. I’m not back at university parroting the books I read or the ideas of philosophers I never met, or working a job that towards the end my heart was never in. I want to think aloud. Process things as much for myself as for anyone else.

I found belief in something most think is a speculation. It feels bigger than a financial position. Not just for me. For anyone whose money and value is being diluted.

It isn’t a one-way journey. I’m learning that it demands something back.

In return, it gave me the first thing I’ve genuinely had to live up to. And the courage to begin.

He now has a window to shore up before the Gorton and Denton by-election, scheduled for 26 February, and then local elections on 7 May.

These two moments are de facto votes of confidence: judgement days on the current administration and Starmer’s leadership.

Diane Abbott MP, who was stripped of the Labour whip, put it bluntly:

“I can’t see him lasting beyond May’s elections…because they’re going to be catastrophic elections. And I think the idea is let him stay in there and take responsibility.”

Starmer may fight it out till the spring, but between now and then, the focus remains on his effectiveness as leader - endangering the process of government.

Formal business continues. Ministers will still appear on the morning media round. PMQs will go ahead. But meaningful government stalls as attention turns inward.

Whatever you think of ex-Conservative minister Jacob Rees-Mogg, his monologues published on YouTube provide an insight into the situation Starmer finds himself in. He lived it twice, with testimony from inside the bunker as Boris Johnson and Liz Truss navigated crises that would result in the end of their time as prime ministers.

“I had a ringside view of what was happening and the same thing is playing out now,” said Rees-Mogg in a video this week. “The formal things happen, but the business of government stops. I mean the evolving of policy, the decision making, the ability to push things through. This stops.”

In a co-ordinated response to the Anas Sarwar press conference and pressure on Starmer to resign, each member of the cabinet came out in defence of the prime minister. The damage had already been done though. As Rees-Mogg explains:

“You look at what is going to happen and recognise that actually, it’s not. If you’ve got a big policy initiative that you would like to push forward, you know that in reality things are about to change and therefore however strongly you believe in it, it won’t happen with the leader that you’ve got.”

“You’ve got the distraction, you’ve got the recognition in your own heart that you’re not going to do these things…And you’ve got the civil service effectively downing tools, not necessarily malevolently, but recognising that it simply isn’t going to happen.”

We should take Rees-Mogg’s words with a hefty pinch of salt. We are a long way off the chaos seen towards the end of Boris Johnson’s tenure, where at its height 62 government and party figures resigned. Starmer still has a functioning cabinet.

This certainly hasn’t stopped those in senior Labour positions spending bandwidth warming up for a potential leadership battle.

Duplicity and political ruthlessness also described by Rees-Mogg:

“You have people who swear blind loyalty to the leader who you know perfectly well have been briefing against him to the newspapers or are working on a campaign to get somebody else elected.”

Starmer may be there as PM to feel the warmth of the May Day sunshine. The point isn’t whether he goes. The fact that we’re even discussing this reveals the freeze already underway. As this week shows, the government is easily put off course while waiting for a verdict on its leader.

I wrote in January how government policy globally was becoming desperately reactive, with presidents and prime ministers lurching to prevent collapse rather than building coherent strategy.

The UK now finds itself further along this trajectory: velocity → reactivity → paralysis.

We can’t afford months of paralysis. The accumulated cost is too high. Economic challenges in particular must be tackled now, not in a quarter’s time: the difference between a business investing and hiring, or pausing plans.

With just 0.1% GDP growth eked out in Q4 2025, the margin is narrow. Any drift could be enough to turn weak positive growth into contraction.

Imagine your roof is leaking. Water pouring in. Instead of fixing it, you think: I’ll wait for it to stop raining. Spring will be here soon.

In the meantime, your home and belongings are ruined.

I’d say look at the forecast, but as we all know, the rain isn’t stopping any time soon.

The only worse outcome than having the “wrong person lead” is months of nothing. The country doesn’t have the luxury of waiting. Stasis, in the hope of a sunnier day.

Written by Lewis Thomas

Written by Lewis Thomas

After three essays on what's breaking, a look at what individuals can now do about it.

My first three Orientation essays were moody.

They weren’t written to be pessimistic, but rather reflect reality: how business risk in the UK is being pushed downward, hamstringing smaller firms, and why our political leaders are becoming increasingly erratic in response to fiscal pressure. There was also a more exploratory piece, inspired by my experiences with AI memory, and the development of systems that don’t forget.

