In my last article, I talked about the market-distorting force of financialization, transforming businesses from tools to benefit society into fungible assets to be traded, leveraged, flipped, and liquidated. Financialization has encouraged some of the worst of today’s finance industry behavior. Crypto and blockchain technology, attempting to build around the problems of traditional finance, has sadly (and a bit ironically) been driven enthusiastically down the same ugly road by its own self-financialization by design.

Paul Graham just published an essay called The Brand Age that describes another market-distorting force. This one acts on the products we buy, and the companies that make them, transforming products that solve problems into fungible brands that can extract more from buyers with less.

This brand-driven process often goes hand-in-hand with financialization, creating a self-reinforcing loop that captures and financializes companies and markets. Later I’ll come back to how that combination of forces hit crypto even harder, actively preventing it from realizing its potential for good. But first I want to talk about Paul Graham’s insight about brands and how it can throw fuel onto the fire of financialization.

Brandification Through Price

Graham’s main point is this: When the features and performance of a given product type commoditizes – that is, when anyone can buy something perfectly good enough cheaply and easily – the way back to profitability is no longer selling features and performance but selling brand. Companies must convince their buyer to spend more on the product not because the product itself is better, but because the product effectively delivers a recognizable and unique brand that the buyer prefers and values. Once companies in a fully commoditized market have started remaking themselves and their products in this way, every product in the market must find and sell its valued brand position or die.

For the sake of grammatical simplicity, I’m going to call this process brandification.

Graham’s example is wristwatches, a market that began to brandify when Seiko introduced wristwatches with quartz movements in 1969. Seiko’s watches without delicate, hand-made gears and springs rapidly made accuracy and thinness cheap and mass-manufacturable rather than the exclusive domain of precision Swiss mechanical watchmaking. The only way for Swiss watchmakers to survive the cheap quartz watch was to create the brandified luxury watch category. Now, decades later, more expensive watches now largely justify their price through what their luxury brand gives you rather than what the product itself gives you.

There are many ways that products successfully brandify and charge a premium beyond what’s justified by strict functionality. The goal is to create a brand that gives the buyer something outside the functional features of the product. To do that, a successful brand must convey values that are compelling to the buyer, whether design (tasteful, classic, streetstyle...), lifestyle vibe fit (active, quiet luxury, tech-forward...), or ironically even notable lack of traditional brand marks. By choosing a particular brand, you may even earn membership to a community of like-minded owners.

I want to focus, however, on the brand value many Swiss watch companies embraced with success: being recognizably expensive to display wealth. They learned they could charge vastly more than Seiko’s cheap and accurate quartz watches by selling the price itself. This meant telling a brand story that their watches were very difficult and expensive to make, and thus were distinctly expensive to buy. Their advertising began to explicitly link their brand to high price, making their products effective ways of displaying wealth, performance comparisons to quartz watches be damned.

Making price itself the primary selling point created a strange new dynamic for these companies. Not only did the product’s marketing need to focus explicitly on high price, it became crucial to ensure that the price of watches remained high, even in the secondary market, lest the brand story of “expensive because it’s worth it” fall apart. As Graham describes, Patek Philippe began strictly limiting production of its top-end watches, setting rules for retail that made them difficult to buy, and putting restrictions on their resale. They even began buying their own watches from the secondary market to ensure that the most expensive Patek models remained expensive.

This doesn’t just happen with luxury watches. Ferrari does very similar things, only offering their top-end cars to long-time Ferrari owners and imposing contractual terms on how those cars may be used and resold, including a requirement to offer Ferrari the chance to repurchase it itself. Violating Ferrari’s terms means Ferrari will no longer sell you a car. Even now when an affordable EV may be as fast as a Ferrari, Ferrari remains successful in large part because it is selling the exclusive Ferrari brand. Certainly some of that brand’s value has to do with design, lifestyle, and racing history. But a big part of it is also the fact that expensive Ferraris stay expensive.

That’s an important shift to dig into further.

When Brandified Products Financialize

Brandification based on price may be just one of many ways to stay competitive, but it’s a particularly insidious one because it changes the nature of the product and the company that sells it.

Brand buyers expect the brand’s values to be maintained. So when the price is the product to most of a product’s buyers, they expect that price to be maintained. As we’ve seen with Patek and Ferrari, that means not just setting the sale price high, but engaging in careful market engineering – controlling supply as well as “structuring” the behavior of the primary and secondary markets. The product very literally becomes a financial asset that the company issues and supports, and the company must diligently treat it that way to remain successful.

Patek Philippe and Ferrari didn’t just brandify their products, they also financialized them.

Like any well-engineered financial asset, why stop at just slowing the slide of its price? Patek and Ferrari are so successful at financializing their products that their price in the secondary market often increases. Purchasing those products not only gives the buyer an effective display of wealth and an automatic membership to an exclusive-by-design community of owners, it gives them a speculative investment. Quite a bargain. And as you’d expect for such an investment asset, high-end Pateks and Ferraris are frequently bought and stored for later resale with the confidence that the manufacturer’s financial engineering will keep that market predictably profitable.

Once a market has brandified and financialized, it’s particularly difficult for it to go back to being performance-value-driven.

Play out the attempted break-out scenario: You create a company trying to enter a brandified, financialized market with a product that breaks through commodification with legitimately greater functional value that nobody thought possible before. In a normal market, you’re in good shape to have a strong pitch to investors and an attractive value proposition to buyers. In the brandified and financialized market, however, you are at an immediate disadvantage.

For buyers, not only are you fighting against entrenched brand-centric mindshare (”Who are these guys? Why should I care? What sort of people own those products?”), they are comparing your premium product against more exclusive competitors that hold or increase their value over time through market engineering. That’s tough to beat.

You’ve also got a tough pitch to potential investors. Building a better product is expensive, time-consuming, risky, and requires careful product judgment. To succeed, your company must diligently find and validate a product opportunity with customer value and usability, technical feasibility, and business viability – and then go do the hiring and hard work of execution. (And if you think AI eliminates all that, you’re the victim of the hype flowing out of today’s highly brandified generative AI market. But that’s a story for another day.)

Your investors are comparing all that expense, risk, and time-to-ROI to brandified, financialized companies. Those companies only need products that are roughly as good as the others – no R&D risk or expense to speak of. All the competitive juice is created with the tools that financial people understand: brand marketing and financial engineering. Those tools are quick, measurable, generate near-term profit, and the cost outlay doesn’t come with any long-term commitments to large engineering staff so the taps can be quickly turned on or off to tune the finances. And once the brand juice runs out, they cut costs, flip the company, and move on.

In the brandified, financialized market, maybe you can break through as a startup insurgent and compete with your better product, but it’s a very hard road. Good luck.

Financial Assets Become Brandified

We’ve seen how brandified products sometimes naturally financialize to compete, and tend to stay brandified and financialized. We can also see the causality go the other direction: Financial asset classes often naturally become brandified “products” to compete against other assets for investment.

For example, what is gold in the modern world but a very strong brand? The price of gold vastly outstrips what is justified by scarcity or function (compare it to platinum or silver) because gold has become the #1 brand in precious metals. It’s the Coca-Cola of wealth preservation assets and it maintains its price because the price is the product.

That brandification of financial assets multiplies the ugly market dynamics of financialization, suppressing sustained innovation and creating speculative bubbles. That’s because when the price is driven primarily by brand value, and the brand value is the increasing price, trading of the asset is inherently reflexive.

The dot-com boom was fueled by easy IPO cash available to companies who made “putting X on the internet” their brand. The functionality offered by internet-based products for users (or lack thereof in the late 90s) didn’t matter to investors when the brand value of internet companies was simply the anticipated massive price increases of their stocks in an overhyped market.

In the lead-up to the 2008 financial crisis, real estate was bundled into abstracted, financialized “AAA-rated” assets that obscured the functional risks of rampant subprime lending. Finance industry buyers of those assets weren’t digging into the underlying soundness of those assets (or lack thereof) because the AAA-rated asset brand, and its attractive returns, was the product. Everybody was getting in on this hot investment asset brand and nobody in the financial world wanted to miss out.

Or there’s Bernie Madoff, his investment fund offering a money-making-miracle brand that everybody wanted in on. Nobody cared about the source of the extraordinary returns (or lack thereof).

But brand-driven value is fragile and reflexive assets tend to violently correct. Eventually it became impossible to ignore that internet companies weren’t making money, that AAA-rated real estate bundles were full of defaulting loans, and that Madoff was running a ponzi that couldn’t pay off. The brand value of the assets was destroyed as soon as the illusion could no longer be maintained, and so the assets themselves collapsed. It was as if we discovered that Patek Phillippe was secretly selling 100 times more watches than they claimed. The price would collapse, because the brand’s value is the successful maintenance of the market engineering supporting the price.

I’ll leave it to others to push for the right regulation to avoid dangerous brandification of investment assets. But in the next article, I’ll get into the link between the brandified/financialized dynamic and crypto, and what it means for crypto’s inability to reach its potential for good.

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Recently, Oren Cass wrote a comprehensive and incisive take-down of financialization as a destructive force in the economy. Read it, please. For context, Cass isn’t some wild-eyed anti-capitalist activist, he’s the chief economist at a conservative economic think tank and former consultant at Bain Capital.

His article brilliantly breaks down maybe the primary underlying force that created the dot-com bubble, the 2008 financial crisis, the loss of competitiveness of US industry, the yawning economic gap, the growing AI bubble, memestocks, and much more of the dysfunction of the economy we see today. It’s the kind of informed, specific call for change that the Occupy Wall Street movement sadly could never articulate.

I want to talk about crypto for a moment though. The desire to escape the pervasive economic dysfunction of our financial system is what originally inspired the creation of Bitcoin, and many of us started working and building in crypto (and DeFi and Web3) because we recognized the potential for the technology to create better solutions to real financial problems.

Despite its potential, I think we have to admit that crypto has failed miserably to achieve that goal. In fact it’s created a new parallel set of assets and markets that largely embody the worst of what Cass points out in TradFi – just faster and more decentralized, even if less impactful to the economy at large. It sometimes feels like crypto was even the proving ground for absurdities that have now moved into traditional finance, like memestocks and complex circular leveraged lending schemes to sustain the appearance of success.

Financialization looks a lot like the primary reason for that failure. The economic and technological mechanisms of crypto make it essentially self-financializing, and we’re unlikely to break out of the cycle without some aggressive changes to how crypto works.

Financialization Removes the Invisible Hand

Financialization, as Cass explains it, is when...

... financial markets and transactions [become] ends unto themselves, disconnected from — and often at the expense of — the societal benefits that support human flourishing and are capitalism’s proper purpose.

