The Spigot

I keep thinking about how we ended up here.

My kids are three and five. I have been in this industry for twenty two years. You would think that somewhere along the way I would have put together a coherent mental model of how the technology industry works, and make sense of what is happening. Something that I could wrap up as wisdom, or advice, or maybe just a pointer as my kids think about their future in a few years time.

Instead, I have been reacting. Lurching from one cycle to another. Mobile, Cloud, Crypto, AI and whatever comes next. As I navigate each cycle, like a befuddled tourist, the scale gets bigger. Each time, it seems that fewer people are thinking and the explanations for what is happening and why are more confused.

So I have been reading. Postman. Karen Hao’s Empire of AI on Sam Altman and OpenAI. Sebastian Mallaby’s The Infinity Machine on Demis Hassabis and DeepMind. Kyla Scanlon on the strange economics of the moment. And I have been trying to put together a through-line. The outline of a semi-coherent narrative that gestures towards why we end up here – arguing about data centers, fretting about AI, as the world literally burns.

I think it starts with a banner ad.

October 27, 1994

Bill Clinton was President, and Marc Andreessen had just released the Mosaic web browser just a year earlier. On that date, Wired Magazine’s digital spinoff, HotWired, launched its website with about a dozen paid advertisements. One of them was for AT&T. It was 476 by 56 pixels. It asked: “Have you ever clicked your mouse right HERE? You will.” Clicking it took you on a virtual tour of the world’s great museums.

The world’s first banner ad

By today’s standards, it was quaint. I suspect it was quaint even by the standards of 1994. But it was the beginning of something that would birth an enormous range of products and services: from social media to AI slop. But at the time, nobody involved thought they were the catalyst to the creation of a giant industry.

Within a year of HotWired’s launch, it was followed by Lycos, Excite, InfoSeek, and others – each company created with advertising as their primary business model. By the time Google created AdWords in 2000, the model was established. By 2014, Google alone was generating $60 billion a year in ad revenue. In 2025, Google brought in nearly $295 billion.

Nobody planned this. Andrew Anker, the former investment banker who wrote HotWired’s business plan, settled on advertising because it was, as an oral history of the era describes the only logical revenue stream he could envision. So, the humble beginnings of the business model that today underpins Meta,Google, and one that upstarts like OpenAI are staking their future on. An incidental decision, that became possibly the most profitable business model ever invented.

The same decision was also the inflection point from where technology went from being the domain of a handful of nerds and dreamers in a sleepy suburb of San Jose to the dominating social and economic force it is today. It is also where the trouble starts.

The Spigot Opens

Digital advertising became the canonical business model as the world went online. Technology meant zero marginal costs, global reach, and rapid dissemination. It generated staggering amounts of surplus capital concentrated in a handful of companies. Google, Facebook, Yahoo before them and many others to follow. The venture capitalists who were early investors in these companies generated mind boggling returns. Serving targeted ads at scale became a money printer.

All that surplus capital needed somewhere to go.

Capital chases returns. When you have that much money looking for a home, the bar for “this might work” drops dramatically. The entire Venture Capital business model is predicated on finding that one unicorn that would generate massive returns. You can see multi-billion dollar bets on businesses leasing office space for a loss while wearing the accoutrements of a technology company were justified.

For a VC, sitting on uninvested funds means your fund underperforms, your investors look to greener pastures. So you fund whatever has the ceremonial language of disruption. You fund NFTs, you fund fancy juice makers, because the alternative would be irrelevance.

The Juicero (RIP) – disrupting the fruit squeezing industry

The post-pandemic crypto boom seems like a fever dream now. Billions raised on the promise that pixelated pictures of digital apes would one day sublimate into collectible and unique art. Investors poured money into automated money-making machines based on complicated DeFi (Decentralized Finance) protocols that required a PhD in applied mathematics and the willingness to suspend disbelief.

I wasn’t immune. I spent way too much time trying to understand how Bitcoin works (and wrote a terrible science fiction story trying). I spent my hard-earned money on staking out some space on the blockchain. Money that could have gone to my kids’ 529 plans. Sorry girls. I wasn’t the outlier though. People way smarter than me poured millions into something that was, when you stripped away the jargon and the vibes, the world’s slowest and most expensive database.

