Inbox Media Network: How the Next Ad Category Has Been Hiding in Plain Sight (Part 2)

The Pattern: How New Media Networks Are Born – 2

Most brands spend enormous sums to acquire customers, gather email addresses, build databases, and collect first-party identity. And then they monetise only a thin slice of that base: the customers currently buying or already high-intent. Everyone else becomes cost already incurred and value still unrealised.

This is the hidden asymmetry in most CRM databases. They are treated as communication assets only at conversion moments, not as media assets in their own right. The non-buying majority is either ignored, suppressed, or later reacquired expensively through paid platforms. The attention between transactions goes unrecognised, and therefore unmonetised.

That is not because the customers do not exist. It is because the product built on top of the surface is wrong.

To see this clearly, it helps to borrow the incrementality lens.

The distinction between the already-committed customer and the genuinely influenced customer does important work here. The already-committed customer was going to buy regardless of whether a message arrived. The genuinely influenced customer is the one whose behaviour actually changes because of the intervention. Most reporting counts both equally. Most programmes treat them the same. The channel gets credit for both. The business only benefits incrementally from one.

That distinction reveals the deeper failure of most current email and CRM systems: they monetise transaction-proximate activity poorly, and they do almost nothing with relationship attention that is not yet translating into a purchase. The same database is being overused at the wrong moment and underused the rest of the time.

That suggests the next media network may not emerge from the point of purchase at all.

It may emerge from the relationship layer.

A media network built on purchase intent asks: what can we monetise when the customer is ready to buy?

A media network built on relationship attention asks a different question: what can we monetise when the customer is not buying — but is still reachable, still known, still permissioned, and still capable of paying attention?

That is the unanswered question. And it points to a surface most marketers still underestimate.

The inbox.

Not email as a legacy channel. Not newsletters as content. Not campaigns as sends.

The inbox as a first-party, authenticated, relationship-attention surface that has never been properly productised or monetised.

Because if the pattern behind every media network is real, then the important question is no longer whether a new media network can emerge from this surface.

It is this: what would it look like to build a media network on relationship attention?

Thinks 1958

WSJ: “The podcasting industry has been embracing video to a degree where audio-only shows are becoming the exception rather than the norm. YouTube is now the nation’s largest podcasting platform. Spotify and Apple Podcasts have enabled video in their feeds. Netflix is adding dozens of established podcasts to its streaming-video lineup. The shift is eliciting strong opinions from longtime listeners. While some say video is boosting podcasts’ appeal and making shows easier to discover on social media, others feel that their beloved medium is neglecting them as it caters to another audience. They fear that video might—once again—kill the radio star.”

FT: “Now a second [China] shock is under way — one that is even more threatening to China’s trading partners: an assault on high-end manufacturing. Vicious domestic competition, coupled with vast industrial scale, ample pools of engineering talent and some of the highest subsidies in the world, has generated world-beating Chinese champions in EVs, solar panels, batteries, wind turbines and a lengthening list of advanced manufacturing sectors. But the same forces that forge those companies also tend to generate overcapacity, crushing margins at home while flooding global markets and fuelling trade tensions. Aided by an undervalued exchange rate, Chinese groups are cutting a swath through the most advanced industries around the planet.”

Mint: “It is critical to distinguish between AI-assisted and AI-executed commerce. While fully autonomous agent-led transactions are still early, the influence layer—where AI shapes decisions—is already at scale. This matters because influence precedes monetization. Once decision-making shifts, value pools follow. Unlike earlier digital shifts, Agentic AI is not building new infrastructure—it is riding on existing rails. Payments, logistics, merchant networks and digital behaviour are already in place. Here’s a realistic adoption curve—Near term (0–2 years): AI-led discovery and recommendations scale; medium term (2–4 years): Early agent-led transactions in repeat categories; long-term (4–6 years): Scaled autonomous commerce.”