It happens when the real drivers of the economy – consumers, investors, businesses, physical assets, etc. – are abstracted away behind stocks, derivatives, packaged financial instruments, and complex financial schemes. Absent any regulation on the creation and use of those abstractions, the best ways to make money quickly cease to be guided by the invisible hand that historically has made capitalism such a powerful force to improve the world. The finance industry ceases to profit alongside the economy by benefitting it, and begins profiting at the economy’s expense.

That kind of financialized activity, Cass argues, now dominates finance.

Less than 10 percent of Goldman’s work in 2024, measured by revenue, was helping businesses raise capital. Loans of Goldman’s own funds to operating businesses accounted for less than 2 percent of its assets. At JPMorgan Chase the figures were 4 and 5 percent; at Morgan Stanley, 7 and 2 percent. Even the efforts at helping to raise capital are misleading, because less than a tenth of it goes toward building anything new. The rest funds debt refinancing, balance sheet restructuring and mergers and acquisitions.

In a heavily financialized economy, there are endless opportunities for short-term profit through abstractions, drowning out more difficult and long-term traditional opportunities in the good and beneficial allocation of capital. Consumers, investors, businesses, and physical assets are no longer seen by finance as engines for economic growth to profitably support, but resources that can be packaged up as interchangeable financial assets that can be for mined for quick short-term profit by extracting their value, trading them, and moving on.

The rational actor has no incentive to allocate capital anywhere but quick wins. CEOs are pressured by shareholders to deliver immediate stock growth through buybacks, cost-cutting, and (increasingly) riding the latest meme wave, killing investments that create long-term competitiveness and productivity. High-frequency traders exploit markets to skim off profit, increasing volatility rather than providing useful liquidity. Layered derivatives and circular financial schemes let insiders take risky bets while shifting the risk to the broader economy. Startups are required by VCs to shoot for mass-scale rapid-growth unicorns, leaving little room for companies taking the time to build innovative solutions to difficult problems.

The Self-Financialization of Crypto

Traditional finance was initially created to solve real economic problems, but financialization has crept in where lack of regulation and new technological capabilities have created the shortcuts. Crypto and DeFi, however, were (perhaps naively) created with the belief that if the technology allows any sort of financial mechanism to be built by anyone, people will do the right thing more often than not and the people solving real problems will win.

Many of us who got into crypto and DeFi went in with the belief that we could fix the problems of traditional finance by disempowering the people who have caused the problems. Decentralization! Disintermediation! Unbundling! By creating the mechanisms of finance more efficiently and on open platforms, middle-men would be circumvented, rent-seeking silos would be eliminated, and transparency rather than secrecy would be the norm.

Cass, however, points out that it isn’t really the people that are the problem with big finance, but the fact that the highly abstracted mechanisms of financialization have been allowed to flourish. With those mechanisms offering the possibility of a shortcut to profit, the profit urge is gravitationally drawn towards the shortcuts and away from beneficial investments and services.

The same thing has played out in crypto. After more than a decade with open blockchain technology, we have discovered that the easiest and most immediately profitable thing to do with blockchain and smart contracts is to re-create precisely the mechanisms of financialization that caused the problems in the first place. Except now they’re more efficient than ever before and available to everyone.

Bitcoin was imagined as a democratized form of digital cash, but instead has become a tool of speculation – another gold-like asset for traders, with value abstracted away from any utility. When Ethereum introduced smart contracts, the first application was to create tokens that could act as abstractions to financialize literally anything (or, in many cases, nothing but a meme). As new blockchains with new capabilities have been invented, the first and dominant applications on those platforms have continued to be those that enable faster speculation and greater leverage. Volatility in markets is held up as a goal, to increase the potential for speculation that creates the primary motive for capital to seek those assets. Real utility and solving real financial problems can’t compete; it’s too slow, too boring, not a 100x.

Beyond just applications, bew blockchain platforms themselves have also self-financialized. Their open consensus designs have always included a platform token, with the token’s value providing an economic cost to attack the network – and also often providing a source of funding for the original developers. The existence of a platform token whose value is expected to rise instantly financializes the platform itself, locking it into a set of feedback loops that turbocharge the negatives we see in traditional finance. VCs and token holders demand that platform creators focus on nothing but quick and massive token price increases. The only thing that matters is buybacks and lockups, empty meme marketing, hype-driven development, and market-making that verges on market manipulation – and that pressure comes with a righteous anger at any sort of operating costs. If your platform isn’t doing those things to pump your token this week, some other platform is, and that’s where the capital will flow.

Surprised that crypto mostly remains a bunch of insider speculation, fraud, and scams and legitimate, long-term-focused projects get nowhere? Sadly I’m not anymore, much as it could have gone a better way.

A Solution for Crypto

Frankly I’m not optimistic about turning crypto around. The financialized mindset has become so entrenched that, like in traditional finance, it seems to be now taken as a positive. Anything that makes money must be good, right? And because crypto is such an effective place to play financialized games without restraint, it has become dominated by users and developers who don’t want it any other way and actively resist change.

Taking suggestions from Cass’s article, perhaps the way forward is something crypto has generally considered anathema: regulation. Absolutely unrestrained activity on a finance platform leads to rampant financialization, and so we may need new crypto platforms that apply some different incentives and technological limits on what is possible. Creators need to be willing to sit down and think about what real problems they want their platform to solve in the world and design the mechanisms so that the natural profit-seeking motive more often than not aligns with those goals, rather than expecting that it will all sort itself out as long as people are making money.

Profitable finance is a tool that society can wield to build, if we can remember that building, not profit, is the goal.

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In 1946, George Orwell wrote an essay called Politics and the English Language which often gets mentioned for its six “rules” of good writing. Back when I was first trying my hand at writing, those rules rewired my thinking about how to write well. Over the years, however, I’d mostly forgotten the specifics of the essay, including what it had to do with politics. Re-reading it now, the specifics (and even the six rules) are less relevant than I imagined, but the more fundamental insights about what separates good writing from bad apply shockingly well to the written (and spoken) word in the age of social media – including pointed warnings that could have been written today about AI.

It got me thinking more deeply about the purpose of writing in our society, and the power we have as both writer and reader. Good writing isn’t about following rules of correctness, but working out how to create thoughts, images, emotions and ideas in other minds. When we don’t respect the importance of that process, it can be dangerous for both writer and reader. Despite huge shifts in writing style since 1946, the dangers have remained, including the potential to distort political thought and opinion that so concerned Orwell.

Today’s chatbot AI systems now pose a new danger, because the technology itself is effectively designed to produce the most dangerous kind of bad writing that Orwell feared.

The Rules Change But the Game is the Same

The stated purpose of Orwell’s essay was to critique and correct what he saw as a degradation of the English language. He believed that this degradation of language was the cause of a dangerous degradation of clear political thought on issues of global importance. His target was the academic elite of political discourse that he saw concealing weak ideas behind an overwrought, impressive-seeming writing style that was in vogue at the time.

The particulars of this argument about the degradation of English have not aged well. The writing style he criticizes has long since gone out of fashion (nobody is scoring points these days by using unnecessary Latin) and it was always an elitist stretch to call this academic style of writing the English Language. Even the idea that a language itself might be in need of repair, and that this could be accomplished through the “conscious action” of learned men, ignores how the evolution of language nearly always happens in reality. See linguist John McWhorter’s many excellent arguments about how language is always evolving organically in order to meet the needs of culture.

Orwell’s main point, however, is a more timeless one. He believes that writing well is worth pursuing as a writer, and that recognizing bad writing is worthwhile as a reader, not just as a matter of aesthetics but as a necessary service to yourself and to society. His insights into what makes for good writing and the dangers of bad writing apply straight through to today’s era of social media and AI.

What exactly separates “good” from “bad”? When we say “bad writing”, we tend to think about the sorts of mistakes that get you red marks on a term paper, but that isn’t what’s important to Orwell:

It has nothing to do with correct grammar and syntax, which are of no importance so long as one makes one’s meaning clear ...

Making your meaning clear, that’s the critical point. It seems obvious, but writing does something incredible when done well. It takes thoughts from the mind of a writer and puts them into the minds of many readers. Good writing does that clearly and concisely, grabbing the attention of the reader and rewarding it with a blossoming of sharply-defined new thoughts in their mind.

Good writing isn’t created automatically by the formal grammar and syntax of language, but by how the writer uses it. It is a matter of writing style. Regardless of what you write, for what purpose, or who your audience is, the fundamental principle of good writing style is universal: Use the diverse tools of language, as you find them, to hold the attention of your readers and effectively put your thoughts into their minds.

Language itself constantly evolves, as does the cultural context of your audience, and so the best way to use language to hold their attention and put your ideas into their minds must also evolve. How you write should depend on what you’re writing and who your audience is. That means that the specifics of good writing are never fixed or universal, and they certainly aren’t about only using “proper” language (although it has its place); sometimes clocking her tea is just the clearest, most concise way of making your point.

It’s tempting to seek out rules we can follow when writing, but specific rules of writing style will have a particular purpose, medium, and audience in mind (think newspaper style guides) and so they may not necessarily apply to what you’re writing – and they will always have an expiration date.

So while Orwell’s six rules were an insightful snapshot of using language well in the academic world of 1946, some are starting to feel a bit creaky 80 years on and a world apart. Some of the more general pieces of advice, however, are timeless. One of the best is to avoid metaphors and figures of speech that are so over-used that they’ve lost their impact and don’t evoke our essential point in the minds of readers. Better to put in the effort as a writer to invent something fresh and vibrant.

As another example, Strunk & White’s famous The Elements of Style, originally from 1920, is also a classic for writers. Even its section titles continually echo in the mind, like “Use definite, specific, concrete language” and “Omit needless words”. But 100 years later, some of the specific advice doesn’t quite hit like it used to unless you’re working for a particularly stodgy newspaper.

We can pick up tips and tricks, but there’s no shortcut. To write well, we have to put in our own thought and care for the topic and our audience.

The Miracle and the Mission of Good Writing

It’s a miracle of human biology that our minds can perform a kind of collaborative data compression when we write and speak. We choose sequences of words to capture our meaning with the expectation that other minds will be able to unpack and expand what we’ve written or spoken into pure thought. The compression is collaborative because it only works when the minds of readers contain concepts, images, and emotions that the writer can evoke through the right choice of word. When that’s true, the writer can play games in a reader’s mind, building up new thoughts from more elemental ones like building blocks.

In a way, writing is similar to composing a musical score, with the minds of readers supplying the orchestra. The composer knows that orchestras generally have strings and horns and percussion that are similar, and they can compress the music in their minds into a simple marks on a page for each type of instrument. Players can then expand those marks back into the combined music of a symphony. (Of course the players provide personal touches, and creative writers often consider their writing a collaborative work with the reader’s imagination.)

