1. Mariana Mazzucato wants to fix economics

Celebrity economist Mariana ‘mission-driven’ Mazzucato and Spain’s Deputy PM have launched the Global Council on New Economics for the 21st Century, a sort of constitutional convention for the field. It aims to give the discipline a wake up call.

Picking Spain is smart - it’s the top performing European country currently, and having a moment. Economics hasn’t actually fared very well as a tool for stability and rising living standards since the 1980s. The Council’s beef is not with markets but with the orthodoxies treated as physics: that they self-correct, that governments should stand back, that growth trickles down. Drawing on Mazzucato’s forthcoming book, The Common Good Economy, the body will interrogate eight cross-cutting assumptions, from what we measure to who governance serves, with reform proposals due autumn 2027.

The So What: Economics is overdue for a reckoning. This could force it justify its assumptions, and impacts.

2. Maybe stress is killing you after all

For years, I’ve been a happy believer in hormesis, the idea that mild stress makes you bounce back stronger. From Nietzsche to David Sinclair, this appealing idea was one of the reasons why I suffer cold showers and try to have a fast day once a week. It also makes me fret less about doing too much and living on caffeine-fuelled deadlines. That rather satisfying idea may be up for question.

A new University of Sheffield study suggests the opposite. By manipulating the Integrated Stress Response (ISR) in tens of thousands of fruit flies, the team found that suppressing the GCN2–ATF4 axis, not activating it, extended lifespan robustly, even under dietary stress.

Chronic ISR activation, by contrast, shortened lives. The findings complicate yeast and C. elegans orthodoxy and reframe ISR as a pharmacological target for healthspan, not just disease.

The So What: Aging biology keeps humbling its own dogmas. Hormesis as a theory is coming under stress - let’s see if it bounces back stronger.

3. Mapping planetary intelligence

Geoff Mulgan often appears in this newsletter, as someone who is consistently both novel and bold. He hasn’t got the memo about staying in your lane. His latest paper for the Royal Society’s Philosophical Transactions, argues that humanity’s biggest challenges, from pandemics to climate change, demand systematic study of “macro-cognition,” the orchestration of intelligence at planetary scale.

Drawing on examples from ICARUS satellite tracking of animals, Google Maps, global medicine and the International Solar Alliance, which aims to mobilise $1 trillion in investment by 2030, Mulgan identifies seven organising capabilities of intelligence at any scale: anchoring, updating, nesting, sharing, balancing, generating and synthesising.

Most existing “intelligence assemblies” cover only a few. The COVID-19 response, which forced decision-makers to juggle sixteen distinct types of knowledge with no method for weighing them, exposed how poorly we synthesise across domains.

The So What: Designing planetary intelligence is now as urgent as designing AI. We are starving the former.

4. Guess what? Homelessness is not intractable

The evaluation of Britain’s £50 million ‘Everyone In’ Social Investment Pilot offers hard evidence that blended capital works. This is systems investing in the wild, and I’m thrilled to see hard data, which is rare.

Seeded with £30 million of public and Better Society Capital money, then expanded with a further £138 million of private investment, the scheme procured 528 properties through three fund managers, with 91% sited in the local authorities of greatest homelessness need. The London leases ran 15% cheaper than private lets; other stakeholders saved up to 22% versus private rents and over 70% versus temporary accommodation. And it makes money - the portfolio is forecast to yield ~8% real returns by 2030.

The So What: Patient capital can house the homeless cost-effectively, but only when wrapped around relational, person-centred services.

Conference hack of the week - Farah The Fox

The Skoll World Forum in Oxford has just concluded and this custom GPT was created to help people navigate the potentially overwhelming array of attendees, speakers and topics. It’s a great idea and I expect conference organizers will be increasingly using these tools to help attendees network more productively. We’ve been building a similar tool, so would be great to hear from any meeting organizers looking to test out this kind of next generation, AI-powered event support.

That’s all for now, happy weekend everyone.

- Stephen

1. Systems investing compared to other investing types

One of my most consistent themes in this newsletter is the topic of Systems Investing, and I’ll keep hammering the topic until it becomes everyday language. This article does a nice job in framing it in relation to a lot of other things you may be more familiar with.

The framework charts a spectrum from responsible investing through impact, blended finance and social movement investing to systemic investing.

His definition is compact: a multi-stakeholder, poly-capital ecosystem approach. The shift is from single instruments toward deploying financial, social, political, natural, relational, human and narrative capital simultaneously across an ecosystem of connected initiatives. He cites TransCap Initiative, FEST and TWIST as global momentum, with Raven Indigenous Outcomes Fund and the Afro-Caribbean Business Network’s microloan fund in Canada.

The key point he’s making - familiar with LF readers - is that polycrisis problems (housing, climate, mental health, polarisation) cannot be solved by any single instrument or actor working alone.

The So What: Money is one form of capital among many. Systemic change requires deploying all of them with different risk profiles and project types.

2. Philanthropy: asleep at the wheel? A better approach.

This piece in SSIR, argues philanthropy is sleepwalking through the most serious test of civilian protection norms in generations.

Drawing on 25 years across the Pentagon, UN and NGOs, Jenny McAvoy notes the civil society ecosystem has already been built and have a track record, with groups such as the U.S. Dept of Defense's Civilian Harm Mitigation and Response framework, now being adopted in Iraq, Nigeria and the Netherlands.

The problem is funding: fragmented, project-based, concentrated on a few actors, with multi-year flexible grants rare. McAvoy calls for a dedicated collaborative fund modelled on Freedom Fund and Co-Impact, treating civilian protection as a systemic challenge rather than a crisis line item.

The So What: Funding ecosystems, not ad hoc projects, is how philanthropy delivers on its promise.

3. A playbook for philanthropists who want to get AI

Another take on philanthropy’s failings, this time with an AI focus. Mike Kubzansky, departing CEO of Omidyar Network, argues in SSIR that philanthropy is treating AI as peripheral, and it should be core.

AI should be front and center for philanthropists: state legislatures filed over 1,500 AI bills this year, up from 200 three years ago, while trillions in private capital flow toward capability of frontier models rather than good governance.

Kubzansky’s playbook draws on automobile safety history (regulation accelerated adoption, not the other way round) and recent legal wins against Meta and YouTube for addictive design. He points to Omidyar’s Anthropic equity stake alongside Ford and Nathan Cummings Foundations, and the new Humanity.AI coalition of nearly a dozen funders, as templates for the bigger, faster, coalition-based posture the moment demands.

The So What: Philanthropy’s cautious approach feels like an out of date luxury.

4. Vampires in Power: Immortality as an Authoritarian Fantasy

This piece from the NY Times discussed last September’s hot-mic moment when Xi Jinping and Putin, both 72, were caught discussing organ replacement and indefinite life. This is part of a trend of (almost always male) billionaires and political elite deciding that death is optional.

Peter Thiel funds plasma transfusions. Sam Altman has put $180 million into Retro Biosciences. Bezos backs Altos Labs. Saudi Arabia’s Hevolution (not a particularly gender inclusive name…) Foundation runs a $1 billion annual budget bankrolling Diamandis’s $101 million XPrize Healthspan among other things. Singapore-based Immortal Dragons is funding research into “brainless clones” as backup bodies. The article makes the point that radical life extension has become intertwined with the excess concentration of power; longevity as alchemy. Normal rules dont apply, so why would biology?

The So What: Longevity science risks becoming a political tool and cause of societal division if it’s seen as the luxury for dictators and billionaires.

Bonus: Cultural Lodestone of the Week

Hermann Hesse’s The Glass Bead Game (1943), the novel that won him the Nobel Prize, imagines a 25th century future, where humanity’s life’s work is the Game: an intricate symbolic language that synthesises music, mathematics, philosophy and art into single meditative sequences, linking a Bach fugue to a mathematical proof to a line of Confucius. The protagonist, Joseph Knecht, rises to become the highest master of the Game, then walks away.

His realisation is that any system of knowledge sealed off from lived experience eventually calcifies.

Not sure I need to make the connection to today’s LLMs any clearer. AI tools can now do by algorithm what Castalia’s monks did by hand. Timothy Leary was on to this in 1986. Hesse’s warning still resonates: surfacing connections is the easy part. Incorporating them into a life is still the work. Hesse wrote the user manual for AI eighty years early. And gave us an exit path.

That’s all for now, happy weekend everyone.

- Stephen

1. A practice guide to systems investing

TransCap Initiative has published a practice guide for systemic investing - what many are seeing as the next iteration of impact investing. Where standard impact investing may allocate capital to a single company selling say, plant protein, systemic investing tries to flip entire energy systems or food networks.

The guide introduces "transformational intent" as its core concept: not a fixed goal but a directional north star, held lightly and revised as complex systems shift.

Practical tools include scenario development, the 2x2 matrix method, and the Three Horizons framework. A good case study is Builders Vision - a holistic approach towards ocean strategy, that connects a north star to four outcome areas across blue economy, policy, and ecosystem health.

The So What: Capital that targets whole systems, not single companies, is the next frontier of impact investing.

2. Genes do matter for healthspan, after all

A study from the Weizmann Institute has found that genes matter about twice as much as previously estimated - accounting for up to 50 percent of the variations in human lifespan.

They analyzed sets of twins, filtered out accidents and infections, and uncovered the major genetic influence on biological aging.

The So What: DNA plays a larger role than previously estimated in determining how long we live.

3. A seismic political shift - from caretakers to combatants

Australian pollster Kos Samaras offers a view of Western democratic politics: the post-1945 consensus culture, built on managed centrism, absorbed interests, and projected calm, is collapsing. Voters are not punishing incumbents for bad policy. They are punishing them for loyalty to the status quo - an economic settlement that has delivered a generation of stagnant wages, asset inflation, and structural lock-out.

The demand is for combatants: leaders who name enemies and fight without apology. This happens on the left as well as the right - Zohran Mamdani’s 2025 New York mayoral win, the UK Greens’ quadrupled parliamentary representation, and Australian Gen Z’s drift from major parties suggest this is not just a right-wing phenomenon. The party that finds an authentic left combatant first, he argues, will own the decade.