WSJ: “Speculators have poured their earnings into all kinds of investments since ancient times, but they always return to gold. The precious metal is a constant in human history—a store and symbol of wealth for everyone from Egyptian royals entombed in golden masks, to working-class immigrants crossing the Atlantic with gold coins sewn into their belts…Currencies cease circulation, markets fluctuate, tastes shift. Yet gold holds its value, even as its price ebbs and flows. Perhaps now more than ever, its safe-haven status has made it a reliable hedge against a tumultuous world. “[Gold is] one asset that’s easy, global, portable, accepted everywhere, with a 5,000-year history and not likely to go to zero,” says Steven Feldman, the CEO and co-founder of GBI.”

Inbox Media Network: How the Next Ad Category Has Been Hiding in Plain Sight (Part 1)

The Pattern: How New Media Networks Are Born – 1

In NeoMails: The Attention and Monetisation Surface Brands Already Own, I wrote: “Every generation of the internet has had a surface that concentrated human attention at scale. Search. Social. Mobile notifications. Each surface looked obvious in retrospect — and was profoundly underestimated in prospect. The next surface is the inbox. Not because it is new — it is fifty years old. But because it has structural properties that no other channel can match: personal, permissioned, identity-linked, algorithm-free, and habitual. And because the tools to make it genuinely worth inhabiting — interactivity, incentivisation, individualisation, and inbox-native monetisation — are only now becoming available.”

And then in Monetising the Rest: Why Every B2C Brand Needs a Media Play, I wrote: “Today, most inboxes are passive archives of offers and updates. Brands enter episodically, make a request, and leave. But once NeoMails, Mu, and WePredict are connected, the inbox becomes a place where value is earned, behaviour is repeated, identity is reinforced, and individual engagement connects outward to a social game. That is a very different role from campaign distribution. The inbox becomes not just where the brand speaks, but where the customer acts. And action, repeated often enough, is what turns a channel into a platform…The Rest were not a dead segment. They were an ignored one. Rest Media is what happens when that ignored segment becomes active attention again.”

This essay expands on the idea of emails as an attention and monetisation surface.

**

Every major media network begins the same way.

Not with an ad format. Not with a dashboard. Not with a sales deck.

It begins when someone realises that an existing attention surface — already large, already valuable, already habitual — is being used for one purpose when it could also be used for another.

Newspapers carried editorial, and then advertising. Television carried entertainment, and then advertising. Search turned intent into media. Social turned identity and scrolling into media. Retailers turned product discovery and purchase intent into media. Each time, the attention surface existed first. The innovation was recognising that the surface had monetisable media value and then building the commercial infrastructure to realise it.

That is the pattern.

Retail Media Networks are the clearest recent example. Amazon did not invent digital advertising. What it recognised was that its product pages, search results, and shopper journeys contained a rare combination of assets: first-party identity, explicit commercial intent, and a native place to put sponsored influence close to the point of decision. Walmart, Instacart, Flipkart, and many others followed. An ad category that barely existed a decade ago has become one of the fastest-growing in marketing.

What did retail media prove?

That when three things exist together, media-network economics follow:

  • a first-party attention surface
  • authenticated identity
  • a mechanism for action

Where those three meet, advertisers pay premium prices. Because targeting gets cleaner, attribution gets tighter, and the action happens closer to intent.

That insight is now spreading beyond retail. Travel platforms, finance companies, hospitality brands, food-delivery apps, and marketplaces are all trying to build some version of “media” on top of attention surfaces they already own. The broader category now called commerce media captures the evolution well: the logic of retail media extending beyond retailer websites into any environment where first-party attention and action sit close together.

But there is an important limitation in the current wave.

Nearly every media network built so far is based on transaction-moment attention.

Shopper attention. Search attention. In-market attention. Browse-to-buy attention.

That is powerful. It is also narrow.

Because the most underleveraged attention in marketing is not the attention that exists at the moment of purchase. It is the attention that exists between purchases.

That is where the real gap sits.