How did this happen? How did so much capital get allocated (and is still allocated!) on something that is so obviously broken?

It is downstream of the spigot. There is so much money in the system, generated by that initial accident of online advertising, that it has to go somewhere. And the job of any ambitious entrepreneur is to provide it a plausible channel. Once the money starts flowing, it becomes self-reinforcing. More money validates the narrative. The narrative attracts more believers. More believers attract more capital. FOMO reigns supreme. The cycle runs until something breaks the spell.

Technopoly

Neil Postman wrote Technopoly in 1992, before the Internet was really a thing. I finished it a few weeks ago and it’s been rattling around in my head ever since.

Postman, a famously skeptical and uncompromising media critic, defined a technopoly as a society that has surrendered its decision-making to technology. Not in a “I welcome our robot overlords” way, but through a blind submission to metrics and statistics of dubious value. His examples – IQ tests, a man “drowning in a river that is, on average, four feet deep”. A society where technology becomes dominant through a self-perpetuating loop where it drives investment in itself, regardless of the impact on human-well being. Does this sound familiar?

Postman didn’t believe resistance was futile

I am also reading Sebastian Mallaby’s The Infinity machine. What comes through in his account of Demis Hassabis, Elon Musk, Larry Page and other industry titans is just how each of them operates with a profoundly different view on Artificial Intelligence – set to be the dominant technology of the 2020s and beyond. Hassabis comes across almost monk-like – viewing AI as the means to understand the nature of existence. Page as a transhumanist who sees the body as a shell to be discarded and the machine as the vessel for eternal life. Musk as a self-appointed guardian of a very particular vision of humanity – presumably with him as some sort of God-Emperor. These are the people who are deciding how and where the most consequential technology in a generation is deployed.

Consider the data center buildout. Trillions of dollars of private capital are being deployed to construct AI infrastructure at a pace that makes the railroad boom look modest. Even adjusted for inflation.

The rationale behind the investment seems to follow a circular logic. AI requires compute for training and inference, so you build data centers and fill them with compute. You fill them with compute which makes rapid deployment of AI possible and sparks massive competition between foundation model companies and hyperscalers to build, fundamentally, the same things. That in turn drives further demand for compute, and so on.

And AI is not just another speculative bet sitting alongside the economy. In 2026, it is the economy. Kyla Scanlon put it plainly: as AI swallows more and more capital, it has become the stock market and the economy simultaneously. The same companies – Microsoft, Google, Amazon, NVIDIA, etc. bankrolling the AI infrastructure buildout are also its biggest customers. Data center construction and investment in AI is driving GDP growth without growing jobs. Scanlon calls it a “jobless expansion“.

The prosperity exists in balance sheets and in the giant data centers sprouting up along state highways in places like Northern Virginia and Tennessee. It does not exist in communities that have been hollowed out as manufacturing evaporated and a career meant becoming the meat interface of a faceless algorithm directing you to the next gig.

Postman would have recognized this instantly. Nobody is in the driver’s seat. No single actor decided this was a good idea for society. No democratic process approved it. The technology cycle itself is driving societal change without any significant discussion. We have abdicated to the technology itself.

I wrote this in my notes on the book: “FOMO-driven investment in AI data centers with little to no prospect of broad societal benefits. We could have spent this money on climate change remediation or education or universal healthcare but here we are.”

Here we are.

The Arbitrage Trap

So there is a clear sense of a backlash brewing against technology. Try posting a pro-AI take on Threads or Bluesky and see the reaction. It’s not just the keyboard warriors who are ready to fight. A young man threw a molotov cocktail at OpenAI CEO Sam Altman’s house last weekend. Politicians who oppose moratoriums on data center constructions are threatened. There is a sense of rage as a new generation emerges into the post-ChatGPT landscape of disappearing knowledge work and the deep sense of careers and meaning being stolen by algorithms and trillion-parameter models.

But there is a key point that is missing in the public discourse. When Bernie Sanders “debates” Claude, it isn’t a meeting of equals. Bernie is an influential Senator and can call for moratoriums, hearings, and regulation. But Anthropic just raised billions of dollars in private capital. Claude runs not on the public dime, but on VC dollars. If Sanders pushed for a ban on data centers in Vermont, they will just build them in North Dakota. It doesn’t really matter where the data center sits. If the capacity is built out, compute will be deployed, and that compute will reshape the day-to-day work of people whether they want it or not.

