Thinks 2022

Geometric Investor: “The AI cycle is a stack of four linked ledgers, with different owners, different time horizons, and different required returns: 1. The infrastructure ledger. NVIDIA, HBM and memory suppliers, foundries, advanced packaging, networking, power equipment, and cooling…2. The hyperscaler and neocloud ledger. Cloud incumbents and GPU-rental specialists must convert installed compute into rented or sold capacity at utilization and gross margin sufficient to cover depreciation, power, financing, and the risk that the assets age out before they pay back. 3. The token buyer ledger. Enterprises and consumers must receive more value from tokens than the tokens cost — labor savings, revenue lift, faster software, automation, fewer errors. If the buyer’s return is negative, every ledger below it is being funded by a future that will not arrive. 4. The macro ledger. If token usage raises economy-wide productivity, trend growth and the neutral real rate can rise.”

NYTimes: “Twenty years ago, the words “Stage 4” almost invariably meant “end of life.” A cancer had spread far from where it formed, attacking distant parts of the body and often making treatment impossible. For some, that remains true today. But for a growing number of people, a Stage 4 diagnosis is not the immediate death sentence it once was. New therapies that target specific genes and parts of the immune system, as well as new regimens of existing cancer drugs, have given many patients far longer than the handful of months they might have once hoped for. More than a third of people diagnosed with metastatic disease now live for at least five years, compared with 17 percent in the 1990s, according to the American Cancer Society.”

FT: “We certainly have better tools than ever to try to extract the signal from the noise, even as the geopolitical climate becomes more volatile. “AI is truly a breakthrough when it comes to forecasting events,” says Anthony Vinci, a former US intelligence officer, international affairs expert and author of The Fourth Intelligence Revolution. “I look at the world and no longer trust my personal opinion of what will happen. I need an AI tool to help me.” According to Vinci, there are four ways of trying to assess the probability of future events. A few individual human superforecasters are superb at such analysis. The collective intelligence of an organisation, such as the CIA or a political risk consultancy, can also be applied. The wisdom of crowds can be harnessed through prediction betting markets, such as Polymarket or Kalshi, although these can be manipulated. And a trained AI model can parse these three sources and crunch the data for additional insights.”

Paul Graham: “The key to starting a successful startup is to understand some group of users so well that you can make exactly what they want. If you’re young you can, and should, use the hack of making something for yourself. You understand yourself. But this is just an instance of the more general rule. Only by understanding users very deeply can you make something they love so much that they tell their friends about it, and only that can get you the exponential growth you need to make a startup really successful. There are other ways to get rich than by starting startups. Some of those do require you to exploit people. But startups are the most common way to become really rich, and if you want to start a successful startup, the key is not exploitation but empathy. What do users really want? What could you do for them that would make their lives dramatically better? That kind of empathy is what we look for in founders, and what we cultivate in the ones we accept.”

The Living Email Factory: Easy to Build, or It Won’t Happen (Part 3)

The Factory

The bar: as easy as making an HTML email today.

Start with the design constraint that governs everything else. A living email must be as easy to make as a static one is today — not almost as easy, not easy-with-training, but genuinely as fast and as approachable as dragging blocks into Bee. If composing a living email takes a marketer materially longer than composing a static one, the static one wins every deadline, and living emails stay rare. This means the factory cannot expose any of the underlying complexity — not the AMP, not the fallback, not the data plumbing, not the memory wiring. Familiar on the surface; entirely new underneath.

Seven layers, from intent to memory.

The cleanest way to describe the factory is as a stack of layers, each one absorbing a discipline the marketer used to lack. At the top sits the Intent Layer: the marketer states the job — ‘a Notify email for a delayed shipment’ — and the system begins from purpose, not a blank canvas. Below it, the Block Layer supplies governed, reusable live components. The AI Composition Layer turns them into a customer-specific draft. The Data Layer binds the email to CRM, CDP, catalogue, orders, loyalty, and automation. The Rules and Governance Layer decides what each surface is allowed to carry. The Render and Fallback Layer emits valid AMP and a genuinely good HTML fallback in lockstep. And the Memory and Measurement Layer writes every interaction back to the Context Graph. Each layer is a thing the marketer would otherwise have had to be an engineer to handle — absorbed into the tool, where it belongs.