Thinks 1957

WSJ: “When I started on Wall Street, a veteran pulled me aside: “Tech stocks are just like Vancouver gold mining stocks. You buy them when the price-to-earnings multiple is high, even infinite, and sell them when the P/E is low.” Huh? Newly discovered gold mines, he explained, go public, attracting speculative investors. The miners spend a fortune on equipment, causing stocks to collapse since the mine makes very little profit early on. But even as profits increase, P/E multiples shrink as mines gets closer to extracting all the gold. We’ve seen it with personal computers, networking, dot-com, mobile, software as a service, electric vehicles and now artificial intelligence. A hype cycle with massive speculation is followed by a selloff as the hype fades and reality sets in. Then the winners who really do successfully mine the gold (or technology) emerge, and their stocks meet or beat their previous peaks.”

Bethany MacLean: “The seven companies are Apple, Alphabet, Amazon, Meta, Microsoft, Nvidia, and Tesla—“the Magnificent Seven,” Wall Street called them. At the close of 2025, these stocks had returned a remarkable 875 percent in 10 years. Indeed, over the last three years, they accounted for 55 percent of the market’s total returns, with the other 493 companies in the index making up the other 45 percent. Within a decade, they have skyrocketed from one-eighth the value of the S&P 500 to almost one-third.” [via Arnold Kling]

Mint: “Meta Platforms is expected to surpass Alphabet’s Google to become the world’s leading digital-advertising business, a first for the social-media company. Advertising research firm Emarketer projects that Meta will surpass Google in net ad revenue this year, reaching over $243.46 billion, edging past Google’s $239.54 billion. The research firm’s estimates account for revenue after deducting traffic and other content acquisition costs, such as the money Google shares with its creators. Meta’s ad business is seeing a lift, thanks to the success of new ad offerings, including the short-form video format Reels, and the broader boost that artificial intelligence has provided.”

Colossus: “Hyperliquid, a blockchain and cryptocurrency trading exchange, is one of the most profitable enterprises per employee on earth. Last year, its 11 employees generated over $900 million in profit. It is three years old, has a market capitalization of $10 billion, and has never taken a dollar of venture capital. The main figure behind it, Jeffrey Yan, is 31 years old and has become, not entirely by choice, one of the more recognizable faces in an industry.”

Thinks 1956

Bloomberg: “The bigger culprit for the woes of recent grads is an imbalance in supply and demand that’s been quietly building for years: From 2004 to 2024, college completions in the US rose by 54%, according to Lightcast, a labor market analytics company, whereas entry-level jobs suitable for those graduates grew by just 42%. To make matters worse, what students are studying is out of sync with where the economy is creating jobs. The result: In 22 of 35 fields of study, the ratio of entry-level jobs per graduate declined over the past two decades, according to a Bloomberg analysis of Lightcast data. “We’ve never seen so many changes all at the same time and at this speed,” says Elena Magrini, the head of global research at Lightcast. “This is the first time where the education pathway to jobs is kind of broken.””

Decrypt: “Japan isn’t interested in building the next ChatGPT. [Recently], SoftBank, NEC, Honda, and Sony Group jointly formed a new company with one goal: build a trillion-parameter AI model that runs machines, not conversations. The move is a direct bet on what the community refers to as “Physical AI”: the idea that the next frontier isn’t language models that write your emails, but AI systems that control a robot arm, drive a car, or run a factory floor. Japan, with its deep industrial base and decades of robotics heritage, thinks it has a natural edge that Silicon Valley and Beijing can’t easily replicate.”

FT (in the context of Anthropic’s Mythos]: “AI is like the atomic bomb — once you invent the means to build one, you live in a different world.”

Mint: “Consumer brands are reworking their e-commerce marketing strategies as digital advertising becomes more expensive with diminishing incremental reach, prompting a shift away from scale-at-all-costs growth. Instead of relying heavily on marketplace (Amazon, Flipkart, etc.) ads and aggressive discounting, small brands across categories such as food and personal care are now dispersing spends across platforms including their own websites, investing more in brand-building, and focusing on retaining customers. “At scale, it becomes very expensive to advertise because you don’t have enough incremental reach available,” said Jatan Bawa, co-founder of Sauce VC-backed oral care brand Perfora.”