Good writing takes maximum advantage of these miraculous capabilities of the mind, and an understanding of the audience, to flow your ideas smoothly through the compression/expansion process. You can think of it as a problem to solve: what words will you choose to beam the idea in your head into your reader’s heads like a pink laser of pure information? Are you compressing your thoughts in a way that other people’s minds, each unique in the experiences that have shaped how they interpret language, can re-expand them easily? Can you invoke concepts already in their minds to paint a picture more quickly? Can you proof read from their point of view, and do the words effortlessly pour out meaning and imagery as you go, or do you have to stop and squeeze them to extract anything satisfying?

Orwell describes one way to go about it:

When you think of a concrete object, you think wordlessly, and then, if you want to describe the thing you have been visualising, you probably hunt about till you find the exact words that seem to fit it. When you think of something abstract you are more inclined to use words from the start, and unless you make a conscious effort to prevent it, the existing dialect will come rushing in and do the job for you, at the expense of blurring or even changing your meaning. Probably it is better to put off using words as long as possible and get one’s meanings as clear as one can through pictures and sensations. Afterward one can choose – not simply accept – the phrases that will best cover the meaning, and then switch round and decide what impression one’s words are likely to make on another person. This last effort of the mind cuts out all stale or mixed images, all prefabricated phrases, needless repetitions, and humbug and vagueness generally.

When the words are well-chosen, a description of a scene leaves a vibrant image in the reader’s mind like a memory of a real place. An explanation of a scientific theory gives the reader a clarity of understanding as if they had come to the conclusions from their own observations. A story can evoke emotions and insights as if the reader had been through the events of its characters. The reality of a well-written book or article is only slightly less incredible than a neural interface in the back of your neck that can teach you kung fu.

No matter what we write, it’s our responsibility to try to solve that problem as well as we can. Rules and guidelines from Orwell or Strunk & White are useful references for solving that problem, but ultimately we have to know our audience and choose our words based on what works. What you had in mind or what you meant doesn’t matter if it comes out garbled and confused on the other side.

The process of solving that problem well also has an additional important benefit. For you to work out what words will re-expand in other minds as crisp vibrant ideas, you first need to have those ideas crisp and vibrant in your own mind. Good writing helps create clear thought for the writer. It’s the source of the old saying that you don’t really understand a topic well until you teach it. If your ideas are vague, what you write can at best convey vagueness.

The Danger of Bad Writing

To understand how writing can go wrong, I want to separate two essential parts of good writing: being clear and being compelling.

Clear writing uses words that accurately convey thoughts to a reader.

Compelling writing uses words that captivate the reader and hold their interest.

Good writing is both clear and compelling. When one of them is lost, we get into trouble.

Writing that is clear but not compelling may be so dry, verbose, or difficult to follow that nobody will hang in there to extract the ideas. Think of a textbook written without passion for the subject, with long (but perfectly factual) paragraphs that you have to read ten times for anything to sink in. Or maybe it’s something written in language or lingo that is just too unfamiliar to the reader. The juice is there, but the reader has to really squeeze to get it, so they may miss your meaning or not bother trying.

Writing that is compelling but not clear may be captivating at first, but falls apart if the reader stops to think about it. It may be comfortingly accessible, welcoming, and speak to people just like them – but it goes no deeper. Think about marketing slogans, trash self-help books and seminars, or common sense that turns out to be false. It might get the clicks, signups, and impulse purchases, but there’s no substance.

In both types of bad writing, good clear ideas fail to be transmitted from one mind to another.

Also in both cases, the writing may not seem obviously bad. It may be perfectly grammatical and even skillfully written. As a result, if you don’t detect the signs of bad writing, you may be inclined to take it at face value, even if you’re a little hazy on the details. For example, the clear-but-uncompelling writing may come off as dry but seemingly written by smart people so maybe you just skip to the end and accept the conclusions. Compelling-but-unclear writing may seem clever, exciting, relevant, and insightful; you may stay engaged and come to be impressed by the writer and their point of view and fail to notice that they’re talking nonsense.

That means that bad writing isn’t just ineffective, it’s potentially dangerous.

It’s dangerous for the reader because it can use language that seems smart, familiar, or impassioned, but actually conceals lazy thinking, obscuring of inconvenient facts, a lack of cohesive ideas, or outright lies. Bad writing can still give the outward appearance of containing meaning and thought – it can even be beautiful – while being ultimately hollow. We can be easily misled and manipulated when we don’t recognize bad writing that uses words designed to be compelling without actually being clear.

It’s also dangerous for the writer because you might not realize that your own ideas are weak or nebulous if you have the skill to spin out compelling language that feels good, grabs the attention of your audience, and generates immediate positive feedback. Maybe you’re really in tune with your audience or know just what kind of writing style has really worked for other writers. It feels like you’re writing good stuff, but ultimately it falls flat in other minds. It becomes clickbait rather than a miraculous tool to share thought between minds.

Bad Political Writing Then and Now

Those dangers are the crux of Orwell’s argument in Politics and the English Language about the degradation of language in political writing. While the specifics have dated, his description of the fundamental danger of bad writing is useful to understand even today.

One of his great fears was “orthodoxy” – of not having ideas of one’s own but rather only trying to fit in with the group. In Orwell’s time, the orthodoxy he was concerned about was fashionable but intellectually lazy support of communism in academia. Books and papers used language that mashed together all of the outward indicators of research, historical basis, and deep thought, but really said little more than “I’m in the smart-guy club too!” The dense academic language was compelling to a receptive academic in-group, but was very far from clear and concealed the lack of any strong rational argument.

Today political orthodoxy looks much different. It’s the party line, the echo chamber, the meme. Influential orthodox writers are now much more likely to be social media influencers, echoing variations on a narrative that speaks to a particular in-group that will like and share based on how instantly compelling it is, even when it’s not just unclear but often absurd or false. We’ve obliterated the elite of yesteryear, and replaced it with thousands of influencers saying ”This must be right because look at my follower count and how many other people are saying it!”

The danger is this: Then as now, orthodoxy means people believe things not because of clear and convincing supporting ideas, but because other people believe them. Orthodox writing skips past thoughtful argument and jumps straight to conclusion. A conclusion without the clear thought to support it is like a shell, and bad writing can be just that: a thin and sometimes beautiful shell surrounding emptiness. Writers whose primary concern is orthodoxy choose words not to convey the strength of an idea, but to echo the language used by the group. Orthodox writing doesn’t try to gather readers in support for good ideas, it polarizes readers into in- and out-groups who agree or disagree with foregone conclusions. And historically when political conclusions are foregone rather than based in reality, the really dangerous stuff starts to happen.

As readers, we can detect the kind of writing style that tends to be used when orthodoxy rather than thoughtfulness is the motivation. Orwell describes the warning signs:

As soon as certain topics are raised, the concrete melts into the abstract and no one seems able to think of turns of speech that are not hackneyed: prose consists less and less of words chosen for the sake of their meaning, and more and more of phrases tacked together like the sections of a prefabricated hen-house.

He goes on to describe how this applies not just to orthodoxy-driven writing, but also speech.

Orthodoxy, of whatever colour, seems to demand a lifeless, imitative style. [...] A speaker who uses that kind of phraseology has gone some distance toward turning himself into a machine. The appropriate noises are coming out of his larynx, but his brain is not involved as it would be if he were choosing his words for himself. [...] And this reduced state of consciousness, if not indispensable, is at any rate favourable to political conformity.

Sound like a political influencer? Or for that matter, a TikTok trend chaser or a corporate middle manager talking about circling back to the go-forward actions?

My favorite advice from Orwell about how to detect dangerously bad writing is this:

[Bad writing] at its worst does not consist in picking out words for the sake of their meaning and inventing images in order to make the meaning clearer. It consists in gumming together long strips of words which have already been set in order by someone else, and making the results presentable by sheer humbug. The attraction of this way of writing is that it is easy.

And that brings us neatly on to the topic of writing with AI.

AI Always Writes Correctly but Never Writes Well

The Orwell quote just above made me do a double-take when I re-read the essay recently, because this...

... gumming together long strips of words which have already been set in order by someone else, and making the results presentable by sheer humbug.

... is a remarkably concise and accurate description of today’s chatbot AI systems. That is literally how the technology works. And clearly the reason people are using it is because, as Orwell says, it is easy.

There is a longer story for another day about how today’s popular AI chatbots, LLMs or “large language models”, are built (if you want to jump straight in, this video from Andrej Karpathy is excellent). But for the purposes of the topic at hand, here is the short form.

The company creating the LLM collects as much written text as possible (the entire internet, all books, etc.) and feeds it into a special “training” algorithm. Across the written output from millions of humans, the algorithm pays attention only to the orderings that words have been put into, and specifically how common various word orderings are. We should expect certain patterns to emerge. For example, grammar itself tends to make specific word orderings much more common because humans tend to choose and order their words grammatically. Standard turns of phrase will make certain orderings of words appear frequently. Different vocabulary and patterns of words will tend to be used in the context of different topics. Common questions will tend to be followed by common answers.

The truly clever thing about LLMs is how they efficiently capture and store those common relationships between words, including extremely long sequences of words. The stored distillation of those word relationships is the “model” of the LLM. Once you have the trained model, it can be used to generate new text. If you give the LLM some input text as a starting point (typically a combination of your “prompt” and a large amount of additional hidden text the AI company feeds in), it will then generate output text that would be likely to follow based on all of its cleverly distilled word-sequence data.

Unsurprisingly, that output text is perfectly grammatical, uses common turns of phrase correctly, draws on things people have written in a topic-specific way, and can reproduce correct answers to common questions. In fact the training text is so unthinkably vast that the LLM’s likely word sequence data encodes even more subtle things. Correct logical conclusions, insightful commentary, and relevant emotional sensitivities are generated in output text simply because those things are more likely in the writings of humans than text that is irrational, absurd, or insensitive.

The result is that using a chatbot feels a whole lot like interacting with a thinking human that knows the rules of grammar, has learned common turns of phrase, knows about a staggering array of topics, and can answer questions with what seems to be logical thought and insight, all with a human touch. But what it’s really doing under the hood is literally gumming together long strips of words which have already been set in order by someone else, and making the results presentable by sheer humbug.

LLMs produce exactly the kind of bad writing that Orwell railed against, but written by a mindless word-ordering machine rather than an intellectually lazy human writer. Like orthodox writing, LLM output provides conclusions without thought. LLMs are fundamentally incapable of motivation, reason, understanding, or care, but they are marvelously capable of generating sequences of words that give the impression of those things.