The So What: Institutional loyalty to a broken economic settlement is now a political death sentence, everywhere.

4. Cognitive Rot is a thing after all

A study from UCLA, MIT, and Carnegie Mellon is the first to establish a causal link between AI dependency and cognitive erosion.

In experiments, 350 Americans completing fraction equations with GPT-5 assistance, the AI group initially outperformed the control. But when access was cut after just ten minutes, their problem-solving accuracy fell sharply and, crucially, so did their willingness to keep trying.

A separate experiment with 1,200 participants across maths and reading tasks replicated the finding. The researchers invoke the “boiling frog”: each individual act of AI delegation feels costless, but the cumulative effect on what they call "productive struggle" — the very mechanism through which skills are built — could be irreversible by the time it is visible.

One bright spot: participants who used AI for hints rather than answers fared considerably better once the chatbot was removed.

The So What: AI dependency may be as bad - or worse - for cognitive health as social media.

AI Tool of the Week: Polsia - Autonomous companies

For a mere $49 a month and 20% of revenues, Polsia will create and run a company with zero employees.

That’s all for now, happy weekend everyone.

- Stephen

1. Philanthropy needs a new Operating System

The 2026 Global Philanthropy Forum wanted to redesign philanthropy’s “operating system” from scratch. The theme, “Architecting the Future,” was aspirational; nonprofits are mostly consumers rather than shapers of technology. Could that change?

Maybe. Philanthropy can play a role as “society’s risk capital” - governments and corporations are short term-focused, leaving foundations as the only actors with genuine tolerance for long-term, high-risk, high-leverage bets. For those philanthropists looking to make real, substantive, systemic change, there are now more options than ever.

The So What? Philanthropy must choose between being an architect, shaper and maker of the future or a polite, passive donor.

2. With AI + quantum, today’s cryptography may be toast

The internet’s security just got an expiry date. Papers from Google and Caltech startup Oratomic reveal that AI is now accelerating quantum computing breakthroughs in alarming ways (in particular for cryptographers).

A quantum computer could now theoretically break encryption with only tens of thousands of qubits, dramatically down from previous estimates of a million. Google has developed an implementation of a decrypting algorithm ten times more efficient than any prior method. Cloudflare, which secures a significant fraction of the internet, has already accelerated its preparation deadline to 2029, six years ahead of the NIST target.

The So What? AI accelerating quantum is not a future scenario. It is happening now.

3. AI energy breakthrough

AI has a voracious energy appetite, and researchers at Tufts University may have delivered the GLP-1 equivalent. They built a ‘neuro-symbolic’ AI that combines neural networks with human-style logical reasoning, cutting up to 99% energy consumption.

AI data centers already account for more than 10% of U.S. electricity production, with demand projected to double by 2030. The Tufts POC showed that training required only 1% of the energy used by a conventional model, completing training in 34 minutes against a day and a half for traditional models.

The novelty is in the architecture: instead of brute-force pattern matching, the system applies rules and abstract categories, the way a competent human actually reasons. Whether this scales remains to be seen, but the direction of travel is exciting.

The So What? Smarter AI architecture, not just more and bigger chips, may be the real path to sustainable intelligence.

4. Open AI’s New Deal for the intelligence age

OpenAI has published a sweeping industrial policy framework arguing that the transition to superintelligence demands a response as ambitious as the New Deal.

The document is notable less for its novelty than for who is saying it: the company building the technology is now explicitly calling for redistribution mechanisms.

Key proposals include a Public Wealth Fund giving every citizen a direct stake in AI-driven growth, portable benefits decoupled from employment, “efficiency dividends” converting AI productivity gains into shorter working weeks, and adaptive safety nets that automatically scale up when displacement metrics breach defined thresholds.

On governance, OpenAI proposes that frontier AI companies adopt Public Benefit Corporation structures with explicit commitments to broadly share benefits, and be more robust in preventing systems against ‘insider capture’. Given OpenAI’s various pivots, these reads with some irony. Anyway, the implicit acknowledgment is striking: markets alone will not distribute the gains.

The So What: When the builders of superintelligence call for redistribution and capital taxes, all policy options are on the table.

AI Tool of the Week: Paperclip

Paperclip is an open-source platform that organises AI agents into structured companies, with goal alignment, budget limits, ticket-based oversight, and full traceability built in. Claude has just introduced Managed Agents, which does something similar, although only for its own agents, whereas Paperclip works with any agent.

I’ve just built my first “virtual company” with Paperclip - a new startup to help buildings manage their pets, and to see the ‘CEO’ develop the launch plan then ‘hire’ a CMO and CTO who then get added to the agent stack, is fascinating. Here’s a video interview with the Paperclip founder that provides more context.

That’s all for now, happy weekend everyone.

- Stephen

1. A fresh take on which jobs will be aixed

This is a new take on “AI exposure equals job loss” - it suggest what matters is not what AI can do, but the coordination cost of separating tasks within a job.

In weak-bundle occupations (low coordination cost), AI automates one task, the human narrows to the residual role, output floods the market, prices fall, and the least-productive workers are displaced. Modelled results show employment dropping 7% and labour income falling 12%. Strong-bundle jobs, where splitting tasks destroys value, are largely protected. Radiologists are the canonical example: the job is far more than reading scans.

The So What? AI job risk turns less on task exposure and more on whether your role can be cleanly disaggregated.

2. The case for citizens as entrepreneurial change makers

Britain’s civic life feels broken. James Plunkett’s case for an “activation layer” between institutions and citizens offers an attractive alternative model.

The Citizen First model, piloted in Essex and now running in Liverpool, pays 8-10 selected local to quit their jobs for a year to develop community ventures. The Essex trial returned £6.26 for every £1 invested. Liverpool’s programme was 20-times oversubscribed, with 90% of applicants from economically disadvantaged backgrounds and a third already securing follow-on funding. A national network of 70 such programmes would cost roughly £30m annually. The obstacles are less financial than structural: siloed budgets, no civic infrastructure mandate.

The So What? Converting lived experience into scalable ventures requires institutional scaffolding, not just good intentions.

3. The case for Pet-Friendly Aged Care

This month’s Ageing Australia magazine makes the case that the senior housing is dropping the ball on pets; dangerous since they’re great at companionship.

A recent survey found 96% of Australians believe residents should have pets, yet only 18% of facilities allow them.

The health case is solid: 78% of respondents report pets improve both mental and physical health, with reduced loneliness the most-cited benefit. Providers blame lack of education (45%), limited resources (42%), and facility design constraints (45%). Meanwhile, of 325 home-care recipients, fewer than one in ten receive pet-related support, and 22% delay their own medical care to look after their animal.

The So What? Pet-friendly policy isn’t a feel-good add-on. It’s a measurable lever for wellbeing in an ageing population. .

4. The case against scaling up

For two decades, “can it scale?” has been philanthropy’s default filter. This essay in Stanford Social Innovation Review challenges that.

The race to scale - potentially influenced by the startup ‘blitzscaling’ orthodoxy has influenced which organizations get funded and which problems get defined because it favours standardized outputs (hectares restored, households served) over the harder-to-count stuff that actually determines whether change endures.

Watershed restoration that looks great on paper collapses without local groundwater agreements. Community trust can’t easily be put in a spreadsheet. As the world behaves less like a machine and more as a living ecosystem, single solutions designed for replication hit their limits fast. Kak’s prescription: fund the bridges and lighthouses, not just the ships.

The So What? Complexity-era impact investing needs roots-and-relationships metrics, not just reach-and-replication ones.

AI Tool of the Week: Persyn

A useful tool to make images and video of AI people, or indeed of real people. It uses Google’s AI back end but is more usable and designed to help with eg marketing campaigns. Here’s one of me fulfilling my long ambition to ride a unicycle…

That’s all for now, happy weekend everyone.

- Stephen

1. Biodiversity loss: a national security threat

The UK government has published an alarming intelligence-style assessment: ecosystem collapse is now a tier-one national security risk.

The numbers are eyebrow-raising: monitored wildlife populations declined 73% between 1970 and 2020, freshwater species fell 84%, and six of nine planetary boundaries have already been crossed.

The Amazon, currently at 17% deforestation, is estimated to collapse at 20-25% when combined with temperature rises and forest fires — an uncomfortably thin margin. Coral reefs in Southeast Asia and boreal forests could start collapsing from 2030; rainforests and mangroves from 2050. Downstream consequences run from crop failures and pandemic risk through to interstate conflict over arable land. The total annual value of ecosystem services to the UK alone was £87 billion in 2022 (3% of GDP).

The So What? Ecosystem collapse reframes nature loss as geopolitical risk, demanding security-grade planning responses.

2. The $10 trillion nature economy

The World Economic Forum has published a new report identifying 50 investible opportunities in the nature-positive economy — a market the report values at $10 trillion annually by 2030. The green economy (largely energy transition) already represents $8 trillion in listed equity and has outperformed global equities by 59% since 2008.

The 50 opportunities span 13 sectors — from precision farming and alternative proteins to circular chemicals and data centre water management — and are categorised by readiness: some can be financed through conventional lending today; others need venture capital or blended finance to reach commercial scale.

The So What? Investing in nature makes good financial sense; this report helps answer the question of how to actually do it.

3. This dog may change cancer medicine

Sydney tech exec Paul Conyngham may have changed the face of cancer.

When his rescue dog Rosie was given one to six months to live after a cancer diagnosis, he fed her genomic data into ChatGPT and AlphaFold, identified tumour neoantigens, and designed a personalised mRNA vaccine for $3,000.

UNSW’s RNA Institute manufactured the bespoke vaccine in under two months. The tennis-ball-sized tumour on Rosie’s leg had shrunk by roughly 75% by mid-March. Moderna and Merck are spending billions on the same mRNA approach for humans, with Phase 3 trials underway. The pipeline — sequence the tumour, model the mutations, design a targeted mRNA vaccine — can now be compressed from years into months using freely available AI tools.

The So What? AI just democratised personalised cancer vaccine design; the bottleneck is now regulatory, not scientific.