What Doesn’t Change in Marketing in the Age of AI (Part 5)

Ads, Distribution, and the New First-Party Layer

Why ads persist

Advertising will not disappear in the age of AI.

This is one of the easiest mistakes to make when a technology transition becomes noisy. People confuse changes in form with the disappearance of function. AI will change creative production, targeting, testing, workflow, and interface. It will not eliminate the basic need for brands to buy reach they do not own.

If anything, it may intensify that need.

When content becomes abundant, distribution becomes scarcer. This is the pattern across all media history. As production gets cheaper, the bottleneck moves elsewhere. In the AI era, it moves to trusted attention, verified identity, and channels where action can happen with confidence.

That is why advertising survives every major technology shift. Print did not kill radio. Radio did not kill television. Television did not kill digital. New surfaces emerge, older ones adapt, and the total need to buy attention grows because the number of messages competing for notice grows. In an AI world, every brand with access to the same tools produces roughly comparable creative. Distribution — the ability to place a message in front of a genuinely attentive human — becomes the scarce and therefore valuable resource.

The regulatory tailwind for first-party infrastructure

At the same time, the architecture of digital advertising is shifting in ways that favour owned, first-party infrastructure. GDPR, India’s Digital Personal Data Protection Act, cookie deprecation, and the general tightening of data regulation are reducing the reliability of third-party inference. As AI makes behavioural inference from third-party signals noisier — more content, harder to separate signal from intent — the value of declared, verified, first-party identity rises.

The brand that owns a first-party attention surface — a live, engaged, consented audience operating on authenticated identity — is structurally advantaged in the ad market of the next decade. This is not a regulatory compliance argument. It is a commercial one. Verified first-party audiences will command a premium over probabilistic third-party inferences, and that premium will grow as regulation and AI-driven noise compound.

The combination that hasn’t happened

Commerce media — first-party attention monetised through in-context advertising — is already a $100 billion-plus category in the US, growing faster than traditional or digital advertising. Amazon, Walmart, and now brands in travel, finance, and hospitality have built significant ad businesses on one core asset: verified first-party attention linked to identity and purchase outcomes.

But all of it has been built on retailer websites and apps. Nobody has built it inside owned email at scale.

That gap — email plus ads plus action, assembled properly — is where NeoNet and ActionAds sit. The concept is not to stuff banners into email. It is to create action-based, first-party, authenticated media that operates inside a relationship channel the brand already owns. This is the Inbox Media Network.

Two ActionAd formats power the system. The One-Tap Subscribe ActionAd subscribes a customer to another brand’s NeoMails with a single tap — pre-filled email address, no landing page, no form, explicit consent logged at the moment of interaction. The form-fill ActionAd generates a verified lead inside the inbox — contact details, a preference, a qualification question — completed without the customer leaving the message. Both pay per completed action, not per impression. Both operate on authenticated identity, not probabilistic inference. The advertiser pays for demonstrated intent, not passive exposure.

NeoNet as cooperative distribution

Most advertising networks are adversarial by design. Brands bid against each other for the same audience. A platform sits in the middle extracting margin from every transaction. The brand does not own the relationship. It rents it at whatever price the market will bear.

NeoNet is built on a different premise. It is cooperative. Brands exchange access to their own active NeoMail audiences — first-party for first-party, no auction, no platform intermediary. A brand becomes a publisher when it carries a curated ActionAd in its own NeoMails. The same brand becomes an advertiser when it places ActionAds in other brands’ NeoMails to recover dormant customers or acquire new ones. Both directions happen on the same infrastructure.