In short, LLMs are machines explicitly designed to produce writing that is often compelling on the surface, but is only clear at conveying ideas by statistical accident. When an input prompt fits into patterns that match enough human-created writing, the thoughts in the minds of the original writers may barely survive the trip through the training process plus the LLM’s mindless gumming-together process, to be recovered in the mind of the reader. But because the LLM is only choosing likely combinations of words rather than choosing words to compress its own thought (which it does not have), the thoughts that happen to be patched together by those words are often muddled, vacuous, or simply factually incorrect. And no matter how much thought you put into your own prompt, the LLM has no mind to understand those words and the intention behind them; it only receives the prompt as relationships of words that influence the likelihood of the output words to follow.

This makes LLM AI not just a particularly bad tool for writing, but a particularly dangerous one.

As readers, we should reject writing produced by AI. It is at best a waste of your time, teasing and leading you on with compelling language that gives an extremely convincingly outward appearance of insight while only delivering it by accident. If it wasn’t worth a person’s time to write something themselves to get the point across clearly, it isn’t worth your time to read it.

Not only that, the dangers of AI-produced writing are substantial if we don’t actively reject it as a society. LLMs are excellent at producing a bottomless supply of compelling orthodox content that doesn’t need to convey meaning to achieve its purpose. It only needs to do what LLMs excel at: using the right words to generate endless tacked-together variations of existing messages, the kinds of messages that draw people into polarized in-groups and reassure them by overwhelming repetition into accepting foregone conclusions, no matter how irrational.

For writers, the best advice comes from Orwell:

What is above all needed is to let the meaning choose the word, and not the other way about. In prose, the worst thing one can do with words is to surrender to them.

By outsourcing your writing to AI, you lose the purpose of writing. You surrender to a sequence of words chosen not by your meaning but by mindless mathematical likelihood, virtually guaranteeing that your thoughts will not be conveyed to other minds effectively while lulling you into believing the opposite. And if you’re writing doesn’t need to convey any real thought, why does it need to be written in the first place? I would argue you’re only increasing society’s horrible poverty of attention.

By not putting in the work of choosing the best possible words to convey your thoughts, you are also robbed of the valuable process of forcing yourself to clarify those thoughts for yourself and others. AI’s command of language will ironically drag you away away from insightful, vibrant, meaningful prose, toward hollow imitation, lifeless word salad, and clickbait.

An LLM may write skillfully and quickly, but it will never write as well as you about your own thoughts, ideas, stories, beliefs, and feelings. While AI has some legitimately good uses, writing is not one of them, no matter how good that writing may seem on the surface. You owe it to yourself and your readers to choose your own words.

As a product engineer getting deep into blockchain tech back in 2017, it was a bit shocking how profoundly hostile crypto was to actually use. I was so accustomed to user experience being the top priority for any sort of new product, it was bizarre to dip into such an exciting technology where good user experience was seemingly not only ignored but maybe even actively resisted.

Eight years on, six of them leading product at Radix, it's tremendously disappointing how small the improvements have been for the general experience of using most crypto platforms and applications – and it's an absolute gut punch how very far crypto has fallen short of its potential to do good.

To make a small contribution to solving crypto's usability problem, I've co-written a paper with a friend and colleague of mine (and cryptography expert), Alex Cyon, describing an idea. It's a cryptographic concept for what we call "decentralized security questions", with example open source implementation. Its purpose is to help bring better user experience to the "your keys your crypto" ethos.

If you're involved in blockchain or wallet architecture, go ahead and click the link above and we sincerely hope you find something useful in the idea.

If, however, you haven't been deeply involved in crypto, I also wanted to talk a bit about the motivation behind the idea. That's what this article is about.

The point I want to make is this: Bad user experience isn't just an inconvenience for blockchain applications. It feeds a vicious cycle that keeps the crypto world locked onto quick money schemes rather than applications that could fulfill its potential for good.

Blockchain's Promise

From its origins, part of what made blockchain tech so exciting was that it could do something that no previous technology in history could: it made it possible for individuals to directly manage digital representations of true ownership without a trusted intermediary.

That's a mouthful, I realize, but it isn't as wonky as it sounds. Consider some things you're familiar with:

• Your bank balance is a digital representation of your ownership of dollars.

• Your RFID-enabled Passport contains a reference to a government's digital representation of your identity.

• Your healthcare account holds a digital representation of your medical data that you own.

• The items you own in your favorite online game are managed as natively digital objects.

In all of these cases, there is an "official" record of who owns what, with tightly-controlled rules for how ownership can be transferred. Those digital records and their rules are what define the ability to own things in a digitally represented form, but they must be trustable for anybody to consider them usefully "official" and for digital objects to have any real value.

In all of the examples above, the record and its rules are managed exclusively within the servers of a company (or a government). That means you log in to their closed system to access what you own, you trust them completely to protect what you own, and your rights to do things with what you own are defined by what that company allows you to do. If the company vanishes, they might take your digital assets with them.

Blockchain makes it possible to create systems where anyone can control digital assets without relying on any single company. You as a blockchain user can directly connect to the network to access what you own there, the network itself protects the assets you hold there, and you directly control what you do with your assets by issuing commands to the network. In short, there's nobody between you and your stuff by default.

Blockchain tech is designed to create good official records of ownership. The rules of how assets can move are reliable, clearly defined, known to all, and enforced automatically. Understanding how this works gets into a dark arts of things like consensus mechanisms and state machines. But in short, a group of participants operates "nodes" of a "blockchain network" by running an algorithm that is designed to mathematically ensure the rules of ownership are respected and that no one party can unilaterally change the rules.

Blockchain folks often call this new kind of digital ownership "self-sovereign", as opposed to the "custodial" ownership that we have today in the systems run by our banks, governments, healthcare systems, game platforms, and more.

But does self-sovereign digital ownership really matter?

The Blessing and Curse of Self-Sovereign Ownership

In many cases there is nothing wrong with the old way of managing ownership, but a lot of people are excited by the idea that it doesn't have to be this way for everything, and can provide some important benefits.

For example: It's useful to be able to use digital money with the level of control we have with cash. It's useful to be able to transfer ownership of things without paying a bunch of fees just because you have no choice. It's useful to avoid managing ownership across multiple complex and closed systems that can conceal the sorts of manipulation that caused the 2008 global financial crisis. And it's useful to be able to build markets and automation that can freely interact with a huge variety of digital objects in the same open, frictionless way that the internet allows people and applications to freely communicate with each other.

That's the good of self-sovereign ownership, but as with many useful technologies there is also a dark side. Free, uncontrolled representations of ownership can also enable quite a lot of bad stuff. We have laws, regulations, and restrictions on how money and other assets can flow because, well, money can enable crime just as effectively as it enables legitimate human commerce. There's a reason they say "follow the money".

We don't have to just shrug and accept the dark side though. It is my long-held belief that blockchain technology can and should enable better implementations of beneficial laws, regulations, and restrictions. This can be done while still allowing crypto to create real efficiencies in markets and businesses, and create useful new applications wrapped around digital ownership that weren't possible before. Part of what I did at Radix was push for its native asset system that, among other things, allowed issuers to easily implement good industry-standard controls on an asset-by-asset basis, with transparency and without compromising the asset's openness and user control.

Unfortunately, most crypto projects have chosen to ignore the hard work needed to take open blockchain networks from a good tech idea to something legitimately useful and mature. Instead they have focused on easy money. And when we're talking about digital assets with real value, there is sadly an overwhelming amount of easy money to be found in unconstrained ponzis, fads, get-rich-quick scams, bribery, market manipulation, and money laundering. Over the years, I've watched crypto's focus on those things collectively suck the energy, attention, and funding away from anything more useful in the long-term.

We'll come back to that in a moment.

Self-Sovereignty's Usability Nightmare

Bringing our attention back to the technology, there's a big tradeoff that unavoidably comes with self-sovereign ownership: If the individual has the power to control their own assets alone, they also bear the full responsibility for the control of their assets.

Think of it like this. If you leave your wallet at a coffee shop and come back later to discover the cash has been stolen, there's not a lot you can do; it was your cash to protect and you lost it. Similarly, if you alone possess the means to transfer your digital assets, you alone must protect those means at risk of permanently losing those assets or having them stolen.

Unfortunately the typical means of controlling digital assets on blockchains today is pretty horrible. To do anything on a blockchain, you need to prove to the blockchain network that you are indeed the true owner of the assets. The simplest way to do that, from a blockchain tech perspective, is using what's called a "private key". There's some cryptographic magic here, but you can think of a private key as a very long password. On today's blockchains, whoever has a user's single private key "password" has absolute and full control of their stuff. Lose your password, lose your access. Have your password stolen, the thief owns your stuff – just like somebody emptying the cash from your wallet.

Blockchain started with this simple solution for maintaining digital ownership, and oddly failed to progress much further. You probably won't be surprised to learn that, as a result, people lose their crypto all the time.

So crypto's bad user experience with private keys isn't just a matter of a little undesirable friction, as it would be in your typical app. It undercuts one of the primary reasons why we might want to use a blockchain in the first place. The very thing we want (self-sovereign control of our assets) is the thing that, as things stand today, is incredibly dangerous.

Bad Usability Feeds Bad Crypto

The private key problem is far from the only usability failure of crypto. Over and over, early technically simple approaches behind many aspects of crypto have become established, standardized, and frozen, with the user experience implications largely ignored.

Even though the fundamental design and security of a blockchain network may be good, the way digital assets and blockchain applications ("smart contracts") usually work in practice on today's most popular blockchains look, to an experienced developer of production financial systems, insane. They look like like tech demos that push enormous responsibility onto the user and developer, rather than into the design of the system. As a user today, you can only really be confident in safely using crypto if you're personally auditing every line of smart contract code of everything you interact with. Even experienced blockchain developers very frequently often overlook expensive errors, exploits, and backdoors that cost millions in losses.

So over a decade after its invention, using crypto is still confusing, complicated, and wildly risky. But why? Shouldn't there be a strong incentive to fix it? The incentives actually run in the opposite direction.

There's an ugly feedback loop between bad usability of blockchain and bad uses of blockchain that is keeping it bad.

The loop begins like this: When it's extremely difficult and risky for the average person to use blockchain, the only people who will do it anyway are the ones who stand to make a lot of quick money by taking the risk.

Then, because the only ones in crypto are the quick money people, good user experience takes a distant back seat to new quick money schemes that keep things as they are so they can keep making money. A common feature of the quick money schemes is that they're an insider's game; if you're a wise guy, you can win at the expense of the schmucks. For a crypto insider who has already come up the learning curve on things like managing your private keys and checking smart contracts, there's not only a certain amount of gatekeeping pride in keeping things the same, it gives you a competitive advantage over the schmucks coming in fresh trying to get their piece of the action.