Figure 2 — The seven layers of the Living Emails Factory. The marketer states intent at the top; a sendable, living, learning email falls out of the bottom.

Block-based, but the blocks are alive.

The factory keeps the one thing about the old editor that works — composition by block — and changes what a block is. In the old editor, a block is an image or a piece of text: pure appearance. In the factory, a block is a live component — a poll, a product carousel, a live-status panel, a size picker, an ActionAd slot — and each carries its own logic, its own data binding, its own AMP build, its own HTML fallback, and its own memory hook, all packaged inside it. The marketer drags in a ‘poll’ the way they used to drag in an image, but the poll arrives complete. The complexity does not vanish — it is packed inside the block, where the marketer never has to see it.

Figure 3 — Anatomy of a live block. The marketer drags it in like an image; the logic, dual render, data binding, and memory hook are pre-engineered once and ride along inside.

Governance is not a constraint bolted on; it is a layer.

The Rules and Governance Layer is where SNR stops being a diagnostic and becomes enforcement. A Notify email may carry live status and a service next-step, but not a random reward mechanic. A Sell email may carry preference capture and first-party cross-sell, but not open third-party demand. A Relate email can carry a Magnet, Mu, one governed ActionAd, and a funding layer, because that is the surface designed to hold them. The factory reads the SNR mode of the email and only offers the blocks that mode permits. The factory does not just make a living email possible; it makes the wrong living email impossible — which is what keeps a bank’s Notify surface from ever sprouting a points game, and a Sell email from leaking a competitor’s ad.

Thinks 2021

Mint: “Every age creates its own managerial obsession. The 1980s worshipped scale. The 1990s celebrated globalization. The first decades of the twenty-first century chased disruption and digital transformation. Today, artificial intelligence has become the new altar before which executives gather. Strategy decks are being rewritten, business schools are redesigning curricula, and consultants are repackaging old wisdom in new algorithmic wrappers. Yet as AI makes knowledge increasingly accessible and expertise increasingly replicable, a more fundamental question emerges: what remains uniquely human in leadership? The answer may lie not in thinking harder but in seeing better. The future may not belong to leaders who know the most. It may belong to those who notice the most.”

FT: “Policymakers who rely on those indicators to judge whether AI is delivering benefits may be missing a deeper shift. The great achievement of modern capitalism was to move activity from the household into the market — converting domestic production into paid specialisation, creating jobs and making output visible to the national accounts. AI-enabled self-service is quietly reversing that centuries-long trend. The automation question — can a machine do this job? — would never have predicted the laundress’s decline. No robot could walk to the well and handwash linens. But the washing machine did not need to. The self-service question — can the customer do without this job? — would have predicted it. If we keep asking the first question about AI, we will keep looking in the wrong place.”

WSJ: “When it comes to the diseases that threaten to steal our healthy years—Alzheimer’s, heart disease, cancer, arthritis—they all have one thing in common: By the time we get diagnosed, often much of the damage is already done. But a wave of new scientific advances have the potential to shift that timeline far earlier.  In the near future, doctors may be able to predict the speed at which your individual organs are aging, and detect cancer, Alzheimer’s and other diseases long before you develop symptoms. GLP-1 drugs, now used for diabetes and weight loss, might be prescribed to protect your heart or brain or to treat a range of chronic conditions. And instead of a knee or hip replacement, you could get new bone and joint treatments designed to reverse physical decline entirely by regenerating tissue in damaged joints. “We’re entering a new era of prediction and prevention,” says Dr. Eric Topol.”

Molly Kinder: “I think what we’re really entering is this messy middle period. It’s a world in which AI gets better and it’s more capable of taking on more work, but we don’t overnight see a jobs apocalypse. Instead, we find something that’s still painful, but more narrow. It’s a world of partial automation, where AI starts to get capable enough to do certain types of jobs, and that is still very painful. A world where most jobs are intact but there’s a concentrated loss is still a world that is politically, societally, and economically explosive. So I’m trying to call attention to this messy middle period, which could last for decades, depending on how good the technology gets. Even in a world where we don’t see a full jobs apocalypse, if we’re seeing a lot of pain in the knowledge sector or early career, that is still going to be something that we feel as a country — and that we’re not prepared for.”