It would have been easy to follow in the same vein again. Not least considering the corruption laid bare this week within British politics and ‘high society’.

But diagnosis without response is just commentary, and the more honest reaction to institutional failure isn’t outrage. It’s to create.

Cynicism also misses the bigger picture unfolding - that we’re in a pivotal moment where the boundaries of what one person can do are being reconfigured and we don’t yet know where they will stop.

Part of what’s destabilising centralised institutions like governments and big business is that the capabilities once associated with scale – resources and financial backing – no longer depend on it. Instead, individuals are now being equipped with powerful new technologies, increasing access to knowledge, skills and networks at a cost that would have been impossible a generation ago.

Where these lines cross, individual action is becoming a powerful opportunity. Not in a heroic, let’s fix all the failing systems kind of way, but a human response as individual capability - to build, create, and solve problems - rises.

This decades-long transition, set in motion by collapsing coordination costs, is accelerating.

In 1990, an international phone call cost more than a pound per minute. Now billions coordinate across borders for effectively nothing. Expensive and slow dial-up home internet now operates wirelessly at hundreds of megabits. Geography is no longer a barrier to collaboration and the economic impact is material: startup costs fell from $5 million in 2000 to under $50,000 by the 2010s. Capital-intensive infrastructure – office space, physical servers, telecommunications – is optional following the development of online systems.

Fundraising has followed a similar pattern. Crowdfunding platforms can bring together large numbers of small backers with founders they may never meet. In the UK, crowdfunding has helped finance over 2,500 companies, including Black Sheep Coffee and digital bank Monzo.

Tools have also become more affordable and accessible.

A smartphone can now function as camera, editing suite and distribution channel - allowing users to capture content and circulate it in minutes.

One of the most important developments has been the growth of open-source software. As a result of the ingenuity and graft of volunteers, infrastructure that was once proprietary and expensive is available to all, often for free. Take Linux, an operating system built by the open-source community, now underpinning Android and running the fastest supercomputers.

The latest stage that we’re currently witnessing is the democratisation of knowledge.

This began with the internet and the emergence of platforms such as Wikipedia and YouTube that function as interactive, continuously updating shared archives. Wikipedia alone hosts millions of articles. My latest rabbit hole is reading about the Klondike Gold Rush, and the journeys of prospectors over the Chilkoot Pass toward boom towns like Dawson City or Skagway - the latter infamous for its lawlessness and economy of drink, gunfire, and prostitution.

Formal education has also found a home on the internet.

The Open University, founded in 1969 as a distance-learning experiment reliant on broadcast media and postal services, delivers the bulk of its teaching online and has educated more than 2.3 million students worldwide.

All of this change has come with the ability to actually do things, not just read about them.

Platforms like GitHub are allowing developers worldwide to share solutions to problems in real-time, learning by doing rather than through formal credentials.

During the ventilator shortages of early COVID-19, open-source designs circulated online within days: makers were able to build functional devices in weeks, while official procurement channels were stalled.

These forces - coordination, tools, and knowledge - are currently converging through artificial intelligence. For less than the cost of a round of pints, an individual is today able to access capabilities that once required years of education, specialist support or significant resources.

Whether researching, writing, coding, or analysing, AI introduces a new dynamic. The work still requires judgment and direction; technical knowledge helps, but the threshold has fallen so that someone can learn basic coding concepts and generate functional code in the same session.

The capability gap between individual and institutions is narrowing measurably.

For solo entrepreneurs and small teams, it levels the playing field. Not guaranteeing success by any means, but giving them new ways to compete.

I left a corporate role recently. It was a large law firm, and was forward-looking when it comes to AI. While it had even introduced AI-usage metrics tied to the firm’s bonus structure, adoption was patchy and mainly limited to CoPilot. A different world to what’s being built outside those walls, led by agile, lean teams with less to protect and more to gain.

Industries such as law will take longer to disrupt. The strict regulatory conditions, complexities and nuance of legal matters require the expert input of humans, and for good reason. Those with less of a technical moat are, however, under pressure.

We are already seeing this in the software ecosystem, where the share prices of giants such as Adobe and Salesforce are sliding.

More than $950 billion of market capitalisation was recently erased from the S&P 500 software and services group. No doubt some of this is overdone, but it shows how the thinking is changing - at least in the mind of investors - and that in a world where an experienced coder can call on the support of simultaneous AI agents, the time and cost involved in creating software is lower.

Companies that once outsourced everything to enterprise software vendors can now build more of it themselves - tailored, cheaper, and increasingly viable.