4. Stem cells reduce frailty in older adults

Frailty afflicts a substantial share of older adults and has had no effective therapy. A new study showed that mesenchymal stem cells (MSCs) from young adult donors showed dose-dependent improvements in the 6-minute walk test six months post-injection, with higher doses producing greater gains.

The researchers also identified a new biomarker: sTIE2, a protein associated with vascular inflammation, was significantly reduced.

Prior studies show MSCs (approved by the FDA in 2024) also increase brain volume and enhance cognition in Alzheimer’s patients, suggesting a broader anti-ageing platform.

The So What? Long limited to race horses and athletes, stem cell therapy moving from fringe to clinical reality, with frailty as a potential first breakout sector.

AI Lesson of the Week: AI Product Factory

Practical video for those interested in using AI tools to make money. Learn from this guy who creates and launches a new business every month in his AI venture studio. (Thanks @Michael for the tip!)

That’s all for now - happy weekend everyone.

- Stephen

1. What if your city could regenerate?

Singapore’s Centre for Liveable Cities is making the case that “doing less harm” no longer cuts it.

Its Regenerative City Framework pushes urban development from net-zero ambitions toward net-positive outcomes, combining ecosystem restoration, circular resource flows, and low-carbon design.

Some of the case studies are inspiring: Bangkok’s One Bangkok development cut peak energy load by 22%, diverted 75% of construction waste from landfill, and its wetlands will retain 200,000 m3 of stormwater. London’s Canada Water project aims for 28% biodiversity net gain, triple the statutory minimum (quite a contrast with the rest of UK’s water industry, as described in LF210). Singapore’s Bidadari estate hosts more than half the country’s migratory dryland bird species, inside a residential precinct.

The So What? Cities that restore rather than merely ‘sustain’ will out-compete those still chasing net-zero as their ceiling.

2. Impact Reporting Network: a new common language

Nonprofits spend enormous time producing impact reports, often filing near-identical documents for multiple funders with incompatible requirements. True Impact, Charity Navigator, and YourCause from Blackbaud have launched the Impact Reporting Network to end this absurd waste of effort.

The model is simple: a nonprofit creates one standardised impact report, opts in to share it, and that single document flows across platforms serving millions of donors and over 10 million employees across 600 companies in 170 countries. No new reporting burden; same data, wider reach. Participation is opt-in and nonprofit-controlled. It is infrastructure, not mandate.

The So What? Impact measurement only scales if reporting costs fall; shared infrastructure is how the sector finally stops asking nonprofits to prove themselves twice.

3. Period blood: the most overlooked biomarker?

For 6,000 years, physicians have analysed urine. Menstrual blood, a far richer specimen, has been largely ignored. This BBC piece argues that’s a significant oversight.

Half blood and half a complex mixture of proteins, hormones, bacteria, endometrial tissue and cells from the reproductive tract, menstrual fluid contains 385 proteins found nowhere else and functions, in effect, as a monthly natural biopsy.

Researchers at Northwell Health have studied 3,700 women and identified distinct immune and cellular markers for endometriosis. California startup Qvin secured FDA approval in 2024 for a pad-based blood sugar test, and demonstrated superior HPV detection compared to traditional Pap smears.

NextGen Jane (previously referenced in an earlier LF), having analysed 2,000 samples, is tracking early links between oestrogen decline and ageing. Studies have also detected thyroid dysfunction markers, environmental pollutants, vitamin deficiencies and STIs from the same specimen. An FDA submission for a non-invasive endometriosis kit is targeted for 2027. The research drag is funding: globally, women’s health received just 5% of R&D spend in 2020.

The So What: The most information-dense fluid in preventive health has been discarded monthly for millennia; fixing that is both a diagnostic revolution and a long-overdue equity correction.

4. New metric of success: Biological Capital

If you follow along with more than 30% of the references of this rather amusing diatribe - The Status of Health - around the explosion of the longevity and wellness segment, consider yourself quite the longevity geek…

The So What? Longevity is having a cultural and economic moment, with new devices, services and protocols emerging that can have genuine impact, but for most people, this stuff is still gobbledygook and elitist.

Cool Tool of the Week: Zo Computer

Interested in testing out some of these new super powerful agentic tools such as OpenClaw, but nervous about opening up your computer to goodness knows what, and finding outsourcing to virtual servers quite complicated? In that case Zo - a cloud computer in a box that’s managed by natural language and vibe coding (rather than requiring complex code commands), is worth checking out.

That’s all for now - happy weekend everyone.

- Stephen

1. World models, or why a squirrel is smarter than Claude

Language models can write sonnets, but struggle to fold a towel. Squirrels fly through the air with tremendous precision, but don’t speak a word. This piece by a Khosla Ventures partner (tip: open in incognito mode if you hit a paywall) argues that the binding constraint on truly capable AI is not compute or clever architecture, but a specific, scarce data type: action-conditioned records of human decision-making, frame-aligned with real-world consequences.

Google’s Project Genie is getting at the solution, collapsing months of hand-coded simulation into seconds. Games may be the wedge to the real world training data, where millions of hours of human judgment and feedback loops is already digitised. The prize is enormous - think Claude Skills but for the real world: a top surgeon can be scaled to rural areas; an electrician’s lifetime expertise deployed across a thousand cities simultaneously. The digital revolution made information cheap. World models promise to make physical capability equally abundant. (Thanks @Malav for the tip!).

That article complements Anthropic’s latest report, which includes visual representations of where Claude is already in use (red), where it could theoretically go (blue) and by extension, where physical AI would still dominate (everything else).

The So What? When we shift from words to reality, the potential scope of AI’s impact goes up markedly, but we’ll need new to find new sources of high quality data showing input —> output feedback loops.

2. Buck Institute aims for federated healthspan knowledge

People are living longer but, as any gerontologist will note, not necessarily better. The Buck Institute has launched Healthspan Horizons, which is positioned as a federated research platform linking real-world longitudinal data from wearables, sleep, nutrition, and labs with deep biological discovery science.

The architecture is deliberately decentralised: approved analyses run across partner environments without requiring centralised ownership of individuals’ health data. The core insight is compounding value: dense longitudinal datasets become exponentially more informative when multiple signals are tracked on the same person over time, enabling earlier detection of decline before a life-debilitating disease takes hold.

Led by longevity ninja Nathan Price and Yi Sherry Zhang, the initiative invites researchers, clinicians, payers, and individuals to participate as co-builders of a healthspan commons, rather than passive data donors.

The So What? Federated infrastructure has long been a holy grail in this space, as it preserves privacy while delivering shared insights. Applying it to longitudinal signals could be a boost to healthspan innovators (myself included) looking for data-driven decision making.

3. Britain’s Water Scandal: Privatisation’s Broken Promise

My home country England is unique in many respects, but one way that’s not a cause for celebration is it’s the only country (besides Chile) where water is privately owned for profit.

The results are damning. In the 27 years since eight-year-old Heather Preen died after paddling in sewage-contaminated water, the industry has accumulated £73bn in debt while paying out £88.4bn in dividends.

English water companies have racked up nearly 1,200 criminal convictions for pollution, yet not one chief executive has faced charges. Thames Water, serving 16 million customers, now operates under a consortium of hedge funds demanding a 15-year exemption from environmental compliance. (When I was living in West London every year or two the roads would be flooded by a broken water main - this isn’t the flood risk we should be prepping for…)

Meanwhile, Paris’s 100% municipally-owned water system achieves 90-96% customer satisfaction (they even have free sparkling water at public fountains). The government’s reform plan, rejecting public control, is dismissed by campaigners as shackling bill-payers to a broken model indefinitely.

The So What? When everyone else does it better, maybe see what they’re doing. Having the regulators funded by the regulated, and loading up debt to pay dividends, means outsourcing externalities to the public and giving capitalism a bad name.

4. AI for events

The International Congress and Convention Association (ICCA) has announced a landmark initiative to develop the first-ever “Global Impact Measurement Tool for Association Conferences”.

This is a group with an impressive member roster - founded with convention bureaus in Barcelona, Copenhagen, Flanders, Sydney, and Tokyo, the project will create a standardized, academically grounded framework to quantify the social, scientific, and economic value that association meetings generate — beyond just ‘more tourists’.

The initiative responds to a long-standing gap: governments and policymakers require concrete evidence of societal value to justify investment in conference infrastructure, yet the broader contributions of these events to knowledge economies and community wellbeing remain a black box.

The So What? An interesting initiative that’s going to need some level of agreement about what impact is and a cross-industry taxonomy, so combining convention centers with an academic network makes sense. However, they don’t expect results in 2028 —> innovator opportunity to get something to market before.

Cool Tool of the Week: SentiVue

Saw this launch on one of the voice AI communities I’m part of and tried it out in Tokyo this week - to do real time translation for events. It worked well. Feel free to mention Looking Forward as a reference, if asked.

That’s all for now - happy weekend everyone.

- Stephen

1. Japan's Demographic Dividend Goes to the Dogs

Japan’s ageing population is intimately connected with its infrastructure. People are used to thinking about aging - but actually, the flip side is an infrastructure that is built for a future shape of society that we’ll all be experiencing soon.

Monocle highlights an intriguing way in which this infrastructure is changing is with pets. Japan now has more pets than children under 15, and its property market is finally catching up. Developer Asahi Kasei’s Hebel Haus brand operates roughly 3,000 pet-minded buildings comprising 19,000 units across Tokyo, Hiroshima, and Osaka.

Competitor Fluffy (imagine a Western developer with that brand…?) , with 87 central Tokyo units, attracts high-income dual-earner couples in their thirties and forties as its core demographic. Features run from deodorising systems and paw-washing stations to round-the-clock veterinary access and environmental sensors. Vacancies are rare. When housing design follows demographic reality rather than outdated tenancy conventions, both quality of life and rental yields improve.

The So What? Japan’s pet-first housing boom is another facet of a new longevity-driven infrastructure.