The Living Email Factory: Easy to Build, or It Won’t Happen (Part 2)

Why the Old Editor breaks

A template produces a document; a living email is an application.

Figure 1 — The template editor produces a document: fixed, identical, inert. The factory produces an application: live, per-recipient, learning.

The cleanest way to see the problem is to name the category. A template editor produces a document — a fixed artefact, complete at the moment of saving. A living email is an application — a small program that runs when opened, responds to the recipient, talks to a data source, and records what happened. These are different kinds of thing, made by different kinds of tool. This is why the instinct to ‘add AMP support’ to an existing editor never quite works. You cannot bolt application behaviour onto a document tool and get an application tool; you get a document tool with a confusing new tab that produces broken applications. The right mental model is not ‘next-generation template builder’. It is an experience compiler: the marketer states what the email should do, and the tool assembles the experience that does it.

Five things a living email needs that a template cannot give.

Be specific about what is missing. First, interactivity — the blocks must do something when tapped, which means each block carries logic, not just appearance. Second, per-recipient composition — the email is a template-of-one, filled differently for each person. Third, live data binding — a balance, a delivery status, a price, fetched at the moment of opening rather than baked in at send. Fourth, memory write-back — every interaction routed back to the brand’s record of the customer. Fifth, dual rendering — an AMP version and an HTML fallback, kept in lockstep, from a single definition. Each is a discipline a template editor has no concept of. The missing capability is not in the marketer. It is in the instrument.

The trap: asking the marketer to become an engineer.

Faced with this, the tempting answer is the wrong one: give the marketer the raw materials and let them assemble the application by hand. Hand-author the AMP. Maintain the HTML fallback in parallel. Wire the data calls. Set up the memory routing. Test across a dozen clients that each render AMP slightly differently. This does not scale, for a simple reason. The people who make marketing emails are marketers, and they will not become engineers to send a newsletter — nor should they. A handful of sophisticated brands will hire the talent and produce a few beautiful living emails a quarter. That is not a channel; it is a craft project. For living emails to be the default, the engineering has to disappear from the marketer’s job entirely. The marketer’s job is to know the customer and the message. The tool’s job is everything else.

Thinks 2020

WSJ: “Clipping, the marketing tactic of paying armies of people to cut longer videos into short viral clips, has inspired debate over how real popularity on TikTok or Instagram is. When they don’t disclose their identities or the paid nature of their work, clippers leave others to guess whether a band, politician or influencer is really as crowd-pleasing as they seem. But for many marketers, clipping is just one more way to catch consumers’ shrinking attention and to squeeze every drop of value from a piece of content…Clipping is a new name “for something good marketers have always done: Meet people where the energy is at. Show the recap. Show the blooper reel,” said Zaria Parvez, director and head of social at DoorDash.”

Satya Nadella: “Companies need to turn their workflows, domain knowledge, and accumulated judgment into AI systems that improve with each use. Private evals should capture whether a model is actually improving against outcomes that matter to the business (not just external benchmarks!). Private reinforcement learning environments should let models grow stronger on real traces from inside the organization. Its knowledge base makes institutional memory queryable and use of tokens more efficient. This loop becomes the new IP of the firm.”

Business Standard: “India’s fertility rate has fallen below replacement level, but the bigger question is whether the economy can create enough jobs and raise productivity before ageing pressures build…India’s demographic arithmetic remains favourable. But the nature of the demographic dividend is changing. The next phase will depend less on how many people enter the workforce and more on whether they can find productive work, acquire relevant skills and generate higher output.”

NYTimes: “For more than two decades, Farid, 60, had been the world’s leading expert in the field of digital forensics, but in the last six months he’d stopped trusting his own eyes. He’d made a career of differentiating visual reality from deepfakes as he fielded requests each day from governments, human rights organizations, journalists, law enforcement and thousands of others who were increasingly confused and deceived by the online world. Farid’s own research had proven that most people could no longer distinguish a real photograph from a digital creation, a real voice from an A.I. clone, a real video clip from a wholesale fabrication. Lately, he was failing his own tests. “I feel like I’m going blind,” Farid said, and he worried that A.I. was obscuring the truth, distorting reality, fracturing democracies and slowly breaking him, too.”