There’s talk in Silicon Valley of billion-dollar solo companies - one person, no employees, built entirely on AI. It isn’t impossible now that the gap between having a vision and being able to test it has never been smaller. We’ll still fail as fast; success hinges on how good the idea is, but finding out may no longer require a large team or millions in venture capital funding.

AI’s impact on business is front of mind, but its reach will extend to other realms, altering politics and public policy. This includes potentially supporting new kinds of civic action that previously most people never get around to pursuing, not because they didn’t care, but because turning concern into action felt impractical alongside a day job, bills, and limited spare time.

We caught an early signal of this in January with the launch of ismypubf---ed.com.

Concerned about the impact of potential business rate increases on Britain’s pubs, Ben Guerin decided to do something about it. On his commute, Guerin came up with an idea for a website that would highlight the impact of the rates, which to some pubs would have been last orders.

He shared the plan with Claude Code, using publicly available Valuation Office Agency rateable value data. Running in the background, hours later the site was live: a colour-coded map of 46,000 pubs, searchable by postcode, estimating how severely each one was affected.

For the Queens Arms, one of my locals, the website showed that the pub’s rateable value could have increased 107%, giving it an FPI score of 62/100. Otherwise, f*cked.

While Guerin has a developer background, this shows how AI could be the difference between a project getting off the ground or not. In this case, it did. The website recorded more than 400,000 visits, circulating widely on X and Reddit, and earning the support of publicans countrywide.

Amid wider industry pressure, the government announced a support package days later. Whether it saves those pubs facing extreme rises remains to be seen. But as a result of one person, one tool, and one idea, 46,000 pubs suddenly had a public advocate they didn’t have before.

For those building using these new tools, platform dependency hasn’t gone away. A creator on YouTube is beholden to changes to the algorithms and monetisation. The developer using ChatGPT to create an app faces Apple’s tax. Substack takes a slice from its writers’ subs.

Just because the playing field is being levelled doesn’t mean it’s now fair. But even here, alternatives are emerging. Nostr is proof of that: an online protocol that is manifesting as a type of decentralised social media with no owner or default algorithm.

Those on Nostr have the ability to send ‘zaps’ - the equivalent of micro-payments using Bitcoin.

This enables creator-to-audience and business-to-consumer payments that bypass platform middlemen. Learn something from a video? Zap them. Need help debugging a website? Zap them. Personal trainer? Zap them. You pay the person, not the platform hosting the exchange.

Nostr is far from mainstream. Most creators and businesses still rely on traditional platforms. Its emergence does show it’s possible and that the infrastructure for peer-to-peer, value-for-value exchange is being built. Whether it scales depends on whether people choose to use it.

Not everyone will take this path. And that’s fine. Some people prefer steady jobs and the structure and security that comes with it. I know, I’ve been there.

For people, however, that have that niggling feeling and an idea that they’ve been putting off, perhaps for fear of not knowing where to start, or the belief that they don’t have the financial means, or the technical skills and knowledge to build it, the conditions are changing.

The arrival and continued development of AI could remove some of what has been standing in their way, turning the question from ‘should I try?’ to ‘why not?’

AI won’t make failure any less painful. It may even make it more difficult to stand out by increasing competition. The disruptors will disrupt the disruptors. This dynamic has always existed though; those driven to try something will do so, regardless of the odds.

The old certainties - that a particular route would hold, that institutions would do what individuals couldn’t - no longer apply. The systems we are used to are being contested by the tools now available to anyone willing to use them. The result isn’t a world with fewer failures, but one with far more attempts.

For those paying attention to what’s now possible, the response is to try to create.

Written by Lewis Thomas

This is January 2026. Not an exceptional month, nor cherry-picked chaos, but so far 27 days of continued global volatility:

The United States captured Venezuela’s Maduro in an overnight raid. Trump threatened tariffs over Greenland, then walked them back days later. Multiple governments shut down the internet amid unrest. Japan’s bond yields surged as elections were called. UK gilt yields rose amid renewed political uncertainty. France survived its latest no-confidence vote.

These aren’t random disruptions, taking place in different timezones or continents. They are interconnected: each political, economic or social rupture creating the conditions for the next one.

Shared financial constraints, hypersensitive markets, and fragile political legitimacy mean these shocks no longer dissipate; they transmit.

Previously, this systemic breakdown emerged as a series of ‘temporary’ crises spread across years. We’re now compressing that pattern into weeks, and the equilibrium can’t be restored between shocks. And the month isn’t even over.