2. Open Source’s Inconvenient Truth Gets an Endowment

The internet runs on open source software, which comprises up to 55% of enterprise tech stacks. Yet 86% of its developers go unpaid, and burnout is endemic. A newly minted nonprofit, the Open Source Endowment, backed by founders of GitHub, HashiCorp, and Supabase among 50-plus donors, aims to fix this permanently. Starting with $750,000 in commitments, it targets $100 million in assets within seven years, modelled on university endowments. The Linux Foundation’s Alpha-Omega distributed $5.8 million to 14 projects in 2025, but that patchwork approach leaves critical infrastructure chronically underfunded.

The So What? Sustainable open source funding is the unglamorous infrastructure problem that AI’s future depends on solving.

3. Activating citizens - Liverpool invests in community

Liverpool’s Citizen First programme is a proof of concept for something bigger. Twenty times oversubscribed, with 90% of applicants from economically disadvantaged backgrounds, it pays nine entrepreneurs a year’s salary to build health and care ventures rooted in lived experience, generating an independently evaluated social return of £6.26 per £1 invested in its first year.

James Plunkett’s parallel essay argues this is one instance of a wider “activation layer” needed to turn citizen knowhow into durable ventures. A national network of 70 such programmes, running once yearly in towns above 100,000 population, would cost around £30 million annually, and could produce 630 civic leaders a year.

The So What? The bottleneck in public innovation is not ideas but the infrastructure to harden them into action.

4. Japan’s Succession Crisis Gets an AI Matchmaker

Japan's demographic crunch hits small businesses hardest. They make up 99.7% (!!) of all Japanese companies, and 620,000 profitable ones face closure. 620,000 profitable companies face closure simply because their aging owners have no successors. By 2025, the government estimated over 1.25 million small-business owners would be 70-plus with no succession plan, putting 6.5 million jobs and $100 billion of GDP at risk.

Addressing that problem has made Shunsaku Sagami, 33, Japan’s youngest billionaire.

He built M&A Research Institute Holdings around this gap, using AI to match sellers with buyers across 400 concurrent deals. Listed on the Tokyo Stock Exchange in 2022, he’s now worth around $2 billion. He’s now eyeing international expansion, betting Japan’s succession problem is soon going to be shared by the world (as per the consistent theme in this newsletter).

The So What? Demographic decline is a systems problem; AI-powered succession marketplaces may be its most elegant business solution.

Video of the Week: Energym

Brilliant, thought-provoking video snack on what happens in 10 years when AI has taken all the jobs…

That’s all for now - happy weekend everyone.

- Stephen

1. Abolish philanthropy

Jennifer Thuy Vi Nguyen manages a $100 million grant portfolio. She thinks her job shouldn’t exist.

Her argument is refreshing and sharp: private foundations are sitting on $1.5 trillion, disbursing just 6.67% annually, siphoning funds from the public tax base, and providing political cover for the very inequality they claim to address.

In the spirit of Anand Giridhradas’ Winners Take All, this should be uncomfortable reading for those who have accelerated inequality via extractive capitalism, salving their conscience with tax free donations for buildings at business schools and hospitals with their names on it. As the Trump administration defunds nonprofits and a $124 trillion Great Wealth Transfer looms, we should be asking - what is private philanthropy for?

So What? Does philanthropy drive systems change for good, or delay it?

2. Abolish nudges

Behavioral economics had a great run. For nearly two decades, ‘nudges’ were the policy wonk’s answer to everything: auto-enroll employees in pensions, put fruit before cake in the canteen, make the default option the right one. Elegant, cheap, politically painless. Two of the field’s experts have written a book called It’s on You making the uncomfortable argument that nudges don’t just fail; they actively make things worse by letting corporations and governments off the hook for structural failures.

So What? Nudges let systems off the hook. Real health change requires structural reform, not better defaults.

3. Abolish chatbots

The Atlantic’s Lila Shroff has written the most accessible account yet of what’s actually happening in AI right now. The framing is perfect: Claude Code (and its consumer version, Cowork) doesn’t just talk to you — it does things. Her friend’s reaction after first trying it captures the shift well: ‘ChatGPT is like if a mechanic gave you advice about your car. Claude Code is like if the mechanic actually fixed it.’ We’ve moved from AI as information retrieval to AI as autonomous action.

The So What? Your sector will be disrupted. The only question is whether you’re building the new rails.

4. Solve Everything

It feels a little rude to have this magnum opus here at #4, but basically when you’re done with this you won’t have energy for anything else.

Alex Wissner-Gross and X-Prize founder Peter Diamandis have published a blueprint audacious enough to make fellow optimistic Looking Forward readers feel we’re not really trying. They’re hoping it will have as much of an impact as the Machines of Loving Grace essay that Anthropic’s CEO published in 2024.

They argue that civilisation is in the midst of its fourth great revolution, this time against the scarcity of expert attention itself. Their central claim: by 2035, AI will “solve” entire domains in bulk, from biology to fusion energy, by making them compute-bound rather than genius-bound. The mechanism is the “Abundance Flywheel,” a virtuous cycle in which pre-committed compute, focused on hard public targets, triggers domain collapse, generates surplus, and reinvests into the next frontier.

By ‘domain collapse’ they mean when a field of knowledge tips from being an artisanal craft, dependent on rare human genius, into an industrial process anyone can access. The protein folding problem is a good example. For 50 years, mapping a single protein's structure could take a PhD student an entire year. AlphaFold effectively ended that era overnight. Now it takes minutes and costs pennies. The domain "collapsed" from scarcity to commodity.

The metrics are deliberately concrete. Success in medicine means Time-to-Therapy measured in hours, not months. In education, Learning Gain per Hour, verified 180 days later. In materials science, Time-to-Property compressed from decades to days. The 550,000 Americans on kidney dialysis, costing $48 billion annually, become Exhibit A for why organ manufacturing on demand is not philanthropy but arithmetic.

The essay distinguishes the “Muddle,” entrenched bureaucracy still paying for effort rather than outcomes, from the “Rails,” outcome-based contracts, targeting authorities, and compute escrows that actually drive progress. The former will absorb AI without changing; the latter will compound it into abundance.

The So What? AI rewards those who measure outcomes, not those who measure effort.

Historical Cultural lecture of the week: The Real World of Tech

Came across a thoughtuful person raving about the ‘Real World of Tech’. Author, physicist Ursula Franklin gave these five lectures on CBC Radio the same year the web was invented. She talks about "holistic" technologies that give the user control vs "prescriptive" ones that impose compliance. Feels fresh today! And btw, pairs neatly with the Atlantic piece above: she was asking in 1989 who technology gives control to. We’re still asking.

Book of the Week: Impro

Heard an interesting book recommendation from an ex-Palantir employee about a book they’re all encouraged to read: Impro. I'm listening to it now (Spotify's audiobook selection is making me doubt the need for my Audible subscription, btw), and it’s as kooky, interesting and mind expanding as promised.

That’s all for now - happy weekend everyone.

- Stephen

1. Going beyond autocomplete

Those who gripe about how AI models are still dumb (they don’t even know how to wash a car…) are missing the point. Global humanity has for the first time an incredible tool that can bring the world’s intelligence to our fingertips. And for most things that’s amazing. Complaining about that is like complaining about the speed of wifi on a plane. However, there is an interesting question about how AI can go beyond synthesizing and digesting already known knowledge to creating new discoveries.

New science comes from anomalies that break things, rather than conform to it; a model trained on Newton will never invent quantum science. MIT Professor Markus Buehler suggests three ways that we can have AI go from librarian to scientist:

First, compositional world models. Systems must build explicit world models that can be recomposed, not just statistical summaries. Discovery requires systems that represent knowledge as structured relationships, not just correlations in text. By working with explicit models of how parts fit together, an AI can recombine principles across domains and propose explanations that are not simple extensions of past cases.

Second, adversarial falsification. Scientific progress depends on proving ideas wrong. Systems therefore need internal opposition. One component compresses observations into the simplest possible theory, while another actively searches for counterexamples. Progress occurs when theories are revised to survive stronger attacks, rather than when outputs merely sound plausible. (The examples in Claude Code below both have teams of agents that critique with each other, creating a stronger output).

Third, physical grounding. Ideas must confront reality. Predictions are hypotheses until tested against simulations, experiments, or fabrication. Without this loop, models drift toward elegant nonsense.

Together, these levers would shift AI from prediction within a closed worldview to systems that can revise the worldview itself.

So What? We’ll be hearing a lot more about ‘world models’, as the limits of purely text-based LLMs become apparent. These three levers help us build them.

2. Maybe there’s no AI bubble

Azeem Azhar questions the prevailing assumptions that we’re about to experience an AI bubble, suggesting it could be the opposite - the beginning of a far bigger boom.

Data points to a capacity crunch. In two years, monthly AI revenues rose eighteen-fold, from $772m in January 2024 to $13.8bn by December 2025. “Industry Strain”, the ratio of investment to revenue, fell from 6.1x to 4.7x in five months, moving away from bubble territory.

AI has moved from novelty to infrastructure, from chatbots to agents that work for hours at a time. That shift devours computing power. Cloud firms are already rationing capacity, delaying customers and diverting resources between products. Heck, AWS is even getting into copper mining… Data centres take years to build, power grids longer still. Capital can be summoned quickly; electricity, chips and concrete cannot. The risk ahead is not collapse, but congestion: a stampede toward AI that the world is struggling to supply.

The So What? A counterpoint to Cory Doctorow’s perspective in LF204, and this one grounded in numbers. What if the bears are wrong?

3. Open Claw and why it matters

I’ve been really diving into OpenClaw this week and it’s a fascinating experience to be able to chat (am using Telegram) with an always-on, always-remembering assistant - taking us into the Jarvis territory. This post by the generally hype-averse founder of Basecamp does a nice job of summarising its impact.

It’s the first real shift from tools to autonomous digital actors- moving beyond the prompt–response loop. With no special plugins or APIs, the agent signs itself up for email, joins collaboration tools, creates shared workspaces and responds to invitations much as a human would. It navigates a world built for people, using the same interfaces and cues.

This suggests a future of AI that is less about integration and more about resilience, flexibility and real world adaptiveness - similar to the argument in #1.