The Living Email Factory: Easy to Build, or It Won’t Happen (Part 1)

Living emails will not exist until they are as easy to make as static ones — which means the next email tool is not an editor but a factory that compiles experiences

The Production Gap

The architecture essay argued that the static template is obsolete, and that AMP, AI, ActionAds, and Atomic Rewards can rebuild Sell, Notify, and Relate into living surfaces. It made one concession near the end and then moved on: living emails are materially harder to produce than static ones, and the tooling to make them is itself something to be built.

That concession is the whole subject of this essay. A living email that only an engineer can build will never be sent at scale, because the people who make marketing emails are not engineers — they are marketers who today drag image blocks into a template. The answer is a new kind of authoring environment — a Living Emails Factory — that makes a living email as easy to compose as a static one, connects to the brand’s data by default, and hands the engineering to AI rather than to the marketer. The tooling is not a support layer beneath the thesis. The tooling is the product.

**

Every part of the living-email argument assumes the email gets built. The interactive poll, the live-on-open status, the per-recipient hero, the funded ActionAd, the memory write-back — each is described as though it simply appears in the inbox. None of the prior work said how. The gap between ‘this is what a living email does’ and ‘here is how a marketer makes one’ is where most good ideas about email quietly die. A static promotional email can be assembled by one person in an afternoon using tools that have existed for fifteen years. A living email — interactive, personalised per recipient, bound to live data, rendering in both AMP and HTML, and writing its results back to memory — is, with today’s tools, a small software project. No marketing team ships a small software project every Tuesday.

Today, an email is built by dragging images into a template.

Look at how marketing email is actually made. A marketer opens a drag-and-drop editor — Bee, the editor inside their ESP, or a builder an agency maintains — and drags in a banner, a row of product images, a block of text, a button, a footer. They style it, preview it, and send. The output is an HTML document: a fixed arrangement of images and text, identical for everyone who receives it, that does nothing once it lands. This toolchain is mature, fast, and widely understood. That is its strength and the reason it persists. But every assumption it rests on is an assumption a living email breaks. The block is an image. The output is a document. The content is the same for everyone. Nothing updates after send. Nothing is remembered.

Thinks 2019

The Next China Is Still China: “There is no substitute for the Chinese market. China accounts for a staggering 30% of global manufacturing and 18% of global GDP, surpassing the European Union and trailing only the United States. With nearly five million STEM graduates each year (more than the total number of US degree graduates across all fields!), China is well-positioned in an era of technological automation, artificial intelligence, and data-powered innovation. However, the strategies that once propelled businesses to success in China are no longer sufficient. A new playbook is needed.”

NYTimes: “A technology — known as plug-in, balcony or garden solar — is already enormously popular in Germany, in part because you can buy a kit for less than $600 at IKEA. It’s a small solar panel system, often producing up to 1,200 watts of electricity, or generally more than a refrigerator consumes, that you can affix to a wall, hang on a railing or prop up in a garden — and then plug directly into a wall socket. With the help of a small device called a micro inverter, it pumps electricity into your household circuits to offset your power demand.”

Manu Joseph: “The best way for a startup to survive in Indian politics is to promise it’s temporary. You can achieve a lot in this world if you reassure people you are not permanent.”

FT: “McKinsey’s assessments of aspiring junior consultants include a “problem-solving” interview that presents candidates with a typical client challenge. This might be how to reallocate and retrain beauty advisers for a cosmetics company, or whether a truckmaker should invest in electric fleets. “We are trying to mirror the problems they will encounter,” says Marie Christine Padberg, partner of talent attraction at the consultancy. Since the end of last year, McKinsey has added a new component to the recruitment interviews: the use of AI. It wants candidates to show how they use it to research and analyse data, test and refine their ideas.”