Speaking at Davos 2026, Bridgewater’s Ray Dalio was clear in his assessment:

”The monetary order is breaking down. What I mean is that fiat currencies and debt as a store of wealth is not being held by central banks in the same way. And that there was a change. The biggest market to move last year was the gold market, far better than the tech markets and so on.”

Dalio’s statement is cutting. It gets to the crux of one of the foremost issues we are facing: the indebtedness of our governments.

The US holds $38 trillion in debt - more than its annual GDP. Japan’s debt-to-GDP ratio sits at 230%, twice the US level. In the UK, more than £1 in every £12 of government spending goes to servicing debt interest payments alone.

Countries are currently moving through predictable stages:

• Hedge finance: Cash flows cover all obligations (principal + interest)

• Speculative finance: Cash flows cover interest only; must refinance principal

• Ponzi finance: Cash flows insufficient even for interest; survival requires rising asset prices or continued borrowing

For most governments, we are now moving from speculative finance, to the Ponzi finance stage, where a drawdown in asset prices is damaging to individuals, and structurally destabilising for governments.

This isn’t a literal equivalence - sovereign states can tax and print money - but the underlying logic is familiar: when obligations outpace organic cash flows, stability becomes contingent on confidence, asset prices, and continued refinancing rather than resolution.

As part of a global market sell off, the S&P fell 2.1% after Trump’s Greenland threats and EU tariff announcement. A modest decline, but as asset prices fell and the potential impact on pensions and portfolios became visible, he reversed course within days - consistent with Ponzi logic: policy responding to prevent a further cascade.

Entering this new territory means politicians face the choice of either allowing a bigger debt crisis to unfold, or postponing it through currency debasement.

These two deeply unattractive choices continue to be played out globally.

The evidence is materialising through long-dated bond yields rising even as policy remains accommodative, with central banks also continuing to increase gold holdings and talk openly about diversification away from dollar concentration. Some investors are also seriously treating bitcoin as an alternative hedge.

As this month shows, policy is becoming desperately reactive, with presidents and prime ministers lurching to prevent collapse rather than building coherent strategy.

And we’re watching it happen in real-time.

What is novel about the current situation compared to the past isn’t just the speed of these shocks or the corresponding reactions, but the extreme visibility of them happening.

Historically, this breakdown was conveyed, even mediated, through gatekeepers. Some of these were logistical: the newspaper was delivered once a day, the evening news didn’t start till 6pm.

Others were more structural. A journalist, their editor, even a newspaper’s ownership may have dictated what stories you saw, and more importantly, how they were told.

These buffers are now disappearing.

The democratisation of information means there are fewer filters between current events and global awareness. Anyone can now document and discuss the breakdown in real-time.

This visibility is a threat to economic and political power.

When the online feed is infinite and ungated, governments have one tool left: kill visibility itself.

We’ve seen this censorship twice already in January.

Iran has entered its third week of internet blackout - one of its most severe - as protests against the Islamic Republic intensified. Uganda also suspended internet access two days before its general election as President Museveni sought a controversial seventh term.

This month gives us a glimpse of what escape velocity looks like, where traditional systems struggle to pull themselves back from the brink: governments under pressure to pay back the interest on their trillions in debt. Central banks diversifying away from the currencies they’re meant to defend. Presidents reversing policy within days because markets can’t tolerate even modest corrections. Regimes shutting down the internet because visibility itself has become destabilising.

Previous generations experienced systemic breakdown through curated retrospective narratives, or if in real-time, through editorial filters. We’re watching this one with full, unmediated visibility.

Written by Lewis Thomas

One of life’s quieter comforts is walking into a familiar pub and being met without pause. No scan of the taps. Just a nod, a grin, and “the usual, right?”

Your face is recognised. There is a thread of continuity - a sense that something about you has been carried forward since your last visit. The same feeling surfaces when you meet an old friend after years apart and find the conversation resumes without effort. It is easy to pick up where you left off, not because everything is remembered, but because enough of you is.

The expectation of continuity no longer stops at people or places. It’s beginning to appear elsewhere. We notice the irritation when we’re made to start again: to restate context, re-explain aims, rebuild a trail we thought was already there. The friction is felt as inconvenience or wasted time, alongside a sense that something which could have been held, wasn’t.