The quality filter is structural and self-reinforcing. An identity enters the network only after opening at least one NeoMail. Dormant addresses sitting cold in a CRM are not the network. Live attention is the network. The audience receiving an ActionAd is not a stored list of addresses. It is a cohort of people who are actively opening emails, completing Magnets, and building Mu balances. That is a fundamentally more valuable audience than anything a conventional ad network delivers.

Recovery points backward: a customer cold for Brand A but still active inside Brand B’s NeoMails can be reached via a One-Tap ActionAd and returned without either brand entering a paid auction. Acquisition points forward: a customer new to Brand A can subscribe from inside Brand B’s audience with a single tap, creating a genuinely new, consented, verified relationship. Both directions run on the same infrastructure. The cooperative structure means no platform extracts rent from the transaction.

As AI makes programmatic targeting less reliable and first-party identity more valuable, cooperative networks built on authenticated attention become more powerful, not less. The open auction degrades as inference gets noisier. The cooperative exchange improves as the network grows and the quality filter holds.

The Magnet as the first-party signal engine

In an AI world, the highest-quality marketing signal is not passive exposure. It is a human choosing to do something. Answering, predicting, preferring, staking, clicking, subscribing: these are active signals that cannot be manufactured by content abundance alone.

The Magnet is how they are collected — one sixty-second interaction at a time. Mu is how they accumulate into a record of consistent engagement that becomes both a churn predictor and a loyalty indicator. ActionAds monetise the resulting attention surface. NeoNet routes that surface cooperatively across brands.

Remove the live attention layer, and the commercial architecture has nothing to operate on. This is why the system only works as a system. NeoMails create the surface. Magnets generate the signal. Mu builds the memory. ActionAds fund the loop. NeoNet extends it. Each element depends on the others.

The invariants as a system

The three parts of this series describe the same opportunity from three angles, and they connect.

Attention is permanent and scarce — and AI makes it scarcer by making everything around it abundant. Email is the structural owned channel that captures human attention without a platform in the middle — and its relative value increases as rented surfaces get noisier and more expensive. Advertising and distribution remain essential — and first-party, cooperative, action-based infrastructure is the form they take when the open auction degrades.

NeoMails, NeoNet, Magnets, Mu, and ActionAds are not separate product curiosities. They are the commercial expression of the same set of invariants: push, attention, owned identity, relationship memory, first-party distribution. Remove any one of them and the system weakens. Keep them together and they compound.

The closing argument

The AI conversation is dominated by questions about what changes. Who creates the content. How decisions get made. Which jobs disappear. Which interfaces win. These are real questions and they deserve serious answers.

But the most important strategic question is the one being asked less often: what stays true?

The permanent asymmetry between brands and customers. The finite budget of trusted human attention. The compounding value of owned relationships over rented ones. The need for distribution that does not require surrendering the relationship to a platform every time.

Everyone else is asking how to use AI to produce more. More content, more personalisation, more targeting, more automation. These are real gains. They are also crowded gains — every brand with the same tools achieves roughly the same marginal improvements, and the competitive advantage disappears as soon as the tool becomes standard.

The uncrowded question is the one this series has answered: what endures?

Build only on what changes, and you are always catching up. Build on what endures, and you get to compound.

The Inbox Media Network is the commercial architecture built on precisely those enduring layers — attention, owned identity, relationship continuity, and first-party distribution.

That is not a defensive position. It may be the most ambitious one available.

Thinks 1955

Benedict Evans: “The experience, product, value capture and strategic leverage in AI will all change an enormous amount in the next couple of years as the market develops. Big aggressive incumbents and thousands of entrepreneurs are trying to create new features, experiences and business models, and in the process try to turn foundation models themselves into commodity infrastructure sold at marginal cost. Having kicked off the LLM boom, OpenAI now has to invent a whole other set of new things as well, or at least fend off, co-opt and absorb the thousands of other people who are trying to do that.” [via Arnold Kling]