A Day in the Inbox

The same customer, the same day, the same emails — one inbox forgets her six times; the other learns at every touch

The inventory essay named where the attention is. The architecture essay rebuilt what the email should become. This one walks a single day and shows the difference being real.

Overview

This essay makes the case for the living email the way it is best made — not as an argument, but as a day. We follow one customer, Aanya, through a single ordinary day of brand contact, and we run the day twice: once under the static template that email has used for fifteen years, and once under the living architecture of Sell, Notify, and Relate.

Same person. Same emails. Same moments. By nightfall, the static inbox has forgotten her six times over; the living inbox has learned something at every touch. The point is not that the living emails are prettier. The point is what each inbox does with the day.

1

The set-up

Meet one customer, one day.

Aanya is not a persona. She is an ordinary customer of a handful of ordinary brands — a shoe retailer she ordered from this week, her bank, a fashion label she once bought a coat from, a coffee brand she likes. Over the course of one unremarkable day, she will receive a handful of emails from them. Nothing dramatic happens. No campaign launches, no crisis, no big purchase. It is the most common kind of day there is.

That is exactly why it is worth examining. The value of an inbox is decided not on the big days but on the ordinary ones — the quiet stretch of routine contact that makes up almost every customer relationship. We will watch Aanya’s ordinary day twice, and the only thing that changes between the two versions is the architecture of the emails she receives.

The static inbox treats every email as a disposable event.

Under the static template, each email Aanya receives is a sealed, one-way event. It arrives, she opens it, she reads it, she closes it, and it leaves no trace and connects to nothing before or after it. Six emails in a day means six disposable events — six moments of attention spent and then discarded.

The static inbox has no memory of its own customer by dinner. Each brand that wrote to her this morning knows no more about her this evening than it did yesterday. The attention she gave — and attention is the scarcest thing she has — was consumed and lost. Here is her day, set out both ways before we walk it.

Figure 1 — One ordinary day, lived twice. The static inbox goes silent by evening; the living inbox keeps earning attention.

2

Morning

8:02 AM — the shipping update.

The day’s first email arrives over breakfast: her trainers have shipped. Under the static template, it is a receipt. “Your order has shipped,” a tracking number, a button that opens a browser tab to a carrier site that may or may not load before she gives up. She reads the one fact she needed — it’s coming — and closes it. The email did its single job and asked nothing of her.

Under the living architecture, the same email opens to a live map: the courier is twelve minutes away, the parcel is out for delivery right now, and a single tap tells it to leave the parcel at the door. The recipient already wanted exactly this information, so live-on-open turns a stale receipt into a useful instrument. This is the clearest use of AMP in the whole triad — Notify becomes live. And in setting her delivery preference, Aanya has told the brand something it did not know a minute ago.

Figure 2 — 8:02 AM. Same delivery, same moment. One is a receipt; one is an instrument.

9:30 AM — the bank statement.

Mid-morning, her bank writes. The static version is the familiar dead end: “Your statement is ready,” a PDF she won’t open and a “log in to view” link she won’t follow. The living version shows her balance live on open, a simple breakdown of where the month went, and a pay-now control in place. The receipt becomes a panel she can actually use.

But the bank statement is also where the architecture shows its restraint, and the restraint is part of the story. There is no reward here, no points, no third-party offer — because this is a regulated, trust-critical surface, and the living architecture deliberately declines to monetise it. A bank email that tried to gamify a balance or slip in an ad would breach the very trust that makes it valuable. What the living inbox refuses to do on this surface matters as much as what it does on the others.

Figure 3 — Morning and midday living screens – live Notify, controlled Notify, interactive Sell.

3

Midday

1:15 PM — the promotional email.

After lunch, the fashion label she likes sends its big sale. The static version is the poster we all know: a banner shouting twenty per cent off, a wall of eleven products beneath it, a “Shop Now” button at the bottom. Aanya scrolls past most of it and closes it without buying. The email taught the brand nothing — not even that she looked.