This type of discomfort isn’t new. Long before modern technology, thinkers recognised that our understanding hinges on memory - on the ability to draw on past experience and carry it into the present. As John Locke argued centuries ago, what makes you you over time isn’t your body or your intelligence, but the string of memory linking past experience to the present. Without that, each moment would arrive as if for the first time, disconnected from what came before.

“as far as this consciousness can be extended backwards to any past action or thought, so far reaches the identity of that person; it is the same self now that it was then…” An Essay Concerning Human Understanding, Book II, Chapter XXVII

The change now is where that continuity is showing up - beyond the normal bounds of human relationships, in systems that carry it across time and space.

Artificial intelligence is rewriting memory in silicon. While many systems have been able to store information previously, AI takes this a step further, using memory actively to shape the present through what it retains. Past interactions with a user don’t just sit in a record; they can feed back into how the system responds, allowing understanding to accumulate rather than reset.

Until recently, interacting with most AI meant starting from near-zero each time. Every conversation was treated as a first encounter. Close the window, begin again. Whatever had just happened was gone. The system could generate remarkably fluent and in-depth responses, but it carried no sense of you across interactions. Context did not persist; each exchange stood alone.

That is beginning to evolve. Some systems can now carry elements of context forward - not comprehensively, not reliably, and not yet with much subtlety. However, even this partial continuity introduces something new. Interaction stops feeling like repeated querying and starts to feel like the resumption of something already in motion: fragmented, but ongoing.

A system that remembers you feels less like a tool and starts to function as relationship infrastructure, building understanding over time, rather than simply retrieving or storing facts.

Persistent memory is powerful because it changes the nature of the interaction.

Over time, it creates a continuity that goes beyond intelligence alone. Patterns accumulate. Context thickens. Connections can emerge. Sometimes this is deliberate and prompted, sometimes it’s without the user noticing them being made.

For me, this persistence has emerged in small but meaningful ways.

I was born with osteogenesis imperfecta - a genetic condition that affects bone strength, and shapes everyday decisions. It’s the kind of constraint that usually has to be carried internally, or explained repeatedly: when thinking about exercise, equipment, recovery, or diet.

As AI systems begin to retain context, even in a limited way, something subtle changes. I no longer have to restate or reframe the condition each time it’s relevant. It’s already there - held in the background - and can surface naturally when decisions are discussed. This helps with optimisation, but it also provides the relief of not having to explain yourself every time.

This kind of continuity improves individual exchanges. It also allows a system and its user to hold threads together over time. Through this broader context, choices can begin to make more sense. The result isn’t certainty or direction, but greater coherence.

Human memory, by contrast, has never worked this way.

Our remembering is partial and reconstructive. We piece together the past from small glimpses, shaped by what we already know and expect. Much of what we experience is forgotten, and even what remains is rarely an exact record of what happened.

This imperfection is not a flaw. It’s part of how memory works for humans. It’s adaptive, selective, and alive to the present rather than completely faithful to the past. We understand this intuitively, so it is not a surprise when we misremember or disagree about details.

Memory’s closeness to identity is what makes it so intimate. Our past experiences shape how we respond, what we notice, and who we become. That intimacy is also why the loss of memory is so devastating. As the past disappears, so does a part of who we are.

Forgetting also serves an important function. By allowing details to fade, our minds make room for what matters, letting the past inform the present without overwhelming it.

Sometimes this can be deliberate rather than accidental. Forgiveness, for example, depends on the ability to loosen the grip of a memory and to allow what happened to recede, even if it is not fully erased. The same is true when we forgive ourselves.

We all carry experiences we would rather not relive in full: mistakes, losses, moments that last longer than they should. If every memory remained vivid and permanent, there would be little space for healing, peace, or reinvention. Forgetting is what allows life to continue without being endlessly replayed. It makes life liveable. We forget because we must. For the sake of our mental and physical health, and to allow identity to remain fluid, rather than fixed.

A system designed and incentivised to retain information indefinitely does not forget in the way humans do. It does not prioritise, reinterpret, or wane with time. Memory, in this case, is not shaped by limitation.

The development of this kind of memory tips the balance between human and AI. It alters the relationship, shifting trust from something felt to something structural.

In human relationships, trust is provisional and internal. It’s built through shared experience, adjusted over time, and withdrawn when something no longer feels right. You trust a friend, but can still hesitate. You trust a professional, but may seek a second opinion. Trust lives in judgement.