If you're building the new blockchain applications, there's good money in delivering that quick money status quo. You're trying to launch apps on a scale of weeks to take advantage of the latest frenzied money-making fad, which means you want development to be what you're used to, you want the experience for your risk-taking users to be what they're used to, and you care not at all about the long-term usability or security of your system because you (and the smarter users) will have moved on to the next thing anyway.

If you're building a blockchain network, the gravitational attraction of the quick money is irresistible and perverse. When your goal is to build something that wins adoption, you are pressured on all sides to focus on whatever brings in the quick money people, not good long-term architecture that can grow and support legitimate sustainable usage. When you're trying to raise funding, the standard has been set that you better deliver the same incredibly fast and steep returns that the other quick money platforms have, which means turning your network token itself into a quick money scheme. "How do we build a useful platform for digital ownership?" rapidly becomes "how do we pump our token?"

Bad crypto feeds bad user experience, which helps keep crypto bad, and the cycle continues. The more money circulating through bad crypto (in the billions today), the greater the strength of that feedback loop and the resistance to anyone trying to break it. User experience remains awful, and crypto remains dominated by its dark side – 1 part genuine benefit to society, struggling to survive and be heard amidst 9 parts well-funded exploitation.

An Idea that May Help (Just a Little)

Breaking the feedback loop and fixing the massive problems with crypto will not be easy, but we can try to contribute in the right direction.

As we saw, one of the (many) things that has to change is somehow improving the user experience of users controlling their own digital assets. A number of folks have been chugging away on various solutions to this problem and I won't try to summarize those efforts here, but idea that Alex and I have published is intended to contribute toward that cause.

We think our "decentralized security questions" idea can help with the usability nightmare of the single private key that has absolute control of digital assets. The basic concept is to allow users to reliably use personal information that they already know about themselves (plus a little cryptographic magic) as part of their ability to control their assets on blockchains.

If you're technically inclined, here's a snapshot of how it works under the hood:

As we describe in the paper we’ve just published, this idea is far from a panacea on its own; it's more like a useful tool that may be combined with some of the other ideas being pursued by others.

The paper, along with some example code, are mostly intended for a technical audience working on blockchain tech, but it's all open source here for anyone who's interested:

https://github.com/Sajjon/svar

Our hope is that we may someday come to a point where blockchain moves past the era of quick money schemes, and that ideas like this one can be used to help solve real problems around digital ownership for normal people in a way that makes sense and is safe.

✍️ Articles on The Foolish Generalist are always written without AI. Here’s why.

I love cyberpunk.

I grew up in just the right place and time for cyberpunk's peak 80s-and-early-90s era to feel both plausibly prescient and totally rad. I had my hands on the embryonic forms of virtual reality that would get us there, and the Asia-inflected hyper-commercialized megacity concept seemed like a plausible direction Los Angeles could go given the right economic conditions (and maybe even felt like a welcome alternative to the dusty decay of 1980s LA).

Right here and now in 2025 – 6 years after the setting of Blade Runner – cyberpunk also provides a bracingly relevant framework for understanding our current world. We live in a reality of trillion-dollar transnational tech companies, AI technology that's cutting a swath through society like a pandemic, massive wealth disparities between the working class and the unimaginably wealthy, pervasive mass corporate surveillance, millions doing app-managed gig work, decentralized cryptocurrencies, government-backed hacker groups disrupting critical infrastructure and elections, and the population of the world essentially jacked into a shared infosphere 24/7.

For those getting started with the genre, I wanted to provide a primer and some entry points to understand what cyberpunk has to say and the kinds of worlds you can explore there, including a list of some of the works I think are the greatest and most influential.

So consider this article a dingy data stick, pressed into your palm in a dark alley – just out of holo-drone scan range – by an old sallow-cheeked netrunner with an outdated neural interface blinking at his temple. "I've seen things..." he mutters. "That is just a sample... I'll be here if you want more."

Cyberpunk Origins

Before I get to the list of media to plug into your brain first, let me define what defines "cyberpunk" that lives up to the name, starting with a little history.

Cyberpunk is a genre that could never be described as "timeless". Its unique combination of immersive future-shock excitement and techno-capitalist dystopian fear arose from a specific combination of late 20th century optimism and paranoia. It's a feeling that sizzled in the collective subconscious as we watched technology begin to remake the world at an accelerating pace.

The stories that first emerged from those fears and desires naturally looked fixedly forward. The foundations of the genre were laid by stories that imagined the dark side of what the world might become if unrestrained profit-driven technology development continued on its rising arc of dominance. What would it be like to live in that world, as the individual becomes insignificant and the line between human and technology begins to blur?

As the 1980s began, a dark future felt increasingly just around the corner (20 minutes into the future as one put it) and cyberpunk had found its moment. The genre rapidly built up a consensual hallucination of the cyberpunk future as writers, directors, and artists caught the mind virus and contributed their own take.

A common aesthetic emerged; it was a wild and sinister extrapolation of 80's greed-is-good economics, fast-moving technology, Japan at the height of its electronics and manufacturing dominance, and anarchist counterculture. The cyberpunk world sharpened into neon-lit focus with looming megacorps, inescapable advertising, chunky electromechanical cyber-tech, and a tech-savvy gutter-punk attitude for those living at the fringes.

Then something funny happened around the mid 90s: the tech outpaced the genre.

When the combined revolutions of the internet and personal computing took off, cyberpunk's paranoia and excitement might have seemed all the more justified and immediate, but the aesthetics of the future took a hard left turn and pulled away at full throttle. Moving into the early 2000s, brain interfaces seemed more distant, but internet technology blew past what anybody expected. The form of high tech redirected away from button-and-light encrusted devices, toward being connected, software-defined, touchscreen-enabled, embedded, and wireless – in short: invisible.

Now, out here in the far future of 2025 (6 years after Blade Runner's setting), we live in a a cyberpunk world stripped of the visual cues we expected. The true techno-corporate dystopia turned out to be clean, convenient, brightly-lit, and personalized. The brain interface we got was a rectangle of glass in our pockets.

Cyberpunk Endures

Despite its distinctly 80s origins, Cyberpunk has lived on. The genre has continued to tell stories that are all the more relevant, but often still wrapped in aesthetics that are now decidedly retro.

Because if that world was so engaging, why give it up as a place to tell stories that still have impact? In retrospect, it was always absurd to think that technology capable of futuristic miracles like mind-computer interfaces would look like the chunky electronic devices of the 80s (plus more cabling), and that cities would drift toward a fever dream version of 80s Hong Kong. But it's unquestionably cool.

Ironically, cyberpunk's world concept is no less fantastical than cyberpunk's awkward spin-offs like steampunk, which imagines futuristic miracles emerging from 19th century mechanical technology taken to dark extremes with the brass-and-oak British empire aesthetics. Who cares if it's implausible if it's a fun place to be? Star Wars has always played a similar trick, imagining far-flung future miracles that are riveted together like WWII bombers and and wired up like radio kits – ridiculous, but an evocative conceit for telling stories of a Nazi-Germany-like expansionist empire and a plucky resistance.

So Cyberpunk – even the unashamedly 80s-inflected variety – remains a genre worth returning to, whether for thoughtful stories about where we're headed as a society and species, or gonzo pulp noir tales that we can't put down. Maybe it is timeless after all, if we understand what makes it enduringly special.

Cyberpunk is sometimes treated as simply shorthand for "sci-fi dystopia", but I think it deserves a more specific definition. The Incal or Judge Dredd comics are great dystopian sci-fi (and highly influential in imagining sci-fi megacities), but I wouldn't quite call it cyberpunk because they focus more on the fantasticality of the world or themes of authoritarianism, rather than the sort of capitalism-driven class struggle and technology-driven redefinition of what it means to be human that gives cyberpunk weight.

I also think it's hard to call something cyberpunk if it doesn't have a pretty tangible link to our current world – a feeling that plausibly this dystopia might be lurking right around the corner. So as much as I love sci-fi works like Schismatrix or Quantum Thief that feature brilliant elements of post-humanism and even some punk ethos, their wild far future sci-fi worlds are too far separated from our own to deliver cyberpunk's visceral grit and paranoia.

So I'd say that cyberpunk has three absolutely essential elements:

• A world dominated by exploitative mega-corporations controlling high technology

• Technology that calls into question the nature of humanity and/or reality

• Massive economic inequality and violent class warfare as a result

The first gives the genre immediacy and relevance. The second gives you the cyber. The third gives you the punk. (And no wonder that there is a natural affinity with the noir genre: the big city, haves and have-nots, and a crime that links them.)

Building on those essential foundations, cyberpunk has collected a set of common building blocks that often contributes to a work's cyberpunkness:

• Virtual reality

• Androids and technologically augmented humans

• Artificial intelligence

• Technological singularities, with unpredictable runaway results

• Hyper-dense architecture, with the haves at the rarified top and have-nots at the filthy bottom

• Advertising run amok, lighting up the city in unnatural hues through the night

So using this as a guide, here are some of the greatest and most influential cyberpunk works across media, split into three eras of the genre's development (plus some extras at the end).

Cyberpunk Forerunners

A few key works ahead of cyberpunk's time that did it first and set the stage.

Metropolis (film, 1927, Fritz Lang)

Stop and appreciate just how ahead of its time this movie was. In the 1920s, the most bleeding-edge experimental technology was television. Electronics would be based on vacuum tubes for decades to come. Films, including this one, were still silent.

And yet Fritz Lang leaps straight to imagining a future of skyscraper-studded megacities, run by a corporate elite, supported by a workforce dehumanized by automation, and an android clone of a working class hero used to manipulate the opinion of the masses. You can draw a straight line from the mad scientist Rotwang to Blade Runner's corporate CEO Eldon Tyrell. Cyberpunk starts here.

Ubik (novel, 1969, Philip K. Dick)

Dick also famously wrote Do Androids Dream of Electric Sheep which (loosely) inspired Blade Runner, but for my money, Ubik delivers the better 60s proto-cyberpunk vision. Taking corporate dominance as a given, the world of Ubik is hyper-consumerized: everything used by the working class is coin-operated and “Ubik” itself is a marketing brand-name of shifting meaning. The protagonist is caught helpless in a struggle between corporate interests, and his reality begins to come apart at the seams. Explanations are elusive, but my read is that it's maybe the first novel that takes place in a form of virtual reality, all related to a mysterious technology represented by “Ubik”.

(Safe when taken as directed.)

The Girl Who Was Plugged In (novella, 1974, James Tiptree Jr.)