The living version is three picks, composed for her by the brand’s understanding of what she has liked before, with a size she sets once and the email remembers. The long poster shrinks to a few interactive decision blocks — Sell becomes a decision rather than a catalogue. She still doesn’t buy today. But she sets her size, and she taps a heart on one coat. The selling email becomes less desperate, because it no longer has to force every open into an immediate sale. A non-purchase that taught the system something is worth more than a static poster that taught it nothing.

Figure 4 — 1:15 PM. The long poster becomes a few interactive picks she can act on.

The quiet contrast at the day’s midpoint.

Pause at one o’clock and look at the two inboxes side by side. They have each shown Aanya the same three emails. The static inbox has retained nothing from any of them — three opens, three closes, three blanks. The living inbox has learned her delivery preference, confirmed her comfort with her own spending, and captured her size and a hint of her taste.

Same three emails. One inbox is accumulating a customer; the other is discarding one. The divergence is not in how the emails looked in the moment — it is in what survived the moment. And the day is only half done. The sharpest contrast is still to come, in the hours when the static brands fall silent.

Figure 5 — By midday, the living inbox has started compounding.

4

Evening

7:30 PM — the relationship moment.

Here is the part of the day the static template cannot reach. It is half past seven, Aanya is on the sofa, and her static inbox is quiet. The brands she bought from this morning have nothing to send her between sales, so they send silence. This email simply does not exist in the static day — not because the brand chose restraint, but because it has no format and no funding for a relationship that isn’t a transaction.

In the living day, the coffee brand she likes sends its daily moment: a thirty-second poll, a streak now twelve days long, a small Mu reward, and a single funded partner offer that quietly pays for the send. It is welcome precisely because it asks little and gives a little. Relate is the surface that does not exist today — the one the architecture does not improve but invents — and it is the difference between a brand Aanya hears from twice a year at a discount and one she hears from every evening by choice.

Figure 6 — 7:30 PM. The static brand has nothing to send. The living brand has a daily habit.

9:00 PM — the moment compounds.

Later, the same relationship surface offers something more than a poll: a prediction on tonight’s match, staked with the Mu she has earned, set against her own small circle of friends, with a score that ticks up when she calls it right. The static inbox, of course, offers nothing — it has been dark since lunch.

The detail that matters is not the game. It is that Relate is not a single email but an accumulating relationship — with its own small economy, its own social loop, its own reasons to come back tomorrow. By the end of the evening the living brand knows Aanya’s rhythm, her circle, and a little of what she enjoys. The static brand has spent the evening, like the day, in silence.

5

The reckoning

The two inboxes at midnight.

Lay the day’s ledger out. The static inbox handled five moments — four emails and one evening of silence where a fifth should have been — and holds nothing from any of them. Aanya is exactly as unknown to those brands at midnight as she was at dawn. The living inbox wrote to its memory at every touch — not as surveillance, but as service: a contactless-delivery preference, a spending comfort, a size and a style lean, an evening rhythm, a prediction circle. Six new facts, where the static inbox kept none.

Figure 7 — The static inbox spent the day’s attention. The living inbox invested it.

The compounding is the whole point.

A single living email is only marginally better than a single static one — a nicer experience for thirty seconds, then closed. A whole day of them is categorically different, because each interaction sharpened the next. The living brand’s morning email made its afternoon email smarter; its afternoon email made its evening email smarter still. Every touch wrote to the Context Graph, and tomorrow’s emails will be composed from what today’s learned.

That is the real difference between the two inboxes, and it is not six better emails. It is the presence or absence of a learning loop. The static inbox spent the day’s attention and had nothing left at midnight. The living inbox invested it, and will draw on it tomorrow. One day of this looks like a small edge. A year of days is a different relationship entirely.

The close.

Return to Aanya, asleep now, her phone dark on the nightstand. Under the static template she is a list entry that received four sends and ignored most of them. Under the living architecture she is a relationship that deepened, quietly, by one ordinary day.

Same person. Same day. Same emails.

***

One inbox forgot her by nightfall. The other knew her a little better than it did at dawn — and will know her better still tomorrow.