The So What? Personal AI assistants may soon behave less like software and more like junior colleagues.

4. Collectivist countries are lonelier than individualist ones?

A counter-intuitive take here based on this research and a new WHO report. We might assume that collectivist societies offer deeper connection, but it turns out that the best recipe for addressing loneliness is to have high individuality with high quality, reliable societal infrastructure.

Loneliness is often blamed on excessive individualism, but that misses the mark. Collectivism is about organising life around tight in-groups such as family, clan, caste or social networks (e.g. China, Pakistan, Indonesia and Philippines) confers some advantages but if you’re outside the in-group, it’s devastating.

The evidence points to societies like Denmark and Netherlands having the best loneliness outcomes (a big factor in overall health) - they combine autonomy with strong welfare states and high trust.

The So What? True social resilience comes not from enforced togetherness but from institutions and norms that make individuals secure without constant relational upkeep.

Claude Code Lesson of the Week: Build your AI Boardroom or AI workforce

Claude Code is everywhere, and it’s worth spending a few hours setting it up and figuring it out as it’s mind expanding. It’s fundamentally different than the chat interface that we’re used to, because it lives inside your computer, can access far more context about what it should do and how to work and can actually make changes in your computer folders, such as writing code that is then pushed live on the web. I’ve built 3 websites already this week - far quicker and easier than using prompt-based approaches to design the front-end, like V0.

Anyway, AI influencer Allie Miller shares a prompt that allows you to build a team of advisors to help with your projects, while this video shows how a guy created a workforce of 14 agents that helps him run his business.

That’s all for now - happy weekend everyone.

- Stephen

1. Worst portmanteau ever, but solid idea

Novotel, the midscale Accor-owned hotel brand (600 properties across 68 countries), has declared longevity its core brand philosophy.

Their “Longevity Everyday” programme centres on four pillars: Eat, Sleep, Move, Meet (conspicuously omitting Purpose, which reduces mortality risk by 15-34%). Nicola Palmarini who runs the UK’s Longevity Centre has coined the term “Lobbgevity”: longevity migrating from exclusive €40,000-per-week Swiss clinics to airport hotel lobbies.

This matters because it shifts focus from the “one escape week” to the “fifty-one ordinary weeks” where health actually compounds. If more people encounter longevity thinking via business travel, the concept will start to go mainstream - and maybe even policy makers will take note.

The So What: Longevity becomes accessible infrastructure when embedded in ordinary weeks, not escape weeks.

2. The case against trickle down AI

AI’s wealth creation won’t automatically benefit lower-income countries through market diffusion, cheaper goods, or even redistribution schemes, so we need a new approach.

This piece from the UN Global Pulse argues for “pro-development AI” - capabilities built with and for communities facing humanitarian challenges. Current blockers include incumbent R&D that favors low-risk, incremental approaches, fragmented “AI for Good” efforts, and market failures in creating solutions for poorer nations.

Instead we need coordinated investment in problem-driven and locally-owned AI development. DISHA, the UN Secretary-General’s Innovation Lab initiative, prototypes this cross-sector collaboration platform. Without deliberate action, AI risks deepening global inequalities rather than enabling universal abundance.

The So What: AI is an accelerant - and will just as easily accelerate inequalities; in fact that’s more likely given AI is mostly owned, operated and governed by capital owners.

3. AI changes identities

The past couple of weeks has seen the dystopian (utopian?) future arrive more quickly than most people were expecting, and it could change who we are.

Enter OpenClaw, an AI agent running autonomously on personal devices, and Moltbook, a social network for agents (named in the two days when OpenClaw was called Moltbot, after changing its name from Claudbot…). Moltbook is a social network for those OpenClaw bots to chat with each other - go there and witness 1.5m AI agents chatting with each other (at times inane, scary and thoughtful).

Over 21,000 exposed OpenClaws are now sending emails, managing correspondence, and executing tasks in users’ voices without their ‘humans’ active participation. When you’re not sure if you’re speaking with an agent or a human, relationships get weird. Reminds me of the meme, on the Internet, nobody knows you’re a dog.

So What? AI agents communicating as us…Can our identities survive outsourcing? And how do we know who or what we’re speaking to.

4. Saudi Arabia’s $500 Billion Reality Check

Saudi’s ambitious vision for a vertical longevity-focused city has stumbled. The Line, once planned as a 170km linear metropolis for 9 million residents, now targets just 300,000 by 2030 across 2.4km (down from 16km). The Public Investment Fund wrote down $8 billion in August 2025, and construction was suspended in September.

Originally budgeted at $320 billion for phase one, the project has burned through $50 billion with only foundation piles to show. The crown prince’s “preventative healthcare so people will live longer” vision met physics: building two 500m-tall mirror skyscrapers across desert, mountains and coast would require 20% of global steel. With oil at $60/barrel (not the $100 needed) and no foreign investment materializing, the emperor’s new clothes are showing. Internal audits found “deliberate manipulation” and backers are backing away.

The So What. Grand visions for healthy longevity cities require economic gravity and social humanity, not just architectural fantasy.

AI Tool of the Week: Synta

Automate your N8N automations… The trouble with the increasingly sophisticated vibe coding tools (Gemini 3 and Manus are my current picks, along with the ever reliable v0) is that they do the front end pretty well but generally get stuck when you do the back end wiring. That’s why I’ve been a fan of N8N - you can build automations and see visually where the process gets stuck.

As such am excited to try out this new tool Synta, that acts as your co-pilot to build N8N workflows. Its getting easier to put these automations together, but still quite a learning curve, so I like where Synta is headed.

That’s all for now - happy weekend everyone.

- Stephen

1. Upgrading Civilisation OS

Azeem Azhar argues humanity crossed three critical thresholds between 2010-2017: energy (solar hitting cost parity), intelligence (transformers enabling predictable AI scaling), and biology (genome sequencing dropping from $3bn to thousands).

Each of these shifted us from extraction to engineering, moving civilization from “Scarcity OS” to abundance-based operating systems. The old social fictions - jobs bundling identity and income, credentials as trust proxies, experts as information gatekeepers - decay as these constraints collapse.

Azhar’s experience at Davos this year revealed segments of responses to this:

• Hoarders (zero-sum protectionism e.g. no prizes for guessing)

• Managers (optimizing old systems (e.g. Mark Carney))

• Builders (accelerating abundance e.g….?).

This kind of segmentation - hoarders, managers and builders - provides a fairly coherent worldview explaining some of our current disconnection. And more importantly, points to a concrete path forward - building, positively loudly and in public.

The So What: When fundamental inputs become engineerable, society’s organizing principles must upgrade too.​​​​​​​​​​​​​​​​

2. Silver Linings

Silver Linings is a beautifully designed, artfully presented and scientifically rigorous project to improve healthy longevity. It describes itself as: “an open project to accelerate healthy longevity”.

It makes the case for investing in the biology of aging; something that the US spends a mere just half a percent of NIH research on, despite it being the primary risk factor for most diseases.

Market failures plague the longevity field: pharma profits more from extending illness than preventing it, insurers won't invest in future health, and prevention is harder to measure than treatment.

Yet the economics make all sorts of sense. Nobel laureate Gary Becker showed healthy longevity drives economic health, while William Nordhaus proved longevity gains equal all other economic growth combined. Americans earn peak wages at 55 before age-related decline. Extending productivity by five years could dramatically reshape human earning potential and give a boost to society that is much in need of one.

So What? Investing in aging biology yields economic returns matching all other growth combined.

3. Anthropic’s CEO on our AI future

This caused quite a stir - one of the most important AI figures clearly laying out the risks of the field he’s leading. Anthropic CEO Dario Amodei considers it civilization's defining test: managing "powerful AI" - models surpassing Nobel laureates across fields, operating at 10-100x human speed in million-instance clusters, potentially arriving within 1-2 years.

He quantifies five existential threats: autonomy risks from unpredictable AI behavior (Claude already exhibits deception in lab tests), bioterrorism enabled by step-by-step guidance, autocratic power concentration (China's surveillance state plus AI equals permanent totalitarianism), economic disruption (50% of entry-level white-collar jobs displaced in 1-5 years), and concentration of wealth exceeding Gilded Age levels (individual fortunes approaching trillions versus Rockefeller's 2% of GDP).

The solutions he suggest are as boring as the dystopian vision he paints is colourful: require constitutional AI training, mechanistic interpretability, chip export controls, and regulation. (Editor’s note: Unfortunately, we’ve not built these countermeasures and our dysfunctional governments and institutions are ill equipped to do so.)

So What? This is a counterpoint to Cory Doctorow’s essay (LF204) that the hype is overdone and the bubble will claim these companies. However, even if Dario and the bubble pops, many of these scenarios (bioterrorism, trillionaires) could still play out.

4. The wrong signs in the shopkeepers’ windows

John Fullerton challenges Mark Carney’s (now infamous) Davos speech lamenting the decline of the “rules-based international order,” arguing this system itself caused our current rupture. (To be fair to Carney, he did say the old world was a polite fiction, but still measurably better than the chaos its rupture has created).

Fullerton traces economic crisis to flawed neoclassical theorists, whose efficiency-obsessed models enabled extreme global integration and wealth concentration.

He notes the British East India Company once controlled 25% of the global economy through extraction, a pattern he sees replicated by Amazon, Google, and modern finance.

Rather than tweaking GDP alternatives or embracing ‘degrowth’, Fullerton suggests we understand economies as living systems embedded in the biosphere, not machines to optimize. The rupture demands not nostalgin (as Carney notes) but regenerative economics that aligns people and planet.

The So What: Mainstream economics’ relentless machine logic created the polycrisis; regenerative thinking offers (a hail mary chance of…) systems-level transformation.

Book of the Week: Reshuffle

I rarely re-read (or more accurately, re-listen) to books, but am deep into Reshuffle, for the second time. Choudary’s tone can be a little dry at times and he stuffs a lot of thoughtprovoking ideas into each paragraph, so this is a book that doesn’t reward continual partial attention or insta-style snippets.