I will forever maintain that this criminally under-appreciated novella truly invented fully-formed cyberpunk and was the secret inspiration of the greats that followed. I discovered this long after reading through the cyberpunk canon and my jaw was on the floor. It has just about every element of story, tech, and aesthetic – in 1974 – that we would come to know as cyberpunk, and it's got the attitude locked down. Just read this opener:

Listen, zombie. Believe me. What I could tell you—you with your silly hands leaking sweat on your growth-stocks portfolio. One-ten lousy hacks of AT&T on twentypoint margin and you think you’re Evel Knievel. AT&T? You doubleknit dummy, how I’d love to show you something. Look, dead daddy, I’d say. See for instance that rotten girl? In the crowd over there, that one gaping at her gods. One rotten girl in the city of the future. (That’s what I said.) Watch.

Fucking cyberpunk. Swap AT&T and Evel Knievel for Nvidia and Travis Pastrana and you could publish that today.

Maybe the only thing The Girl... lacks is the lone hacker knocking around in cyberspace, encountering an emergent AI. Which brings us on to...

True Names (novella, 1981, Vernor Vinge)

Incredibly influential, Vinge's True Names establishes the modern notion of virtual reality – a shared global digital 3D space inhabited by avatars controlled by users. From that launching off point, he tells a story of wily hackers who get drawn into very deep virtual waters with powerful forces, and a conflict that has devastating effect on the real world.

After True Names, every writer had a concrete vision implanted in their minds of brain-computer interfaces, runaway technology, and the rapidly-approaching potential for humans to become something more.

Cyberpunk Peak Era

This is the time where all the pieces were in place for an explosion of cyberpunk output that felt just in time to understand, and be properly excited by/terrified of, the world we were about to create in the 80s and 90s. These are the works that achieved the highest highs for me, and it kicks off with a spectacular 1982 ...

Akira (manga, 1982, Katsuhiro Otomo)

No place on earth was riding the technological wave of the 80s harder and faster than Japan, and cyberpunk found a natural home there. Akira provided a feverishly imagined cyberpunk Tokyo overrun with technology like an invasive organism and a terrifying vision of corporate trans-humanism. It also established that the best cyberpunk protagonist is one from the slums with a high-tech motorcycle. The later film version is excellent, but nothing beats staring at the full-page spreads of the original manga.

Blade Runner (film, 1982, Ridley Scott)

In the same year as Akira, Blade Runner provided another aesthetically definitive cyberpunk vision. Syd Mead's design work on the film flipped the optimism of his prior (often corporate-funded) futurism on its head to create a bleakly failed techno-Los Angeles. Blade Runner, and its private dick android hunter, was perhaps the first work to recognize that you can map a straight noir tale directly onto cyberpunk and the result is beautiful.

Tron (film, 1982, Steven Lisberger)

Maybe a controversial pick. But my god, Disney released this in 1982? As groundbreaking as Akira and Blade Runner were during the same year, Tron was the first popular imagining of virtual reality as the battleground between the little guy and the corpo overlords (and their sinister AI). There's a weird kind of cyberpunk trinity here, linked by Syd Mead's Tron lightbike design – a crisp virtual object compared with the real-world grime of Mead's LA in Blade Runner, and an iconic motorcycle design that inspired the design of Kaneda's bike in Akira.

Neuromancer (novel, 1984, William Gibson)

Often cited as the seminal cyberpunk novel, Gibson puts all the pieces together: cyberspace, megacorps, hackers, noir, AI, Japan, digitized consciousness ... and throws in ninajs, mirror shades, razor fingernails, an orbital enclave for the wealthy, and a bunch of hip cyber-jargon that would end up sticking with the genre forever. Gibson has always been more of an observer of social phenomenon than a tech-head, but those have often ended up being the aspects of cyberpunk that have turned out to come true.

Robocop (film, 1987, Paul Verhoeven)

Maybe also a little controversial, but stay with me. While all the action in cyberpunk world is clearly happening around the Pacific rim (see above), I always wondered what was going on in the second-tier cities of the world. What about Detroit? OCP, ED-209, and Robocop – a man hybridized with tech for the profit of the local two-bit tech executives. It establishes the cyberpunk idea of the law enforcement protagonist who is almost as much a victim of corpo control as the suckers in the gutter.

Max Headroom (TV series, 1987)

Max Headroom has the honor of bringing a thick slice of no-compromises cyberpunk to television for the first time, and it's fantastic. Its own spin on the formula is to fuse the powers of tech and media under a dark governing corporate broadcast entity Network 23. Here the protagonists are independent journalists. Admittedly it missed the mark pretty badly on what the internet would do to news and networks. But: it has cyberpunk vibes for days, imagines digitized consciousness as not ready for prime time in the form of the glitchy Max, and it starts with the genius tagline 20 minutes into the future...

Snow Crash (novel, 1992, Neal Stephenson)

As Neal Stephenson tends to do, with Snow Crash he got properly obsessed with some stuff – corporations controlling the future and hacking the brain among other things – and drove those ideas to their extreme endpoints. This isn't just a dark city with the logos of corporates on buildings in 50-foot neon, it's an America that has spun apart into city states and franchise-organized quasi-national entities. It's cyberpunk on eyeball-injected neuro-stims, contains lengthy diversions on Sumerian culture, and not only puts the lone hacker hero protagonist (named Hiro Protagonist) on a motorcycle, but straps a katana to his back. It was also famously influential among the internet boom generation of silicon valley tech elite, among other things coining the phrase "Metaverse".

Ghost in the Shell (film, 1995, Mamoru Oshii)

For me, this is the pinnacle – the culmination of the genre, and the final capstone to the era of cyberpunk without a trace of irony. It picks up the thread of the augmented law enforcement officer, embraces the best cyberpunk elements of what came before, and weaves it all into a contemplation on the nature of conscious existence with flawless animated action across the highs and lows of its Hong Kong-inspired future city. Without it, The Matrix would not exist.

It could only have been made in the mid-90s; just late enough that the internet is a core part of the world (in a way that maybe only True Names foresaw), but early enough that the possibilities of the internet were formless, leaving room for Ghost in the Shell to fill up the imagination with a gorgeous and maybe-just-plausible cyberpunk world.

Cyberpunk Retrovibes Era

Heading into the end of the 90s and beyond, the cyberpunk aesthetic had dated itself and cyberpunk lost much of its literary steam. But it became a productive wellspring for film, TV, and video games for a certain kind of often irony-tinged nostalgia – an alt-future that might have been. A spate of truly terrible, lazy cyberpunk, VR, and hacker films did their best to kill the genre, but the good stuff has kept the flame alive.

Deus Ex (video game, 2000)

This wasn't the first cyberpunk video game by any means, but it was a superb achievement. It eagerly and lovingly put its arms around virtually every trope of the genre, and had the brilliant insight of adding conspiracy theory paranoia to the mix. Still worth playing 25 years later.

Altered Carbon (novel, 2002, Richard K. Morgan)

Similar to Deus Ex, Altered Carbon fully commits to the bit. It's every inch the pulpiest of pulp noir stories, told through a thick pastiche of timeworn cyberpunk tropes. There are no deep insights to be had here, but it's a hell of a joyride.

Ghost in the Shell: Standalone Complex (TV series, 2002)

This series is kind of related to the original 1995 movie, but is more of an alternate reality story than a sequel. It's a police procedural at its core that still very much inhabits the sort of cyberpunk world we saw in the film. The episodic format gives it a lot more room to explore the corners of that world and tell individual stories about augmented humanity, tech-enabled control and rebellion, and AI – as well as a longer-arc about emergent social phenomena in an incomprehensibly complex and interconnected world. It's fantastic TV, and I’ll take my dystopia with a tachikoma companion.

Psycho-Pass (TV series + films, 2012)

Made by the same studio as Standalone Complex, it almost feels like a prequel to that show, with things like cyberbrains and pervasive androids just on the horizon. Again a police procedural, it focuses more on surveillance, control, and power – and crucially the kind of people who come to wield it. It really hit its stride with the movie Sinners of the System which steps outside the typical Neotokyo city center to explore what we might expect in a wider cyberpunk global setting.

Mr. Robot (TV series, 2015, Sam Esmail)

The brilliant thing about Mr. Robot is that it's a fully committed oldskool cyberpunk hacker-vs-corpo story with all the beats you'd expect, but played absolutely straight in its setting in our current day, rather than a gritty cybercity. The insight here is that we already live in a cyberpunk dystopia, but without the neon-drenched trappings. And Mr. Robot gets extra points for being nearly as technically accurate in its depiction of real hacking techniques as you could expect from popular entertainment. The first season and (frustratingly) the last season are especially great.

And More...

While not trying to create anything like a comprehensive list of cyberpunk works, here are a few extra items worthy of a scan.

Neo Tokyo (film, 1987)

This anthology of 3 short films is a satisfying meal if hungry for more Japanese-inflected cyberpunk world building.

Shadowrun (tabletop game, 1989)

Not satisfied to just be a well-designed cyberpunk D&D style game, Shadowrun adds a magical fantasy element into the mix which is oddly compelling. The much more recent video games are pretty solid as well.

Blame! (manga, 1997)

This nearly violates cyberpunk requirements by being set in a far distant future, but I give it a pass because it's a future firmly rooted in a recognizably near-future cyberpunk world. Imagine the worlds above, and then let the forces of those worlds run wild for tens of thousands of years. Then begin your journey with a boy and a gun, trudging through the ruins.

Rainbow's End (novel, 2006, Vernor Vinge)

Sadly Vinge's last novel, Rainbow's End explores cyberpunk concepts stripped of the outdated aesthetic baggage and updated for the arc technology actually took in the intervening years since his True Names. Told mostly from the point of view of children who have grown up with elaborate augmented reality technology, it's a very different take.

Deus Ex: Human Revolution (video game, 2011)

A worthy extension to the original Deus Ex, with a greater focus on biotech.

Quadrilateral Cowboy (video game, 2016)

A tiny indie game with hilariously lo-fi graphics, nothing else has made me feel more like the elite hacker in a cyberpunk crew.

Cyberpunk 2077 (video game, 2020)

You gotta respect the dedication to crafting a deep and high-fidelity, while decidedly oldskool, cyberpunk experience.

Pantheon (TV series, 2022)

Based on set of short stories by Ken Liu. Like Mr. Robot, Pantheon sets aside the 80s aesthetics of typical cyberpunk, starting in a very familiar world – perhaps just a few years ahead of us. It imagines the tipping point when one of our current silicon valley mega-corps reaches a critical threshold of computing capacity, neural algorithms, and biotech and unstoppable forces remake the world as a distinctly trans-human cyberpunk place.

✍️ Articles on The Foolish Generalist are always written without AI. Here’s why.