Hope Bernie has a Claude Max plan

Jasmine Sun, who writes one of the sharpest Substacks on AI and Silicon Valley culture, spent time in DC and San Francisco earlier this year tracking what she calls “AI populism.” Her observation is stark: there is a widening chasm between the people who are building and funding this technology and the people who will live with its consequences. Politicians gearing up for the 2026 midterms are scrambling to design their AI agendas. Labor unions, environmentalists, social conservatives are all rushing to come up with a position.

But the backlash lacks a mechanism to break the capital flow. Moratoriums work only if they are coordinated and enforced. Otherwise you just get regulatory arbitrage. Capital exits to friendlier jurisdictions, and the places that resisted end up with neither the investment nor the jobs. That is the trap.

And if you want to see the arbitrage logic taken to its absurd conclusion, look no further than Elon Musk’s push for building data centers in space. As they say, in space, no one can hear your strident demands for a datacenter moratorium.

Spending a trillion dollars to deploy millions of GPUs in space seems insane, but it is also internally consistent with the incentive structure.

The Ratchet

The AI investment cycle can be best described as a ratchet. It moves only in one direction before locking in place. We seem to be committed to seeing where this cycle plays out – even if it ends in tears.

Sun points out the worst case scenario in a recent post – “One nightmare is a future where we get AI that’s good enough to wreak social and economic havoc, but not yet good enough to cure cancer / solve climate change / deliver 10% GDP growth. In that world… who pays?”

I work with AI every day. I run teams that build with it. I can see the utility. I have watched it compress weeks of work into hours and deliver real value for my clients. I am no old man shaking my fist at the clouds. But I also know that when the backlash arrives in full force, when the torches are lit and the pitchforks come out, the distinction between “I used AI thoughtfully” and “I profited from AI” will not matter. I worked in investment banking in 2008, I know what it means to be a social pariah.

People like me, who have bet careers on this technology being useful, will be caught in the same sweep as the people who bet billions on it being transformative. Everyone on the ratchet moves in the same direction. And yet, apart from the odd paper, there are little to no concrete suggestions from the same billionaires about how to make technology work for everyone apart from some vague gesturing to super-intelligence and to abundance.

And what feels like willful delusion rather than mere miscalculation is that the ratchet keeps clicking forward even as the world around it deteriorates. The United States, Israel, and Iran are in an active military conflict with direct strikes and counter-strikes. The Strait of Hormuz, through which a quarter of the world’s traded oil passes, is under threat. Russia’s invasion of Ukraine grinds on. These are the kinds of events that should be sending capital fleeing to safety. Instead, the markets shrug and carry just .. carry on?

Trying and Failing to Understand the World

I started this year realizing that I did not have a coherent mental model to explain what was happening. I read Postman, Hao, Sun and Scanlon to try and see how others made sense of a world so utterly dominated by technology and the eccentric billionaires who control it.

I ended up with a series of explanations that seem to involve some sort of hardware. Spigots, ratchets, and data centers in space. But I do not think I have a mental model. I do not think I can predict what comes next except a vague feeling that we will continue to spin faster until the whole edifice comes crashing down or we ascend to the singularity.

Postman’s views on the subservience of humanity to technology appeal to me because they seem to be manifest everywhere I look. From people scrolling aimlessly on their phones to pouring out their darkest secrets and deepest fears into the maw of a trillion-parameter language model. It is grim stuff.

But Postman also offers a solution. He calls it a “thoughtful rebellion.” Maybe the movement to touch grass, the surging sales of physical books and vinyl are signs that there is a genuine desire to disengage from digital technology. But how much of that movement is itself driven by mimetic desires pushed by algorithms, through BookTok and the like?

Perhaps technology provides its own means of meaningful disengagement. And maybe that is the only, if unsatisfactory, answer.

My kids will inherit a world shaped by decisions nobody consciously made, funded by a torrent of money nobody voted to spend, run on infrastructure nobody asked for. The best I can do is to show them the machinery that drives the world. And hope that they can find a way.