With persistent AI memory, that judgement changes shape. The system already holds your history. You may not be able to fully verify what it remembers, yet its memory shapes the interaction before you act. Participation assumes trust, because continuity depends on it. Understanding accumulates within a memory system unconstrained by natural limits. The user, in turn, becomes reliant on how that memory is recalled, interpreted, and brought into the present.

Reliance can also emerge more explicitly.

As users increasingly rely on AI systems to act as memory, the incentive to remember for themselves weakens. A similar process appears to have played out with the proliferation of mobile-phone GPS. These tools did not make people worse at navigating overnight, but they slowly changed how often people tried. Routes once learned became routes followed. Orientation shifted from internal knowledge to external instruction. Memory, outsourced, slipped out of use.

Persistent AI memory introduces a similar dynamic. As the system gathers context, history, and preference, the user is freed from holding those threads alone. The question is not whether this is useful - it clearly is - but how much remembering we are willing to give up in exchange.

As the cost of data storage has collapsed, remembering has become the default. It is now often cheaper and easier to keep information than to decide what to discard.

In that environment, memory stops being a choice and becomes a cumulative process. Data is kept not because it is immediately useful, but because it might be. What can be remembered, increasingly is.

Systems not bound by human limits can drift toward unified memory. A single, continuous record can span decisions, preferences, conversations, and contexts across a person’s life. The more complete that memory becomes, the more useful the system appears - able to recognise and anticipate needs, and personalise responses with increasing precision.

Continuity also carries economic weight. A system that remembers more feels harder to leave, not through coercion, but because starting elsewhere means starting again.

Unified memory can retain and recall even minute details, and does not forget in the way people do. It does not soften experience with time or allow earlier versions of the self to loosen their hold. Where human memory is selective and fleeting, unified memory remains intact.

While bringing undeniable power and potential, it is unclear whether a form of remembering optimised for these systems can peacefully coexist with life that depends on letting things go.

There are already situations where we entrust our most intimate memories to others.

Doctors, therapists, and lawyers routinely hold our personal histories, vulnerabilities, and even confessions - often formally recorded, but deliberately contained. Those memories are bounded by domain, shaped by professional duty, and protected by norms that acknowledge their power.

Something similar is beginning to take shape with AI systems.

Through repeated interaction, they can assemble a working sense of who someone is over time. That picture may become more encompassing than the one held by any single professional.

AI systems may come to hold information as intimate as that shared with a doctor or therapist, but they are not bound by the same ethical or institutional duties. These conversations lack those kinds of professional privilege and are not governed by norms that define responsibility, confidentiality, or restraint. This is both a privacy concern and an ethical gap: memory entrusted, without a corresponding obligation to protect it.

This gap is not theoretical. Even those building these systems acknowledge it.

Speaking on Theo Von’s This Past Weekend podcast, Sam Altman put it plainly:

“People talk about the most personal [shit] in their lives to ChatGPT. People use it as a therapist, a life coach. Right now, if you talk to a therapist, lawyer or doctor about those problems, there’s legal privilege for it, there’s doctor-patient confidentiality, there’s legal confidentiality. We haven’t figured that out yet for when you talk to ChatGPT. If you go talk to ChatGPT about your sensitive stuff and there’s a lawsuit, we could be required to produce that. I think that’s screwed up.”

Historically, sharing memories has been a privilege based on friendship or duty. With AI, memory is arriving first - ahead of obligation, protection, or defined responsibility. This sequence matters.

We are now entering a future where the past is more concrete.

Memory may no longer fade by default. It can be retained, recalled, and reintroduced with accuracy - offering coherence, clarity, and a continuity that humans have never been able to sustain alone. But this clarity comes without the limits that once shaped it. Forgetting is no longer guaranteed. Distance from the past is no longer automatic. And the process through which we move on from who we were - and discover who we are becoming - is less certain.

Being remembered is a relief, until remembering stops knowing when to let go.

If you’d like to follow the thinking as it develops between essays, I occasionally write in public on X via @OrientationFrom and Nostr via @Orientation.

Written by Lewis Thomas

Despite years of policy intervention, the conditions required for people to take risks - and to fail safely - have been weakening.

Since 2020, the UK Parliament’s official record shows more than 4,000 uses of the term “high street” across debates, questions and committee proceedings. A simple, stark measure of how persistently these social and economic spaces have occupied Westminster.

This attention matters not because high streets are symbolic, but because they are everyday places where policy decisions intersect with the lives and work of ordinary people.