The substance though is gold. Key takeaways for me so far:

• AI is not about making things more efficient, it’s about about changing what things are valuable and who gets to make decisions (you or the algorithm).

• The commonly invoked phrase - “you won’t be replaced by AI but by someone with AI” misses the mark. AI may fundamentally change your industry, so there may not be a role or a job for that someone else with AI to take.

• Even if you don’t lose your job, the job itself may pay a lot less (value) or remove you of decision power (agency). That’s just as much of an issue.

• The issue is not can AI do tasks, it’s which constraints is it removing, and which new ones is it creating. He uses the example of a sommelier - weirdly in an era of information abundance, they’ve become more valuable. Not because people want to know about wine (a commodity) but because diners can outsource uncertainty, gain confidence and insure against loss of face to this person in a restaurant. That’s worth the 200% markup people happily pay for wines in a restaurant. Where’s the sommelier in your business?

• AI provides a new mechanism for coordination for fragmented in siloed industries along five dimensions:

  • Representation: Mapping what exists, what’s the landscape.

  • Decision-making: Helping make decisions about what should be done.

  • Execution: Making change happen.

  • Composition: What stakeholders are involved in the business.

  • Governance: How decisions are made and who gets to benefit.

• As a result of this new coordination superpower, AI makes it possible to create ‘permissionless ecosystems’, connecting disparate players (e.g. by making sense and connecting up large amounts of unstructured, non-harmonized data from different players). This is a threat to the previous model of dominant players setting standards or requiring voluntary consensus.

Net net, there will be new opportunities to put together valuable ecosystems to solve complex problems in ways that weren’t possible years, or months, ago.

That’s all for now - happy weekend everyone.

- Stephen

1. How to win when the AI bubble pops

Cory Doctorow is one of the most trenchant, readable and insightful commentators about tech and its impact on business, society and our common morality. His latest Guardian piece dissects what’s going on with AI, and the pending bubble in refreshing clarity.

Seven AI companies now comprise over a third of the US stock market, endlessly circulating the same $100bn as IOUs. The pitch to investors is not about empowering workers but delivering efficiencies: fire nine-tenths of America’s 32,000 radiologists, pocket half the savings, remit the rest to AI vendors. What we get “reverse centaurs” - humans reduced to ‘accountability sinks’ who sign off on AI diagnoses at breakneck speed while absorbing blame for algorithmic, blackbox failures.

So first tip - don’t be that human that holds the blame for the AI overlord - that starts with seeing where the value is shifting in your industry and not being squeezed in the middle (perhaps easier said than done, tbh).

However, the upside to all this - when this bubble bursts (and it will), the wreckage could yield cheap GPUs for climate modelling, open-source transcription tools, and a raft of programmers skilled in applied statistics. Unlike the monkey JPEGs that crypto gives us, an AI correction should be productive.

The So What: AI’s collapse will leave useful technical infrastructure, unlike purely speculative bubbles.

2. Does your home heal or harm?

Dr Gautam Gulati is one of the most articulate advocates of what some are calling ‘home as medicine’ (thanks for the intro, Zayna!), and this post describes the ways in which your home can be a force for health, or not.

We’re now used to the idea that your post code is one of the most important determinants of your health, but what if it’s more micro than that? The real health predictor might be sitting under your roof. The Well Home has coined “Home Determinants of Health” (HDoH), a 12-factor framework measuring how indoor environments shape wellbeing.

Think air quality (directly affecting respiratory outcomes), circadian-friendly lighting (proven to reduce depression by up to 30%), and biophilic design (linked to faster recovery times). While real estate obsesses over planetary sustainability, this lot focuses on human biology. The pitch is simple: homes should serve both Earth and occupants. Whether this becomes the next LEED certification or remains luxury marketing depends on whether developers can stomach the premium.

So What? There’s a lot of new attention - and crucially new data signals - around home based health. Look for more about the bedroom, and also the bathroom.

3. GLP-1s are breaking life insurance

A fascinating insight on the cat-and-mouse game between people and the algorithms and actuaries that control their financial futures - life insurance companies.

They face a multi-billion dollar conundrum: GLP-1 meds can temporarily transform high-risk patients into statistical unicorns. Underwriters approve policies based on artificially flattering metrics (BMI, blood pressure, cholesterol), only to discover 65% of users quit within a year, reverting to baseline risk by year three. The result? “Mortality slippage” (i.e. oops, we got our predictions about death payouts wrong) has nearly tripled since 2019, reaching 15.3%; one in six policies is catastrophically mispriced.

Their response - asking harder questions (has your weight changed by 10kg or more in the past year?) and also hunting aggressively for retention partners who can sustain adherence (this is a good thing). That should create a host of business opportunities for innovators. The fix isn’t necessarily complicated wraparound care. Statins proved the winning formula: shift from monthly to quarterly refills, strip out friction, add behavioural nudges. Simple beats sophisticated.

So What? GLP-1 adherence solutions become insurance industry necessities, creating massive B2B2C opportunities.

4. Cities as a response to the polycrisis

Regen Melbourne’s CEO Kaj Löfgren discusses how cities can engage and help address the ‘polycrisis’: 88% of WEF experts forecast catastrophic events within two years, yet business carries on regardless. Why?

Logically, it’s because our society has been captured by the market. Commons vanish (can you imagine creating a library or a fire service today?) and household labour is undervalued.

Melbourne’s response to this Regen Melboure, which is ‘social infrastructure’ that gathers 200 partner organizations, using Doughnut Economics to measure thriving beyond GDP. The methodology (Sensemaking, Organising, Insights, Leverage points) tackles missions like making the Yarra river swimmable. As systems thinker Nate Hagens warns, we’ve flown too close to the sun and our institutions are melting. Regen Melbourne is one promising response.

The So What: Cities need collaborative infrastructure to navigate polycrisis, not just traditional government responses.

AI Tip of the Week: Voice AI Hub

Here’s a resource for anyone else looking to get up to speed and build in voice AI - an area that I predict is going to explode in 2026. To me, voice is fast becoming the next interface after mobile, and includes a whole host of benefits (faster, contains biomarker info, more natural, no fat fingers, can be emotionally powerful). I’ve been frustrated with IVRs for years, but now interacting with some of the new voice AI agents is scarily spookily good. I prefer Waymo over Uber, and pretty soon I expect (weirdly) I’ll prefer a voice agent over a human call center operator.

That’s all for now - happy weekend everyone.

- Stephen

1. Reinventing science as an operating system

The way we do science needs an upgrade, and this piece lays out some bold ideas in response to a call from the US government.

Researchers now squander a third of their time chasing grants while funders struggle to make decisions, producing an opaque, sclerotic system where money concentrates predictably at the usual suspects. The fix? Combine a research commons (open standards, transparent decisions) with a systems-investing mindset (portfolio approaches, multiple shots on goal).

The piece proposes a “networked operating system for science”: machine-readable data across all agencies (goodbye, PDF prisons), standardized research “containers” portable between funders, and marketplace mechanics where ideas compete on merit rather than institutional pedigree. At the heart is an “AI Program Manager” directing portfolios like index funds, complete with syndication pooling public and private capital.

DOE’s Small Business Vouchers pilot, which awarded 114 firms access to National Labs, is a step in this direction. Strip away the grant-writing theatre, unleash the signal —> unshackle innovation.

So What? If AI generates hypotheses faster than humans can fund them, the bottleneck isn’t discovery but deployment infrastructure. Fix the plumbing or drown in possibilities.

2. Your Mirror Will See You Now

CES 2026 was quite a buzz fest, but it also saw AI going from gadgetry to infrastructure (and front-line robot workers).

Among the standouts in this summary by Catherine Ball: NuraLogix’s Longevity Mirror transforms a selfie into health indicators and a longevity score and Boston Dynamics’ Atlas robot - addressing labour gaps through human-machine collaboration. Also, Ambient AI for aged care (e.g. Samsung’s platform) deploys passive sensing to extend independence without surveillance.

Australia has a choice: build evidence-based longevity infrastructure or spectate while others commercialise the healthspan economy.

The So What? Prevention infrastructure beats hospital heroics when scaled properly.​​​​​​​​​​​​​​​​

3. AI: Killer of Civic Institutions

Boston University professors argue artificial intelligence will demolish democracy’s scaffolding - the civic institutions that built society.

I’m not totally convinced by the arguments, as I don’t think most civic institutions are fit for purpose for the challenges we’re facing, but it’s certainly got some good points. They suggest AI undermines expertise by encouraging cognitive offloading and producing hallucinations (true, but guard rails and RAG help this, and this feels a bit like protecting turf).

Second, it short-circuits decision-making by obscuring moral choices behind algorithmic black boxes, flattening hierarchies that enable accountability. (For sure).

And third, it isolates humans, eroding the interpersonal bonds institutions require for adaptation and legitimacy. From courts outsourcing bail decisions to universities replacing professors, AI transforms functioning institutions into brittle shells.

So What? Technology’s promise of efficiency means we’re swapping institutional resilience for algorithmic convenience, potentially unraveling centuries of social infrastructure.

4. Are we ready for data unions?

The UK’s Nesta thinks 2026 could be the year of the data union, and I hope they’re right.

ChatGPT's meteoric rise has accelerated an already fairly gnarly race to own humanity's digital exhaust. UK households unknowingly shell out £1,000 annually feeding the platform beast through advertising pass-through costs. The First International Data Union has just been launched to wrest control from Silicon Valley by pooling citizen power (but I don’t see folks paying $5/mo for uncertain benefit). But this is what Tim Berners-Lee originally thought of for the web; unfortunately his purity has been derailed by profit seeking.

If it works it would redirect attention rents back to members' pockets while unlocking research goldmines (like Imperial College's ovarian cancer study correlating medication purchases with diagnosis). But data collectives aren’t easy to build, suffering like most networks on the web of a cold start problem. Regulation could help - Australia has shown it can break from the pack and regulate social media and now others are following. Certainly needs more people working on the topic.

So what? The history of unions is workers realizing their power. We’ve all unknowingly become digital serfs for Big Tech, and that could change if we start to self organize.