Agency and LLMs as Mentors

Cate Hall, writing on Substack, suggested that a way to do hard things is to ask “What would someone 10x better do?” and then do it. Reading the post made me realize that agency – the belief that we can ‘just do it’ – is what holds most of us back from success.

I saw this play out again and again growing up in India in the 1980s. You were expected to do as you were told, to not question authority, to focus on getting credentials – degrees, membership of networks, family connections – to get ahead in life. I was lucky to have mentors who encouraged me to read and indulged my curiosity. But millions of kids weren’t so lucky. Who didn’t have anyone to talk to about books, art, movies, and… well… dinosaurs.

What’s forgotten in debates about AI replacing human creativity, taking jobs, or generating slop is that these models can act as expert mentors.

Don’t have anyone to help you with a presentation? Ask AI Simon Sinek to give you feedback. Thinking about how to live your life? Get AI Marcus Aurelius to talk to you about Stoicism. Never written a love letter? Maybe AI Jane Austen could help..

This democratization extends beyond learning into creation itself. Those who sneer at people creating Miyazaki-style images are practicing the same gatekeeping that once kept mentorship exclusive.

Yes, those profile images may seem trite, but they’re also gateways – introducing millions to the worlds of ‘My Neighbor Totoro’ and ‘Spirited Away.’ More importantly, they make it possible for anyone to create, explore, express…

People today have access to world-class mentors via AIs on their phones, regardless of whether they live in Boston or Baroda. These mentors may just be the catalyst to inspire a generation of young people to say, “I can do it.” To embrace agency and set themselves up to do impossible things.

Without gatekeepers, without credentials, without someone telling them what they can or cannot do.

PS – This image is an AI rendering of one of my favorite portraits of my daughter and our dog. Photography was also once looked down upon as “not really art”. Today, it remains one of my favorite hobbies and ways of creative expression.

Obesity, Second-Order Consequences & ..Molds?

I came across this series of posts on the root causes of Obesity by Slime Mold Time Mold, a delightfully weird pseudonym for the team behind the posts. The posts are long, well researched, and, despite the weighty content (haha), quite fun to read.

The blog series is not complete, and I am fascinated to see what comes next.


The writers start with the observation that we have seen a startling increase in obesity rates from 1980 to the present day as seen in the animation below from Our World in Data.

As of 1980, around 11% of the population of the Americas was obese. In 2016, this went up to a staggering 28%. What has caused this?

The team at Slime Mold Time Mold (SMTM) reviews research and data spanning the last 150 years. From studies done on the BMI of Civil War veterans to looking at rates of obesity in Macaques – they cover an incredibly wide range of material. Their thesis is that 1980 was an inflection point – after 1980 we see soaring rates of obesity across the industrialized world.

Strangely, this increase does not seem to be driven by a big change in the total number of calories consumed or in the way that we live our lives. Indeed, the diets in the early 20th century were more calorific and unhealthy than present-day diets.

Just think of all the big dinners on Downton Abbey.

Carbs, glorious carbs..

We eat fewer carbs today than we did a hundred years ago. While the research does show an increase in the total number of calories consumed, the data does not support the increase in obesity rates being driven by an increase in calorific consumption.

SMTM’s thesis is that environmental contamination is an important driver of the increase in obesity rates since 1980.

They look at a number of different culprits – Lithium, a group of chemicals called PFAs as well as the presence of antibiotics in livestock.


If indeed environmental contamination is a primary driver of the obesity crisis, we are looking at a public health scandal that will be bigger than smoking or lead in gasoline. The jury is still out, but SMTM’s work seems to point to a strong correlation.

It also makes me think, again, that we are very poor at thinking through the second-order consequences of our actions. I think we are tinkerers by nature and are biased to action. This has helped us make a lot of progress in a short time – but we are also continuously fixing (or abandoning) things that we have broken along the way.

Environmental contamination and obesity are just another of a variety of different examples of “progress” messing things up. Maybe the research will identify a smoking gun and the problem will be regulated away.

We are strikingly poor at figuring out how complex systems operate and how they may trigger feedback loops. Global warming, disinformation on social media, and many other modern ailments can be tracked to us not being able to think through the consequences of our actions.