Thinks 2018

Foreign Affairs: “Because quantum computing has the potential to crack the encryption most broadly used by governments and individuals alike, the threat that it poses to national security is difficult to overstate. The cryptography that secures much of the Internet today relies on the difficulty that conventional computers have solving certain math problems, such as factoring very large numbers. Quantum computers, however, are expected to perform some of these computations far more efficiently, enabling attackers to break the codes and seize sensitive data. No such machines exist yet, and it is difficult to predict when they might come online. But recent advances suggest that a quantum computer could break at least some forms of commonly used cryptography within the next few years. More important, rivals of the United States are not waiting around for a quantum computer to materialize. China and Russia have already collected encrypted U.S. secrets, betting that some of the information will still be relevant once they have the tools to decrypt it.”

NYTimes: “Humanizers rewrite A.I.-produced text to make it sound less robotic, formulaic and trite. Autotypers slowly drip words and sentences into documents, making it appear as if papers were typed at a human pace when in fact, they were produced by A.I. They even fabricate typos, deletions and revisions. Both tools can help students evade software designed to detect A.I. Colleges and K-12 schools are trying to keep up, with A.I. detection becoming a significant expense. But educators attempting to restrict the technology, worried about students failing to develop basic skills, are often lagging in what tech-industry leaders are calling a detection arms race.”

Luciana Lixandru: “A large percentage of large company founders in the US are repeat founders. Not repeat founders who had a mega-exit. It’s repeat founders who had the modest exit but had a taste for success. And the second time around, they want to go bigger and bolder. They’ve learned from their own mistakes. Often, they already know who their co-founders are. So we find that this profile of founders works incredibly well in the US. And now we’re seeing these people in Europe because the ecosystem is mature enough and because they’ve had time to build and exit and have another idea and start again.”

WSJ: “The search for the ideal office design has produced a rotating cast of answers—open floors for collaboration, private rooms for focus, hot desks for flexibility. But the search often misses something fundamental: The real driver of productivity isn’t the layout. It is how much control—or agency—people have over their own space. This shouldn’t come as a surprise: The ability to shape how you work—what you do, how you do it, where you do it—is central to both satisfaction and performance. Take that away and the message is clear: You’re a cog. Office space is no exception. Tell employees they are empowered while assigning seats and locking down the furniture, and the space undermines the message.”

Email’s New Architecture: Sell, Notify, Relate (Part 5)

The Two Constraints

The AMP reach ceiling — design fallback-first.

AMP renders in only a subset of email clients — Gmail, Yahoo, and Mail.ru. A large share of every base, including Apple Mail and Outlook, sees only the HTML fallback. If the new architecture depends on AMP for its value, then a third to half of all recipients experience the old static email, and the result is a two-tier channel that works for some and not others.

The discipline is to design fallback-first. The HTML version has to be genuinely good on its own; AMP is the enhancement layered on top, never the floor. An architecture that only works for Gmail users is a smaller and weaker claim than the one this essay is making. The honest version treats the static fallback as a first-class deliverable and lets AMP raise the ceiling for the clients that support it.

AMP raises the ceiling where it renders. The HTML fallback sets the floor everywhere.

Living emails are harder to produce — and the tooling is itself the product.

A static email is easy to author. A living email — interactive, personalised per recipient, monetised, and writing back to memory — is materially harder. It breaks across clients, it demands new authoring skills, and it requires the sender to be AMP-registered in the first place, which is its own gate of DMARC and deliverability work.

An architecture that asks marketers to hand-build micro-apps will not scale, because they will not do it. So the architecture depends on tooling that makes a living email as easy to produce as a static one — and that tooling is itself something to be built. This is where the agentic-marketing layer and TwinFactory earn their place in the story: not as features bolted onto the side, but as the production system without which the whole architecture stays a slide. The primitives describe what a living email can be. The tooling is what determines whether anyone can actually make one.

***

The future of email is not more campaigns. It is a new architecture of living emails — Sell that helps customers decide, Notify that helps customers act, Relate that helps customers stay connected. AMP provides the interactivity, AI provides the personalisation, ActionAds provide the funding, and Atomic Rewards provide the habit. Applied unequally, matched to intent, and designed fallback-first, they turn the inbox’s oldest format into its most capable one.

The static template had a thirty-year run. It is over.

Email stops being a message you send. It becomes a surface the customer lives on.