FT: “Are you the person who takes the time to explain to new hires on your team what everyone does? Are you the person who notices when a project is in danger of going wrong because two teams have different ideas of what is actually required? Do you know the name of the person on the third floor who can sort out the fiddly problem that has slowed down your colleague for weeks? If you answered yes to most of these questions, then you are doing “glue work”: you build relationships with people; you can see the bigger picture; you fix the organisational cracks and help to hold projects together…Now is a good time for managers everywhere to ask themselves a few questions. Who is doing the glue work on your team? Are you giving them credit and promotion for it? Are you making sure everyone is learning how to do some of this work? Because in the tech sector, AI hasn’t suddenly made those skills valuable to organisations — they always were. It has just made the fact impossible to ignore.”

Asymco: “As AI has emerged as a technology, we are in a strange position where the interface, born as a chatbot, suggested an infrastructure that is massive in scale. The magic sauce of GenAI isn’t so much the algorithm, which is quite a simple idea. It’s the scale of the data and computation that permits the illusion of intelligence. In developing the commercial idea, investors are imagining the device while investing in the infrastructure. In other words, the investors are poised to put trillions of dollars to work on what amounts to “the grid” without knowing exactly what the motor will be. The cash flows associated with infrastructures are very different from those of devices. Devices are iterated rapidly and evolve to changing tastes and discoveries of behavior. Infrastructures are built once, maintained and perhaps re-built but only after decades. Therefore financing for infrastructures is more likely through bonds (debt) rather than shares (equity). Returns are also much more subdued as the risk for infrastructures is lower. Regulation and relations with labor are also dramatically different.”

WSJ: “When everything from oil prices to ‘Survivor’ is worthy of a wager, everyone needs a bank of screens and a headset…There was a time when this kind of behavior would be called doomscrolling. Now, in the vernacular of our bet-on-anything era, it’s all part of monitoring the situation. People who’ve never worked on a trading floor are moving markets with informed wagers. Some are getting rich.”

What Doesn’t Change in Marketing in the Age of AI (Part 4)

Email, the Missing Relate Layer, and NeoMails – 2

AMP changes the category

Before introducing NeoMails, there is a technical shift worth naming: AMP for Email.

Most people still think of email as a static object — text, images, links, a call-to-action button leading somewhere else. AMP changes that category. It allows forms that submit inside the inbox, polls that respond in real time, quizzes that react immediately, dynamic content that updates on open, and actions that complete without the customer leaving the message.

A static email is a document. An interactive email is a product.

That shift is more significant than it first appears. A surface that can receive input and respond to it is a fundamentally different kind of thing from a document that can only be read. The implications for what email can do in a customer’s daily life are significant and mostly unexplored. NeoMails are built on this infrastructure.

NeoMails as the attention architecture

NeoMails are not a better email template. They are a different category of inbox interaction — one designed for the conditions AI creates.

The unit is the APU: BrandBlock, Magnet, Mu, ActionAd.

The BrandBlock gives the NeoMail identity. The brand’s voice, perspective, and world — before anything is asked of the reader. The Magnet gives it lift: a quiz, a prediction, a preference fork, a tiny challenge that earns engagement before anything is asked of the reader. Engaging with the Magnet earns Mu — the micro-reward currency that builds a visible streak and accumulates over time. The ActionAd funds the send — one curated, brand-approved in-email action unit per NeoMail, covering the cost of delivery and making the Relate message economically rational for the first time.

This architecture is exactly suited to what AI changes and what it does not.

AI makes content abundant. NeoMails are not mainly a content idea. AI makes personalisation cheaper. NeoMails are not mainly a targeting idea. AI makes creative production easier. NeoMails are not mainly a creative-format idea. They are an attention architecture — bounded, participatory, cumulative, self-funding.

Bounded: sixty seconds, completable, with a beginning and an end. There is a cognitive science finding worth naming here: the Zeigarnik effect. Incomplete tasks occupy working memory; complete tasks release it. An infinite scroll produces a form of low-grade anxiety — the sense of having consumed without finishing. A completed NeoMail produces something different: the mild satisfaction of having done a small thing. That satisfaction is not incidental to habit formation. It is the mechanism of it.