If you've been trying to make your first GitHub project website using Github Pages and Jekyll, I wager you've gone through something similar to the sequence of frustration that I did:

• You heard that GitHub Pages gives your open source project free website hosting. Nice!

• You tried to use the cool-sounding "theme chooser" described on the GitHub Pages site, only to figure out that it has been deprecated in favor of setting up a website using Jekyll. Fine.

• You configured your project's repo Settings for a Pages website served out of your repo's docs folder or a special branch.

• You installed Jekyll, created an initial site, and filled in your site's info in the _config.yml. Hello world achieved! You saw a placeholder website with the default ugly theme.

• You excitedly went on to change the theme to one of the Pages-"supported" ones by simply specifying it in _config.yml.

• You loaded up the site to take a look and got a blank white screen – both in the local preview of the site on your machine, and on GitHub (if you pushed it). Um...

I found a few pages out there describing this problem and they all tell you to start downloading files from the default Minima theme's _layouts folder into your project, which doesn't quite solve things. And nobody seems to actually explain how Jekyll themes work or why exactly a blank page is showing up.

Using Jekyll with GitHub Pages is actually quite nice, and finally I figured it out and am a happy Pages/Jekyll user. I burned some hours getting there though.

The issue is this: while in theory you can just change themes with a _config.yml change, in reality it's a little bit more complicated than that. Here are a few critical pieces of info I wish had been explained up front.

The Basics of How GitHub/Jekyll Works

Basically, GitHub/Jekyll reads your _config.yml file describing how you want your Jekyll site setup (including which theme you want to use), grabs all the standard files from the theme behind the scenes, and builds your website automatically.

This is cool because you don't have to pull a full copy of all of the theme's files into your project and keep them updated (more about this here). All you have to include is what matters to you:

• Your _config.yml file configuring your website

• .md (or .markdown) or .html files that specify the pages the site will have and their content

• Any files present in the theme that you want to override (we'll get back to this)

This means that GitHub/Jekyll does not automatically pull in the default example .md or .html files from your template. And those example files are not the same between the themes – particularly between the initial default Minima theme and all of the other Pages-official themes.

When you first install your Jekyll site using…

jekyll new --skip-bundle .

… the installation includes:

• An initial _config.hml file, for you to customize for your site

• An initial Gemfile file, which helps configure things if you want to test it locally

• index.markdown, about.markdown, and 404.html example content files

• A _posts directory containing an example blog post markdown file

Why You're Seeing a Blank Page

The critical thing to understand is that those last two items – the various .markdown and .html files – are example content pages that are specific to the Minima theme. So after installation, your example site is working well! Then when you change to any other theme in the _config.yml, the example content pages from the default theme are still there, and they are referencing files that don't exist in other themes. Result: blank white page.

Let's look in more detail. For your fresh site install, the homepage is defined by the index.markdown file. Open that file up. You'll see the line layout: home. What this means is that Jekyll will look for a home.html file in the _layouts directory to define what that page should look like. You don't actually have a _layouts directory because GitHub/Jekyll will just automatically grab that from the theme behind the scenes.

The problem is that most of themes other than Minima don't have a home.html in their _layouts folder. So when you try to load index.markdown, that lookup fails for other themes and you get the blank page.

Solving the Problem

Understanding that, the solution should be more clear. You should not start grabbing files from the Minima repo's _layouts folder, as some online guides suggest, because those files aren't intended for other themes.

Instead, you should strip out Minima's example content files, and start with the example content files for the theme you actually want to use:

• Delete index.markdown, about.markdown, 404.html, and the _posts folder.

• Pull up the repo for your chosen theme (links here)

• Download any .md, .markdown, or .html files at the toplevel, and put them into your own site's toplevel

That done, your site should now appear the way it was intended for your chosen theme, including that theme's example files to get you started.

(As a note, read this if you want to understand the purpose of the _posts folder. In theory you might want it, but most of the GitHub Pages themes don't use it...)

If you open those files, you'll see the layout html files it expects in its own _layouts folder. If you want to actually customize any of those layouts, then you can create your own _layouts folder locally with the contained files from the theme's repo, and go to town.

And of course you can create your own .markdown, .md, or .html files to create new pages, each specifying at the top which layout file it should use from that theme.

Once you get past that part, the GitHub Pages documentation starts to become helpful again, telling you how to do things like customize the CSS of your site and such. Have fun!

✍️ Articles on The Foolish Generalist are always written without AI. Here’s why.

A Brief Introduction

Our general experience with light in the real world makes it seem quite simple and straightforward: Light lets us see what color things are. Mixing colors together creates other colors. A rainbow shows us all of the colors by splitting up sunlight. Lenses focus light to take pictures or project images. That kind of stuff that you probably got in basic science and art classes.

For a bunch of years I worked in the "photonics" industry – basically, technologies having to do with light. That field turns out to be quite esoteric, even though the output includes lots of everyday things like TVs, projectors, cameras, and lasers. The deeper I got, the more I learned that light – this seemingly pretty straightforward thing, is far more than it seems, and is often frankly just weird.

As I read more about the science behind the weirdness over the years, I realized more and more that even our own seemingly simple human experience of light and color hides an absolutely mind-boggling amount of physics and human biology. And the more I assembled bits of understanding into a bigger picture of light and color, the more breathtaking it became, flowing between aspects of physics and biology, art and expression. It felt a little like, in the words of Rust Cohle, mainlining the secret truth of the universe.

I always wanted to help other people see the hidden truth of color and light without having to pile through the esoterica of the science, but finding a good starting point was always elusive. Then I noticed a news item that struck just the right chord...

A New Color?

Science news headline writers recently had an unusually easy job making this story sound interesting:

Scientists Unveil 'Olo', a Brand-New Color Humans Have Never Seen Before

This Impossible New Color Is So Rare That Only Five People Have Seen It

And my favorite, from The Atlantic...

The 'Profound' Experience of Seeing a New Color - The Ecstacy of 'Olo'

A new color? Why have only a few people seen it? Ecstacy?

The obvious thing you'll go looking for in the articles is the description of what Olo looks like (as seen by one of the lucky five who've seen it):

He described the color as a beautiful, ultra-intense teal.

(Link to the research paper where you’ll find the quote, if you’re so inclined.)

Now… intense teal sounds a lot like an existing color, not a new one. I can imagine many readers closing the article muttering about yet another sensationalized science headline.

There is, however, actually something quite amazing about olo. And not only is it interesting in its own right, it gets right to the heart of the surprising nature of color itself. That's because before you can say whether it's right to call olo a "new color" or not, you first have to define what you mean by "a color". And once you've done that, you can start to see how something like olo really could be a thing of ecstasy.

Prismatic Color

A reasonable place to start defining "color" is using nature's perfect palette: a rainbow. Thanks to popular science educator, Pink Floyd, we know that we can use a prism to create a rainbow by splitting up white light into the colors it's made of:

What is being "split up" here are different wavelengths of light. For example, if you want to identify a particular shade of green in the rainbow, you can measure it to find out that its wavelength is, say, 540 nanometers.

Understanding what "wavelength" really means is a story for another day. For now, don’t worry about what “nanometers” is about; it's safe to just think of wavelength as a label for different colors from the rainbow. (Color scientists are so used to this way of referring to colors that if you say 680nm or 480nm, they immediately see in their minds eye deep red or pale blue.)

So you might think that we already have a nice simple definition of color:

A color is a particular wavelength of light.

However, it turns out that that definition isn’t very complete. In fact, it has a couple of pretty surprising problems. To explain, we have to open up the eyeball (and the brain, a little bit) and understand exactly what happens when we experience color as humans.

Connecting Color to Our Brains

The retinas in our eyes are made of special light sensor cells (or "photoreceptors" if you want to be fancy). Those cells are spread out across the back of the eye kind of like the pixels of a camera sensor. You probably already know this part. What exactly do those cells do though?

Each sensor sends a signal to the brain if you hit it with light – the more light, the stronger the signal. You can think of the signal from each sensor cell as a reading on a brightness meter, ranging from "I see no light" up to "this is the brightest light I can deal with".

So imagine every sensor cell in your eye wired up to your brain, spitting out a meter reading for each "pixel" in the camera of your eye. But notice in the diagram above that each meter reading doesn't say anything about the color of light hitting it – just the brightness of the light. So it seems like the camera of our eye would only see in black & white.

The way our eyes add color to the picture is by having different kinds of sensor cells, which lets the brain pull a clever trick...

A Clockwork Orange

Let's break down how we experience one color from the rainbow, orange (wavelength of 600nm).

If we only had one kind of sensor cell, there would no be no way to tell this orange from any other color. But fortunately us humans actually have three distinct types of sensor cell, which color scientists tend to call S, M, and L. Each type of sensor cell can only sense brightness from a particular part of the rainbow:

• S (for "short", smaller wavelengths) senses brightness of violet/blue colors.

• M (for "medium", wavelengths in the middle) senses brightness of colors around the greenish.

• L (for "long", larger wavelengths) senses brightness of colors that are around yellow/orange.

Here's the part of the rainbow the S, M, and L sensors can each see respectively.

Remember, though, that each sensor doesn't know what colors are hitting it. So what the three types see is really more like this.

If each type of sensor is hooked up to a brightness meter, what do those meters show for our 600nm orange light?

The S sensors (which only see violet/blue) see almost nothing of our orange, the M sensors (which see around greenish) see a little brightness, and the L sensors (seeing colors around yellow/orange) see quite a lot of brightness. Like this:

Now here's the really important and interesting part:

The brain combines the readings from all three meters to decide what color you see.

Let's stop for a moment to understand this, because it's quite amazing.

When we look at a rainbow, we see an array of vibrant colors that couldn't look more distinct. Try to count the colors and you'll pick out maybe 7 "major" distinct colors, with smooth shading between them.

Given that, you might expect that our eyes would need at least 7 different kinds of sensor cells to create that experience. And yet, because of some clever clockwork in our brain, we can make do with just three!

How does that work? When the three types of sensors send out their meter signals, the brain is looking at the ratios between them to figure out the color. Like this:

What is red, to the brain? It's the kind of light that mostly lights up the L sensors, just a little bit of M, and no S at all.

Moving down from there, orange is when there is a greater ratio of M – and yellow is when there is even more M. Green is when M now reads higher than L (still with no S). Cyan has less L still and brings in a little S. Blue loses nearly all L and most of the M, and violet is just about only S signal.

The ratio of those three meter readings is enough for the brain to create the mental experience of a rainbow in all its vibrancy, letting us see the different wavelengths distinctly.