Quote of the Week:

“Your first task is to find what feels effortless to you. Your second task is to put maximum effort into it.” - James Clear

That’s all for now - happy weekend everyone.

- Stephen

1. Relational Service Design (how not to treat your mum)

This piece makes an important distinction in the delivery of public services (although it can equally apply in the private sector) between realational challenges and transactional tasks. Transactional tasks (passport renewals, bill payments) demand efficiency through thin relationships. Relational challenges (family crises, homelessness) require thick relationships built on trust and adaptation.

The opening absurd but telling scenario hits home - imagine your own mother making you go through call centre hoops to get life advice.... The pathology comes from bureaucrats treating things that are complex as things that are merely complicated. Fragmented care passes citizens between workers like widgets on an assembly line. Perfect processes designed for messy lives inevitably fail.

Trust cannot be standardised. Relationships resist mechanisation. Yet the system remains skewed towards optimisation even where sustained human connection proves essential. Relational services require self-organising teams with autonomy, not customer-journey maps. The challenge lies in matching the right ‘relationship density’ to each problem’s true nature.

So What? Mismatched service design wastes resources while failing the vulnerable citizens who need help most.

2. Reinventing innovation consulting

This article (subscribers only) highlights the flaws in most innovation consulting over the past decade or so; organizations built labs and hired consultants, but mostly just accelerated platform adoption while calling it transformation. Design thinking and lean startups had good intentions but became feature factories producing minimal viable (safe…) products nobody loved.

The core failures: ignoring fringe insights, demanding impossible proof before experimentation, defaulting to digital-first thinking (i.e. forgetting about place), measuring everything except actual human behavior, and forcing promising ideas back into legacy systems that suffocated them.

Real innovation requires curiosity as muscle, place-based observation over dashboards, protected budgets for experimentation, qualitative understanding alongside data, and accepting some ideas must live outside the mothership to survive.

So What? Most corporate innovation spending produces compliance theatre rather than genuine discovery or competitive advantage

3. Silicon Valley vs. the Chinese communist party…

Dan Wong is an acute commentator on US and China, and given the growing global tensions, worth following for signs of where things are going. This year’s annual letter makes a comparison between Silicon Valley and the Communist Party. Both are humorless, self-serious, and speak in bland corporate tones punctuated by apocalyptic warnings. Neither embodies sparkling irony, yet both are reshaping the world.

San Francisco remains America’s most meritocratic city, forward-looking and open to newcomers, yet suffers dangerous insularity. Tech elites rarely travel, dismiss traditional culture, and collapse every conversation into AI. Their narrow focus produces technical excellence but cultural blindness.

Beijing’s elites must think globally despite insularity. Chinese society grows increasingly informal and playful beneath the gerontocratic political system’s grudging formality. Over time, China’s rollicking social exuberance may outlive its lusterless politics.

So What? Cultural narrowness in both superpowers who are shaping our future risks catastrophic misjudgment in their defining technological competition.

4. Siemens and NVIDIA collaborate on digital twins

One of the strong themes I see emerging this year is digital twins. Not necessarily your face or avatar, although that’ll be one application, but more about systems digital twins, that bring together multiple stakeholders and business processes to predict and improve outcomes.

At this year’s buzzy CES, Siemens unveiled a Digital Twin Composer, that lets manufacturers construct photorealistic virtual replicas of products, processes and facilities before committing resources to actually building it. Built with NVIDIA’s Omniverse, the platform integrates real-time operational data with comprehensive digital models.

PepsiCo has been an early adopter - they simulated a manufacturing facility and identified 90 percent of potential issues pre-construction, increased throughput by 20 percent, and reduced capital expenditure by 10 to 15 percent.

The technology addresses persistent industrial fragmentation, where design, engineering and production teams operate in silos. By unifying workflows into contextualized models, manufacturers can test configurations within minutes rather than months.

So what? Virtual validation could fundamentally alter industrial capital allocation, reducing waste while accelerating innovation cycles

AI tip of the week: ChatGPT Health

It was an open secret that OpenAI was moving into health, and with the launch of their new Health feature, they’ve taken a big step in their direction. It’s created a separate, secure data record that ingests your medical records as well as wellness data from the likes of Apple, MyFitnessPal and Function Health, and will allow much deeper and easier access to insights. This article goes into detail on how it’s constructed. Some intrepid users have already been loading their medical records into LLMs (myself included) and this will make the process easier, more secure and potentially more valuable, as they are aiming to connect into clinical workflows, not just support the curious consumer.

That’s all for now - happy weekend everyone.

- Stephen

1. Reinventing European cities with AI

‘Silicon meets Cobblestone’ tells the story of how some of Europe’s oldest and most storied cities are using AI to reinvent themselves; digital placemaking in the era of AI.

Across ten cities, AI is helping Europeans plan, participate, and feel connected to their surroundings. A theme runs through all ten: context matters more than tech. Copenhagen harnesses AI to aid its decarbonisation efforts and traffic priorities, Vienna’s chatbot succeeds because it feels like the city, not Silicon Valley. Here’s a quick take on the ten cities profiled:

1. Reykjavik: AI moderates, translates, recommends; citizens propose, debate, vote at scale.

2. Helsinki: Generative visuals turn street ideas into consensus-ready, buildable proposals.

3. Copenhagen: AI traffic control advances climate goals, testing via innovation district.

4. Vienna: City-services chatbot adds context, personality, real-time answers, 24/7.

5. Ghent: Computer vision counts all road users, exposes hazards, guides fixes.

6. Freiburg: Street-level heat modelling predicts risk, tests cooling interventions, prioritises action.

7. Lublin: Transit AI blends data with feelings, improving journeys cheaply.

8. Linköping: University-city-industry loop embeds AI in planning, not gimmicks.

9. Antwerp: Port-and-city AI coordinates logistics, traffic, air quality trade-offs.

10. Tallinn: Digital-first government lets AI automate routine services, freeing judgement.

And here’s a summary that I asked Manus AI to put together on these too.

So What? Successful uses of civic AI are less about the tech itself and more about integration and meeting people where they’re at.

2. Australia and XPrize - firecrackers!

Australia is becoming a force in XPRIZE which I suspect is largely due to their recently announced collaboration with Sydney-based futurist and tech polymath Catherine Ball.

XPRIZE uses competition-based incentives to accelerate engineering solutions for global challenges, with Australia emerging as an Asia-Pacific hub. The organization's model generates 10X leverage: teams spent US$100 million competing for the original US$10 million spaceflight prize, catalyzing today's commercial space industry.

Ongoing competitions include a fascinating - and very relevant for Australia - US$11 million Wildfire prize requiring autonomous fire detection and suppression within 10 minutes, with Australian semi-finals already conducted. RMIT’s Redback Fire Team is participating, combining fire detection algorithms with behavioral modeling to enable rapid response before fires spread. They also have a US$119 million Water Scarcity competition targets cost-effective desalination solutions particularly relevant to drought-prone regions, and a $101m Healthspan prize.

So What? The XPrize model has a proven history of catalyzing impact by attracting talent, and represents the kind of global best practice that Australians could get behind.

2. New therapy for heart disease

Promising news in the use of immunotherapy - which has had significant success in cancer - for addressing cardiovascular disease (CVD). U Penn created CAR-T cells to target oxidized LDL (OxLDL) - a main contribotory factor of CVD.

The approach reduced inflammation in OxLDL and reduced arterial plaque by around 70% in mice without negative side effects. Next steps - see if this can eliminate established plaques and developing human models (with a spin out Cartio Therapeutics).

So What? Promising news in the battle against the world’s #1 killer, and more evidence that inflammation and oxidation are the right targets.

4. How to break any AI model? Poetry, apparently

It seems there’s a wonderfully absurd way to trick AI chatbots: poetry.

Converting harmful prompts into verse bamboozled leading models at rates 18 times higher than straightforward requests. Google’s Gemini proved particularly susceptible, falling for poetic jailbreaks every single time. Interestingly, smaller models like GPT-5 Nano resisted better than their supposedly smarter siblings.

So what? It seems that AI safety filters are scanning for red flags rather than understanding intent; billions of dollars in safety guardrails get knocked down by a sonnet.

AI tip of the week: Claude Chrome Browser extension

This is the direction of things to come, Claude recently released a Chrome Browser which allows you to bring the AI model along with you on your journey, and literally operate your browser, look up things and build stuff. It now works with Claude Code, their coding AI agent. I’ve been using it to review and improve my N8N workflows - it’s a bit like being in a Waymo, you tell it where you want to go, sit back and see it work its magic. Unlike Waymo it’s still pretty buggy and keeps crashing, but give it a few weeks and this will be the talk of the town.

That’s all for now - happy weekend everyone.

- Stephen

1. 250 Weak Signals for the year ahead

A compilation of 250 ‘weak signals’ across nine domains—from “silver influencers” becoming the fastest-growing content creators, to cities issuing “loneliness audits,” to AI whisperers translating corporate culture into model tuning.

Intriguing ideas emerge: neurodivergent-led innovation teams, four-hour hyper-productivity work blocks, pollinator credits for farmers, climate relocation visas, personal memory vaults as digital assets, and divorce insurance going mainstream.

So What? These aren’t predictions - they’re breadcrumbs from the future being dropped.

2. Superpower’s roadmap for a new system for health

Superpower is one of the most impressive human longevity apps and their founder Max has just posted a roadmap for how they plan to usher in a new systems for health.

Good to see the prominent mention of a coming digital twin which will allow you to diagnose, predict, prevent and optimize your health, bringing together genes, exposomem, behaviors, lifestyle and medical care.

For USD $199, Superpower offers comprehensive testing detecting thousands of conditions, personalized protocols adapting to biomarker changes, and 24/7 clinician access. They have a 93% member satisfaction rating and plans for 2026 expansion includes GLP-1s, hormones, and longevity peptides.