So what is the solution? One way is a monastic retreat to the wilderness. But when even remote Alaska is contaminated with PFAS chemicals, retreat does not seem to be a viable option. Maybe we need to push regulatory bodies for stricter enforcement of laws and punitive measures for those who do not comply. But the revolving door between big government and big chem does not fill me with confidence that this is an avenue that holds much hope.

The one, teeny-tiny, ray of hope comes from us being able to deploy massive computational power to model and simulate the world a little better. Perhaps we could get better at figuring out how complex systems interact and that might help towards a more thoughtful and considered approach to change?


One can live in hope. Until then, I wait for my next SMTM fix.


Footnote

The work by SMTM is worth reading (and following) in full. It is a great example of just some “random people on the Internet” using open data to think through and attempt to answer difficult questions.

Reading SMTM reminded me of the early, pre-social media engagement-driven, Internet. I remember stumbling upon blogs such Naked Capitalism (Still going strong), The Epicurean Dealmaker (RIP), and Slate Star Codex (also RIP) and enjoying reading about topics that were outside my areas of work or of study.

The death of Google Reader and the rise of Social Media has made the Internet a much less surprising place.

Computer Says No

Photo by Andre Hunter on Unsplash

Everyone has dealt with a “Computer Says No” situation. You call up a customer services agent hoping for a quick resolution to a perfectly reasonable query. But “computer says no”. You go through a convoluted questionnaire, answer the questions as best you can, but “computer says no”. The customer service agent shrugs saying that they can’t do anything because the system won’t let them.

It is tempting to call the customer service agent a jobsworth, or someone who doesn’t care about their job. To hang up in frustration and curse the status of the customer service industry.

So why is modern customer service so bad? Why do we dread calling up a help line or deal with an online customer support agent (who may or may not be a bot)?

Atul Gawande’s recent New Yorker article on why medical professionals hate their computers may have an answer. Dr. Gawande is a surgeon. In the article, he talks about how the medical informations systems used in his hospital make it difficult to really look after his patients.

Hospital systems in the US (much like the NHS in the UK) have spent billions of dollars to make medical care more efficient. But when we go visit our local general practitioner, we find them struggling with their PC more than talking to us. Instead of empathy, we get distracted clicks and frowns while the doctor tries to figure out how to massage the conversation into a bunch of drop downs and radio buttons. It is a terrible experience for everyone involved.

I am an engineer, I like efficiency. I like measuring the performance of the code I write and love reading articles about how to optimise software. In this pursuit of perfection, I fear that we have optimised ourself into a corner. Our systems are optimised, everything is measured — except the misery that they inflict on those who actually have to use the system every day. Human conversations and problems cannot be modelled so easily into a workflow. Improved throughput and the need to be more efficient drive design decisions more than the need to solve a problem. So we end up systems that their users hate. These systems and workflows lead to dis-engaged employees and ultimately to terrible customer service.

The next time that someone talks about having poor customer service, don’t blame the agent. Blame the analyst who designed the convoluted workflow in the software they use and the engineer who implemented it.

Review: The Rise of the Robots by Martin Ford

Rise of the Robots: Technology and the Threat of a Jobless FutureRise of the Robots: Technology and the Threat of a Jobless Future by Martin Ford
My rating: 3 of 5 stars

Rise of the Robots (RoR) was voted as the Financial Time’s Business Book of the Year* for 2015.

I found the book to be a disappointment. RoR goes over well trodden territory around automation, the shift of from a labour driven economy to a capital driven economy and the impending collapse of the consumption due to the shrinking middle class. Mr. Ford also provides a brief tour of the issues around the emergence of general purpose Artificial Intelligence** and nano technology. The book concludes with an argument for a universal, work appropriate basic income scheme and a discussion around the system of incentives that would make such a scheme work.

The book provides anecdotal commentary around the decimation of white collar jobs and the emergence of machine learning. It covers well trod territory on the failures of MOOCs and how a degree from a University may no longer guarantee a prosperous middle class life.