Participatory: the Magnet requires the human to do something — predict, choose, rate, answer. Participation generates a first-party signal that no AI-generated content can replicate. A choice expressed, a prediction staked, a preference registered: these are human signals of genuine attention. In an AI era, where passive exposure becomes cheap and abundant, active participation becomes the premium signal.

Cumulative: Mu builds a visible record of the relationship. From the customer’s point of view, the inbox usually has no memory — each send is a stranger introducing itself. Mu changes this. The balance in the subject line says: yesterday mattered. Showing up left a trace. The relationship has a history. Histories are harder to abandon than novelties.

Self-funding: the ActionAd covers the cost of delivery. A message that earns attention is also the message that funds itself. That single economic inversion is what makes the entire architecture viable at scale.

The Relate message as the human signal

When AI generates all the transactional and promotional content, the brand that sends something genuinely worth opening for its own sake stands out precisely because it is rare. A message that asks for nothing except a minute of genuine engagement becomes the rare signal that a human relationship is being maintained — a brand that is treating the customer as a person rather than a conversion target.

That is not a sentimental argument. It is a competitive one.

In an inbox increasingly populated by well-crafted machines talking at customers, the Relate message is the differentiator. Not better AI. Not smarter targeting. Simply: something worth opening when nothing urgent is happening.

Email did not fail because the channel declined. It failed because brands stopped having anything worth saying between transactions. NeoMails are the answer to that failure. And they are more relevant in an AI world than in the one that preceded it.

Thinks 1954

Manu Joseph: “Spare me the young, why should they matter for everything? They have no money, no clout. Even if it was true that they won’t read a magazine, which I don’t believe is true, why should that decide the survival of a product? I notice this fixation with the young in several businesses. It is as though there aren’t other kinds of people on this planet. That is odd when those businesses survive on other kinds of people. In cinema, television, dining, apparel, hospitality, social media and just about any business except hospitals and old-age homes, people at the helm worry a bit too much about the young—how to get them, or how to keep them. Entire nations are obsessed with the young. That insufferable buzzword, ‘demographic dividend,’ is all about this phenomenon. The value of the young is not only their fertility rate anymore, as the average age at which people become parents has been increasing. Their value is said to lie in their contribution to society, which I believe is overblown. They are merely loveable, and society is coming up with excuses to disguise its love for an adorable segment as a wise investment of time and money.”

Benoit Denizet-Lewis: “I’ve come to believe that the “self” in self-transformation is only half the story. Change is less about willpower than we imagine, more shaped by other people than we admit, and far more mysterious than the self-improvement industry can afford to sit with…In other words, we might think of self-transformation as a team sport.”

TheMaxSource: “In the last 12 months, something shifted in the tech-related job market and it didn’t make headlines. Just a quiet, consistent pattern showing up in job listings across tech related industries: ”The specialist titles are shrinking, and the broader ones are coming back.” Not because companies got lazy with job descriptions. Because the economic logic that created hyper-specialization in the first place — that scale required narrow focus — no longer holds the way it did. AI absorbed the repetitive execution. And suddenly, one person with range is worth more than two people who each own a slice.”

WSJ: “The idea behind silicon sampling is simple and tantalizing. Because large language models can generate responses that emulate human answers, polling companies see an opportunity to use A.I. agents to simulate survey responses at a small fraction of the cost and time required for traditional polling. Phone polling has become exponentially harder. Web polling is too uncertain. Silicon sampling removes the messy, costly part of asking people what they think. But this undermines the very idea of the opinion poll. Public opinion is used to guide policy, politics and social science, and it has value only insofar as it summarizes the beliefs and opinions of actual humans. Using simulations of human opinions in place of the real thing will only worsen our broken information ecosystem, and sow distrust. We should not turn to an artificial society to try to understand our real one.”