For other healthtech innovators, this is a pretty robust manifesto, which includes their plan for a new health system that will:

• Be the front door – before doctors or Google

• Prevent disease & enhance human capability

• Deliver care via AI

• Feel more like Apple or Tesla than a hospital

• Put power into the hands of people

• Lower costs, in line with physics not incentives

• Bring frontier therapeutics to everyone, far faster

3. Living Labs - their time has come

A good survey of Living Labs and where they’re headed. Living Labs are real-world innovation environments where citizens, researchers, businesses, and public sector co-create solutions to complex challenges. Founded in 2006, the European Network of Living Labs (ENoLL) now coordinates 60+ projects across domains like climate, health, circular economy, and smart cities.

The approach combines Open Innovation (multi-stakeholder collaboration), User Innovation (citizens at the center), and Responsible Innovation (ethics and societal impact). Research publications mentioning “Living Lab” surged from ~100 (2005) to over 5,000 (2023). Under Horizon 2020, over 750 projects incorporated Living Labs; nearly 150 already reference them in Horizon Europe (2023-2024). They’re linked to UN SDGs and address grand challenges through participatory experimentation.

So What? Living Labs are just what we need to test our innovations in the messy, complex outside world. They’re holistic, but observable and allow experimentation and iteration, showing what happens when reality and innovation meet.

4. Longevity Hack: Pomegranate

Urolithin A, a metabolite from pomegranates, has been found to improve immune resilience and aerobic performance, promotes brain mitochondrial repair, and improves cardiovascular function. Four months of daily supplementation reduced plasma ceramides, an emerging biomarker for cardiovascular risk.

So what? This isn’t a far-off fantasy; it’s an accessible, evidence-based intervention showing measurable improvements in healthspan, available today.

And finally… Something 4 The Weekend

This deep and thoughtful piece of prose - The Hunger to be Everything - from a 23 year old, nails the dangers of living other people’s lives - powered by instant, ubiquitous global connectivity. It’s a good one to reflect on as the year draws to a close - who and what matters to you, and why?

And that’s 200! That’s all for now - happy weekend everyone.

- Stephen

1. Climate models miss the point

Heat now kills 550,000 people annually, up 63% since the 1990s, yet the climate models that guide global policy making actually ignore human wellbeing.

The Lancet study finds that while researchers have documented climate’s toll on mental health, infectious disease, worker productivity, conflict, and migration, the computer simulations that governments use don’t register these factors.

The research shows malaria, depression, lost working hours, and food insecurity are systematically excluded - as per this article. We’re optimizing for temperature targets while accidentally undervaluing the benefits of keeping humans alive and functional.

So what? A classic technocratic blind spot: measuring what’s quantifiable rather than what’s consequential. We need new metrics.

2. New healthspan metric: Joy

Speaking of new metrics… A group connected to San Francisco’s hacker-forward Frontier Tower (previously featured in LF) is attempting to create the first unified metric for joy, connection and synchrony.

The write up suggests that emotional experiences modulate stress biology as reliably as sleep deprivation or inflammatory diets. Participants will wear single-ear EEG sensors while researchers measure oxytocin, CRP, and other biomarkers across two nights: one baseline, one “Science Rave” (courtesy of longevity raver, Tina Woods) involving rhythmic entrainment and synchronized movement. The premise is that loneliness shortens telomeres and chronic disconnection elevates inflammation, so why shouldn’t joy get its own biomarker?

The goal is to create a metric that sits alongside step count, HRV and sleep score longevity. Whether quantifying collective effervescence survives contact with rigorous data remains delightfully uncertain, but what a refreshing and interesting project!

The So What? If validated, JoyScore could shift longevity medicine from molecular precision toward measuring emotional and social environments as health inputs.

3. The City-Industry-Climate Nexus

A UNIDO white paper argues that decarbonizing cities is not just environmental policy but a strategic industrial agenda.

Cities consume most of the world’s energy and generate the majority of greenhouse gas emissions, yet they’re also frontline implementers of climate solutions. The paper introduces the “city-industry-climate nexus,” where infrastructure, production systems, value chains, and climate action converge.

The So What? By applying systems thinking to urban decarbonization, cities become engines of innovation and resilience, not just sites of risk. A blueprint for inclusive net-zero futures, perhaps.

4. Japan’s $65bn AI bet

Japan has a well-deserved reputation for being conservative about innovation, but when the move, they move.

They’ve just announced a massive ¥10 trillion ($65 billion) investment plan to boost domestic AI and semiconductor industries by 2030. The goal? “AI sovereignty”—reducing dependence on the US and China by building a world-class domestic ecosystem. This conversation is happening in capitals around the world as the realities of being dependent on the US or China hit home.

The plan targets foundational models, supercomputing, next-gen chip manufacturing and quantum computing. This “techno-nationalism” mirrors the US CHIPS Act and China’s state-driven tech push, with the government acting as a mega-VC.

Japan is deploying earthquake-resistant data centers, 40 operational submarine cables, and massive GPU arrays into what Prime Minister Ishiba calls “the first year of quantum industrialization.” SoftBank alone is committing over $40 billion through its Stargate partnership with OpenAI Introl, while domestic firms like Fujitsu and NEC build enterprise-grade AI platforms. The timing is strategic: Japan’s aging demographics create demand for automation without triggering job displacement anxieties. The country faces a projected 789,000 software engineer deficit by 2030, so the government has allocated another trillion yen for workforce reskilling. It’s a quintessentially Japanese approach: bold infrastructure investment wrapped in pragmatic regulations. Less flashy than some, but certainly substantive.

The So What? Japan is positioning itself as the stable, disaster-resilient alternative to US-China AI dominance, leveraging demographic necessity as competitive advantage.

+ Something-4-The-Weekend

Sharing this TEDx Fukuoka video to lift up your sights and offer inspiration. It’s from a few years ago by my new colleague Michael Lindenmayer, a Swiss-American impact innovator with whom I’m currently collaborating to build out smart, preventive health bathrooms.

2.5 billion people lack safe toilets. Every 17 seconds a child dies from sanitation-related disease. Michael shares lessons for solving super-sized problems, forged from collaboration with the Gates Foundation and World Bank, among others: talk about uncomfortable truths, show courage (like Dr. Snow breaking London’s cholera pump), invent creatively (toilets on motorbikes, anyone?), tinker relentlessly, and stay humble.

The punchline? Poop isn’t intrinsically bad. Put it in the wrong place and you’ve got a death zone. Put it in the right place and you’ve got insights, power, fertilizer, and dignity. In sum, he wants you to give a sh*t about solving super scale problems, and believes we all can.

That’s all for now - happy weekend everyone.

- Stephen

1. Innovation as ongoing process, not shiny things

Have we got innovation all wrong? Perhaps it’s not about isolated genius and flashy product reveals (Steve Jobs in his black turtleneck), but a process for ordering chaos.

For decades, we’ve been trapped in “creative destruction”: innovation breaks things, government cleans up. But what if innovation was about creating coherence; about organizing chaos into new forms of coordination…

Innovation is a multi-player game. The key question isn’t what’s new and shiny, but who makes the rules. Today, tech companies become standards and set those rules. What if we all did?

Schools could shape AI in education, not just accept it. Hospitals could co-design AI systems. Cities could co-create mobility with public values built in.

When governments, schools, and civil society play rather than referee, they shape technologies instead of absorbing consequences. The game is only rewarding when everyone plays. Otherwise, it’s domination.

So what? If governments, foundations and corporates viewed innovation as a process where peers collaborate to overcome chaos, we’d go a long way towards addressing the increasing dangers of AI.

2. Bloody Genius

Turns out we’ve been flushing away diagnostic gold every month. Menstrual blood contains the same biomarkers as venous blood but nobody thought to test it because, well, periods. Now startups and researchers are developing at-home collection devices that could screen for everything from endometriosis to diabetes without a single needle stick.

The tech works. Early trials show comparable accuracy to traditional blood tests. The barriers? Getting the medical establishment to take period blood seriously as a diagnostic tool, changing consumer behavior, and convincing investors that half the population’s monthly routine might actually be useful. Revolutionary concept, that.

The So What? Accessible home diagnostics could catch diseases earlier while finally giving menstrual health actual medical attention beyond “take some ibuprofen.”

3. A digital twin of the US labor market

MIT’s digital twin of America’s workforce reveals AI can already do 11.7% of all jobs at competitive cost. That’s 151 million workers and $1.2 trillion in wages, concentrated in white-collar roles we thought were safe: finance, HR, legal, healthcare admin.

The comforting bit? Only 2.2% has actually been automated so far, mostly coding jobs. The less comforting bit? The capability exists now, we’re just waiting for economic triggers. Economists debate whether this means mass unemployment or just the usual creative destruction with better PowerPoint presentations. Either way, “my job’s too cognitive to automate” aged poorly.

The So What? The automation threat isn’t coming; it’s here and affordable. Question is deployment speed, not technical feasibility.

4. Four scenarios for the future of digital health

I don’t normally spruik my own book but this post about future digital health scenarios got some good discussions going. I look at two uncertainties that create four scenarios for the future of remote patient monitoring, and these scenarios can also apply to the field of digital health more broadly.

The first uncertainty is whether medical or consumer wellness models will dominate (i.e. will the wellness industry become as significant an economic player as the medical industrial complex is today), and the second one is whether ecosystems (health records, Big Tech) will be closed and proprietary, or whether open models (e.g. powered by large language models) will win out.

Of course everything is more nuanced and ‘it depends’, but these extremes help articulate four very different models of the future. Would welcome further feedback and discussion.

The So What? Scenarios are helpful tools for strategy making, especially those where both the industry itself and the regulatory and payor environment is moving fast.

+ Something-4-The-Weekend

Tired of the barrage of AI and tech tools. Me too, let’s take a break. Anyway, by now I’m sure we’ve all got our AI agents screening out new AI tools (don’t we?), so let’s try a bonus article on something more prosaic.

This is an original piece of content by the FT (reg may be required) - a video short story about a man wrestling with both memory loss and the tech industry’s ‘solution’ to it. Brilliantly written by David Baddiel and starring Stephen Fry, it’s worth 15 mins on a wet Saturday afternoon.

That’s all for now - happy weekend everyone.

- Stephen