RoR comes across as a lament for the golden post-war age of increasing prosperity, high levels of employment and with the middle classes having a secure financial future. Mr. Ford mentions on a number of occasions that we are reverting to a feudal system with a small percentage of the population controlling access to capital and the majority of us becoming sharecroppers in a digital economy. I agree with this bleak prognosis but do not find Mr. Ford’s solution of a increasing consumption via a universal basic income satisfactory.

I found RoR to be a sharp, succinct read with extensive foot notes and references. There are few mentions in the book of the sort of challenges facing countries like India that are not wealthy and where a basic income would be difficult to implement. India, like China before it, has staked it’s economic future on creating millions of jobs through manufacturing and services. If these jobs are not to materialise due to the “Rise of the Robots”, what options remain open? Regrettably, Mr. Ford does not offer much in the way of insight here.

I would recommend RoR as a primer on the type of issues that developed nations will face in the coming decades but find Mr. Ford’s arguments for a solution unconvincing and his exploration on the deeper issues around ethics around general purpose AI unsatisfactory.

Notes:
* FT Business Book of the Year: http://www.ft.com/cms/s/0/45ea0f60-8d…

** Nick Bostrom’s Superintelligence provides a detailed exploration around the issues behind the emergence of General Purpose AI: https://www.goodreads.com/book/show/2…

View all my reviews

Propaganda in the age of Wikileaks

Gloria Origgi, in Edge 335 states that we are leaving the information age behind and are entering a reputation age. She posits that one of the reasons for the influence Wikileaks wields in current political and social discourse is due to powerful, and reputed media organisations like the New York Times and The Guardian acting as conduits for it’s revelations.  We trust the contents of the Wikileaks secrets because of our implicit trust of these formidable media organisations.  We believe the revelations because we believe in the integrity of the Guardian or the Times.

When a reputed newspaper breaks a story, we assume that the sources have been vetted, and that the editors have double checked the allegations / revelations before publishing them.  Wikileaks, however, presents an interesting dilemma.  The contents of the leaks were uploaded by someone (presumably PFC Bradley Manning) within the US military establishment.   The behaviour of the US government (and other governments) subsequently offer some reassurance that these diplomatic cables did come from within their organisations.  Not surprisingly, “Cablegate” has become perhaps the media event of the year (or even the decade).  Hordes of commentators have descended on the Guardian website venting their spleen about the evils of the US government, and the hypocrisy of US foreign policy.

I can’t help but be a little cynical about this hoopla.  Yes, clearly some of the contents of leaks may jeopardise national (or indeed international) security.  However, I wonder how easy it would be for a government, or any other organisation to manipulate public opinion via a channel like Wikileaks.  Could Wikileaks itself be used as tool for government (or indeed corporate propaganda)?  Would it be easier for the US government to sell overt support of a South Korean invasion of North Korea given the cables published on the topic?  Would it be easier for the state department to withdraw a diplomat / intelligence agent from a tricky situation abroad now that he has been “outed” and him disappearing would look very bad for the host nation?

Yes, this is tinfoil hat territory.  I just want to convey that we should think twice before taking the contents of the Cablegate memos at face value.  Even if the leak was unintended (as it appears), it could be quite easy for a motivated organisation (government etc.) to move quickly and use it as another avenue for propaganda.

Echo Chamber

Does anybody even remember the term “Information Superhighway” any more?  Do you remember a pre-global warming, pre-divorce, skinny Al Gore and his dubious claims on inventing the Internet?  We were told about having the world’s knowledge at our finger tips. The Internet would free information and provide the most egalitarian way to get to knowledge previously limited to inhabitants of ivory towers.  But what happened?  The story of the last ten years unfolds almost like a moralistic tale. Like Midas and his golden touch or like the Genie from Arabian nights and their granting of life wishes that destroy lives.

We don’t learn any more.  We bookmark.  We don’t read any more, we skim.  We don’t discuss any more, we forward links to points, and another set of links to counter points, followed by links for the conclusion.  When we do decide to comment, it is a comment made in character, stereotypical.

We all live in an echo chamber of our stereotype.  Our voices bounce off the walls, and are magnified by those of our peers, also of our stereotype.  These voices then pour out of the mouth of the chamber and as an atonal roar that clashes with those coming out of other chambers.  We are here, shouting at one another, but not bothering to understand why or what we are shouting for.  We like shouting because it is what we do, our slogans are what define us.