Governments of all stripes have spent years layering intervention upon intervention: from the 2011 Portas Review and early innovation funds, to the Future High Streets Fund and Towns Fund, statutory powers and investment through the Levelling-Up and Regeneration Act, High Street Rental Auctions, and most recently Labour’s Pride in Place programme.

And yet despite sustained attention, multiple reviews, and billions of pounds in targeted funding, many UK high streets, town and city centres are in visible decline.

Using the most recent data available, Centre for Cities shows that in places like Newport, Bradford, or Stoke, vacancy rates sit close to 20% - meaning one in five shopfronts stands empty.

Even the lower national average of around 13% tells its own story.

On a typical British high street, roughly one in every eight units is closed: shutters down, or windows polished into slow circular swirls that keep the space presentable while concealing the emptiness inside; “To Let” signs lingering longer than the property agent intended.

The pandemic brought this fragility into the light of day, compressing years of pressure into months. For businesses operating on thin margins, this exogenous shock - and its secondary effects, from collapsing footfall to accelerated behavioural shifts - pushed them beyond viability.

Longer-running secular trends also continue to reshape the high street. Chief among them is the steady expansion of online retail, which now accounts for around 28% of all retail sales in the UK. This share jumped during the pandemic and has since stabilised at a materially higher level.

The combined effect of the pandemic and the shift online has been to permanently alter the economics of physical retail, in particular.

Brick-and-mortar businesses are now competing for a smaller share of discretionary spend, fragmented across online platforms, out-of-town retail, and experience-based consumption. While demand has not disappeared, it is thinner, less predictable, and less anchored to physical place.

For high street businesses, this matters because their cost base has gone the other way.

Wholesale energy costs for UK businesses spiked dramatically in 2021–22, with electricity prices rising sharply and gas prices more than doubling at their peak. Both remain materially higher than pre-pandemic levels. Labour costs have also risen, with the National Minimum Wage increasing repeatedly and, under current plans, set to be uplifted again later in 2026 to £12.71 an hour.

Raw materials show similar upward pressure: global coffee bean prices, for example, reached near multi-decade highs in recent years.

For a small coffee shop, that amounts to a triple squeeze - paying more for beans, more to heat the premises, and more in wages - all while competing for a consumer that is also under pressure.

The instinctive response to these strains is to reach for further policy levers: new, but often the same played-out incentives, targeted funds, or regulatory tweaks designed to revive local enterprise and footfall. The sheer volume of parliamentary debate and successive initiatives over the past decade suggests concern - and perhaps misdirection - rather than neglect.

And yet the ongoing deterioration of our urban centres and high streets points to a deeper, more unsettling problem.

Repeated intervention has struggled because it continues to treat the high street - the heart of our towns and cities - as a retail, leisure or property challenge to be managed, rather than as a risk environment in which people decide whether it is worth starting, or sustaining, something at all.

It is not just a question of symptom management, focusing on addressing footfall or funding, but of confidence: the belief that opening a café, restaurant, shop, co-working space, or pub is a risk worth taking, and one that will not be unfairly penalised by forces beyond the owner’s control.

This uncertainty for existing and prospective small business owners continues to be bred by a policy and economic framework that pushes financial volatility and operational burden downwards - away from institutions and onto the smallest actors least able to absorb it.

Recent reforms to UK employment law and labour protections offer a clear example.

Many of these changes have been introduced for legitimate reasons, strengthening worker security, reducing exploitation and expectations around fairness at work.

For a small business on the high street, however, labour is no longer a flexible resource but a fixed commitment. Higher minimum wages, increased employer national insurance contributions, changes to holiday pay rules, and more formalised dismissal processes all raise the cost and administrative burden of taking someone on. None of these shifts are inherently unreasonable. But together, they alter the risk calculus dramatically and can make it harder to run a small business.

The tension is not between fairness and exploitation, but between systems designed for scale and environments that depend on operational flexibility and small-scale experimentation.

A 20-cover restaurant that may once have relied on seasonal, flexible student staff is now expected to manage employment risk through the same processes as larger chains, which can spread these fixed administrative and compliance burdens across many sites and staff, often with in-house specialists; for a single-site restaurant, the same rules demand the same time and expertise, diverting scarce time, money and attention. It’s a mismatch.

In an environment where demand fluctuates and margins are slim, these changes are reducing the room to experiment, adapt, or recover from small mistakes.

The result is predictable: fewer hires, shorter hours, delayed expansion - or the decision not to open at all. It’s why so many units remain empty, devoid of economic lifeblood.

Recent surveys from bodies like the Federation of Small Businesses and British Chambers of Commerce reflect this, with small employers frequently citing rising labour costs and new employment protections as among the top barriers to expansion or even maintaining headcount, contributing to subdued hiring intentions into 2026.

Another way this asymmetry of risk shows up is in how fixed costs are imposed on high street businesses, mostly regardless of performance or demand.

Business rates, for example, do not flex automatically when footfall falls or margins compress. Levied on shops, pubs, cafés and other premises, the tax is based on location and property value, making it one of the largest fixed costs many high street businesses face.

Reform of the business rates system has long been debated as a potential tool to ease pressure on smaller operators. Yet in practice, relief has tended to be temporary and conditional, rather than structural. With pandemic-era support schemes now unwinding and the next revaluation cycle due in 2026 - based on 2024 rental values - some high street businesses face the prospect of higher rateable values irrespective of where we are in the wider economic or consumer cycle.

That disconnect became particularly visible earlier in January for pubs, where planned changes threatened a cliff-edge moment for already fragile operators. The government’s subsequent reversal softened the immediate impact, but it also underscored the issue: a system that is politically charged, reactive, and difficult for small businesses to plan around with confidence.

Focusing primarily on treating the visible symptoms of this system has left permanent scarring for business owners and those considering starting a new venture. Official business data shows that business deaths have often outstripped births since 2020, resulting in a net loss of nearly 15,000 enterprises UK-wide - a reflection of the heightened downside that deter new businesses.

The data captures the businesses the UK has lost. The more revealing damage lies elsewhere: in the number of people who would like to take space on a high street and start something, but decide not to. The most consequential losses are no longer the closures we can count, but the attempts that never happen - deterred by a system that is rigid and difficult to navigate, and where failure is not a reversible chance for learning, but a swift, public, and financially and psychologically difficult experience to recover from.

The absence of new ventures is most visible in the units that remain vacant, but its effects extend well beyond empty shopfronts. High streets are not just economic corridors; they are social and civic spaces shaped by daily presence and routine activity. As legitimate activity dwindles, those spaces become less predictable and more vulnerable to antisocial behaviour and crime.

In England and Wales, police-recorded shoplifting offences hit 530,000 in the year ending March 2025 - the highest level since current recording began. This is no longer peripheral behaviour. It has become part of the everyday experience of town and city centres: alarms sounding, security staff intervening, and a sense that public space is less orderly than it once was.

Bedford offers a useful case study in how local confidence collides with national constraint.

Peter McCormack, a Bedford-based business owner, previously funded a private security pilot in the town centre after opening a café and witnessing, in his words, the scale of disorder “when you sit there all day.” The initiative involved hiring licensed security staff at a cost of around £10,000 per month, funded privately, with the aim of restoring visible order and making the high street more safe and accessible again for families and small businesses.

For a period, the intervention appeared to work. Shopkeepers reported feeling safer and footfall improved on pilot days. But speaking more recently on What Bitcoin Did, McCormack explained that he had stopped the effort. “So I gave up,” he said, concluding that the problem was no longer local. “I realised it didn’t matter what I did in Bedford - everything is downstream of central government.” In the same discussion, he described deciding not to proceed with opening a further business - a pizza restaurant - despite having capital available. As he put it in an earlier podcast:

“I’ve got money on the side now, ready to open more businesses in the town, and I’m sat there going, I don’t know if I can turn a profit here because of government.”

McCormack’s experience is revealing because it is not one of inexperience or risk aversion. Alongside his other ventures, he has overseen successive promotions with football club, Real Bedford FC - a capital-intensive, operationally complex project with uncertain returns. And yet even individuals willing to take on that level of financial exposure are now choosing not to extend themselves on the high street. The decision not to open another business is not a retreat from enterprise, but a response to a set of conditions that no longer feel proportionate or navigable.

Our high streets now expose not just decline, but the erosion of confidence in the act of trying. Not just for well-resourced serial entrepreneurs, but for first-time founders and small operators deciding whether to take space and test an idea. Confidence is not built by just protecting incumbents or endlessly refining support schemes, but by resetting the risk environment itself - ensuring a new business can fail without becoming a financial, legal or reputational catastrophe.

Until the asymmetry eases, where the downside of trying feels proportionate to the upside, every vacant high street unit will continue to stand as quiet evidence of risks not taken: not just closures we count, but the ventures, experiments, and small acts of confidence that never begin.

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