So when we look at our 600nm orange, a special mix of L and M sensor signals are sent to the brain. The brain then creates a mental symbol – a new experience – for that combination of signals that we come to think of as a particular shade of orange. It’s the mental symbol that is triggered for our experience when looking at a sunset or an orange fruit, and maybe we start to associate it with feeling of a cool dusk breeze or the taste of citrus. (And there’s more for another day about that translation of sensation into the realm of mental symbols…)

Getting Back to "What is Color"

This is all interesting, but why is there a problem with our proposed definition of color?

Here, again, is what we proposed:

A color is a particular wavelength of light.

Now that we understand more what’s going on in the eye and brain, this has two problems.

First, let's look what happens if you show more than one wavelength of light to the eye at the same time. Let's combine a some red (640nm) with some green (540nm).

The sensors in the eye measure a combination of the light from those colors. Basically, it's like taking the meter readings we'd get for red and for green separately and averaging them together into a single set of S, M, and L readings.

And once we've combined those readings, the result is familiar if we look at the meter readings above for single colors...

Mixing red and green creates the same meter readings that we got for yellow from the rainbow. That means your brain can't tell the difference between rainbow-yellow (570nm) and red + green (640nm + 540nm). The colors (by their wavelengths) are very different, but the resulting meter readings are the same, and so the experience the brain creates either way... is yellow.

This is kind of mind bending, but we see it every day.

Computer and phone screens can't create just any wavelength of light they want – they are usually designed to only create red, green, and blue light. But using different combinations of red, green and blue, it turns out that you can use the trick above to fool the sensors in your eye to see (almost) any color in the rainbow.

A side note here: You may have thought that the sensor types in our eyes were red, green, and blue – matching up with the red green and blue of computer screens and camera sensors. As we saw above looking at the S/M/L sensors, that's not actually true. However, using some clever math, we can show that as long as you have a wide enough range of any three colors, you can reproduce just about any color the eye's three sensors can see. Red, green, and blue provide a usefully wide "color gamut" to capture or display colors intended for humans.

It isn't just a trick of computer screens either. Colors in nature are almost always mixtures of lots of wavelengths. What looks like a yellow flower might actually be reflecting almost no yellow light around 570nm. It might just be reflecting lots of both red and green and your brain sees that as yellow. That yellow is no less "real" than the one on the rainbow, because your experience of yellow is defined by your brain.

Another side note: If we had a fourth sensor cell type in our eyes – maybe one far at the reddish end – we would in fact be able to tell the difference between yellow-from-the-rainbow and yellow-from-red-and-green. They would look like different colors entirely. What would those colors look like? Nobody knows; our brains aren't wired for it. But the brain of the mantis shrimp is, because it has a dozen or more types of sensor cells in its eyes. A mantis shrimp would be thoroughly unconvinced looking at a picture on a computer monitor, trying to recreate colors with only red, green, and blue!

So a color is not just "a particular wavelength of light", as we originally proposed. Problem #1, as we've just seen, is that what we experience as a single color (like yellow) isn't only created by a single wavelength. It can also be created by a combination of wavelengths.

Problem #2 is where it gets really interesting: There are very real colors we experience that have no single wavelength at all. They don't exist in the rainbow.

How's that possible?

Look again at the meter readings of the rainbow colors above. Even pretty small differences in ratios can create the experience of very different colors in the brain. But looking at the different ratios of meter readings for the rainbow colors, we can imagine some pretty distinct ratios of meter readings that don't appear at all.

For example, none of the rainbow colors combine meter readings lots of S and L at the same time.

Is that combination of meter readings even possible? It's actually pretty easy to get close to, but we need to use a mixture of colors: Blue light drives pretty much only the S sensors and red light drives pretty much only the L sensors. So if we combine blue and red light, we can get quite close to our mystery not-in-the-rainbow ratio.

What happens when you feed the brain signals like this?

The answer is, basically, barbie pink. Pretty attention-grabbing, right? It’s not so surprising when you realize that it’s a color pushing your brain’s buttons in a pretty distinct way.

You won't find that hot pink/fuchsia color in the rainbow, because it can only be made by a combination of wavelengths at opposite edges of the rainbow’s spectrum. Whether you’re seeing that color on Barbie, the fuchsia square on your computer monitor above, or a flower in nature, the only way to get the S and L sensors to light up to create that color is with a combination of blueish light and reddish light at the same time.

So defining “color” is a lot more complicated than it first seems. We've shown that the experience of a color isn't just a single wavelength – it can be created by a combination of wavelengths. We've also shown that there are very real (and very attention-grabbing) colors that can't be created by a single wavelength at all.

What About Olo?

Right, so what kind of color is olo, from the science headlines?

Look again at the meter readings for the rainbow colors. We found a ratio that wasn't present there – lots of S and L with no M – that creates a quite shocking color: Barbie pink.

There's another distinct ratio missing: what if we could have only M, with no S or L?

Since unique ratios always create the experience of different colors in the brain, we would expect that this would create quite a different color experience.

That color is what the researchers named olo. But it's much more elusive than Barbie pink.

I’m completely unable to put an example square of olo on this page like I can with Barbie pink. Fuchsia is a combination of two signals, which we could do pretty well using red and blue to isolate the S and L sensors. But to create olo, we need to isolate just one signal: M. Because M is in the middle of the rainbow, there is no combination of colors that can do that. All of the wavelengths that push the M meter up also push up either S or L. For example, you can see green and cyan push up the M sensor readings strongly, but green also pushes up L quite a lot, and cyan even includes a little bit of S.

To trigger M sensors alone, you'd somehow have to put light only on M cells while preventing it from falling on S or L cells. That's impossible when looking at anything in the world because sensor cells are extremely small and any spot on the retina includes all three types of sensor. So instead you'd have to do something crazy like:

• Scan a specific person's eyeball and create a map of all of their individual sensor cells by type

• Create a super-fine laser that you can aim into an eyeball and aim precisely enough to hit exactly one sensor cell at a time

• Track your subject's eye and fire the laser at a cluster of individual M sensor cells, avoiding all of the S and L cells

If you could do that, then you would have full control to create whatever ratio of meter readings you want, including the mysterious M-only olo ratio.

And that is literally what the olo researchers did, which is absurd. It's also why only 5 people have seen it – it's extremely difficult to do the individual eyeball scans.

So...

We know what L alone looks like: Red.

We know what S alone looks like: Violet.

What does M alone look like, unmuddied by other signals? Olo.

Olo is kind of close to green or cyan – which also have a lot of M – but we'd expect it to be a color that is far more intense. It might be kind of like the crazy intensity of Barbie pink, but "opposite" in some sense (since it is made from the opposite sensor ratio).

And indeed here is what the lucky 5 had to say about the saturation (the intensity/vibrancy) of olo:

Subjects consistently rate olo’s saturation as 4 of 4, compared to an average rating of 2.9 for the near-monochromatic colors of matching hue

It has to be incredible to see a color that is so much more intense and vibrant than the nearest "regular" color at its brightest.

The best I can imagine is by comparing it to the opposite. Take the most intense cyan your computer monitor can produce, and then start adding other colors to desaturate it (less saturation). It fades... becoming turquoise, pale aquamarine, a misty sky blue, and then ultimately white – the color we see when all three types of color sensors are activated at the same time (although there's much more to white - another story for another day).

Olo is in the other direction, becoming more saturated than cyan/teal by removing colors that would normally be impossible to remove. It would go from an already quite intense color to something... unimaginable unless you’ve seen it.

Olo is a real color that our brain can experience, but not by looking at any light or object in the world that can ever be created (which makes it very irritating that somebody is claiming to now sell olo paint – it's just teal, dude). Olo can only be created by reaching into the eye and plugging straight into our individual sensor cells.

Crazy. I hope I can see it someday.

Thinking Bigger

Olo is just an introduction - a beautiful one to the true nature of color and light and how full of wonders it can be. So let me get a little Sagan here and point the way to the bigger picture...

Olo has given us a taste of a richer answer to our original question of what a color is, but not a very conclusive one. The wavelengths-of-the-rainbow definition seems to be contradicted by the ratios-of-color-sensors definition. So which is it?

It's both... and many more, in fact.

The prismatic spectrum of wavelengths in the rainbow are colors in a very important way; they are fundamentals of physics, unchangeable and precisely measurable. Those colors have deep meaning.

All matter in the universe is constantly vibrating at an atomic level, and those vibrations create light that broadcasts the echoes of those unique vibrations as different wavelengths of color. The whole Universe rings with complex chords of color, keyed to the tune of each object's individual chemistry as things glow, collide, explode, and live. As light spreads outward, it falls on other objects and strikes new chords in those materials that are rebroadcast once again as combinations of color.

The vibrant colors of crystal formations, the green of leaves, the red of blood, the blue of the atmosphere glowing in sunlight, and the swirling chemical hues of planets, stars, and galaxies – their colors all sing of their essence, far beyond what we can see with our eyes.

At the same time, color is also truly subjective. It is a creation of the mechanisms of our human eyes and mind. By capturing light, the sensor cells in our eyes hum in sympathy with the vibrations of objects right in front of us and at unthinkable distances. As we've seen, our eyes can only hum three closely-spaced notes to the brain, so there are many colors we cannot see directly. But even that is enough to create an incredible awareness of the world around us, a beautiful glimpse of the rich symphony of Earth and the Universe.

Humans have also learned how to extend our senses, building artificial "eyes" that can see exquisitely fine gradations of color, and wavelengths billions of times beyond violet or red. And how strange light can become in these exotic colors! In some wavelengths, a glass window is opaque while a slab of metal is completely transparent. In others, a seemingly dark patch of sky is bright with galactic activity.

Increasingly we can listen in on the full symphony of color around us, giving us profound insights into the Universe and the fabric of reality, because light itself is woven deeply into the finest structure of that fabric.

You've probably picked up that the story of Olo leads off in a number of other directions – stories for another day. And I hope to pick up those threads and see where they lead in future articles...

✍️ Articles on The Foolish Generalist are always written without AI. Here’s why.

An Uneasy Global Village on the Web

The early 2000s brought an explosion of experimentation with what could be done on the web, and nearly all of my friends from Ishar dove into software development. They companies they joined, from startups to megacorps, raced to be part of the boom as they figured out how we would work, play, buy, sell, educate, and entertain online.

The experiments with social communication were as wild as anything else. Wave after wave of social platform explored every imaginable way in which we could make it quicker and easier to do the sorts of things people do together: share, discuss, follow, show off, argue, and all the rest. It seemed like the global village was finally under construction.

Something strange happened during that couple of decades of growth. The internet became more and more convenient and pervasive, and we all got more and more constantly connected and at higher fidelity. We came to take it for granted that all information and commerce is a couple of taps away on our phones, in words, emojis, pictures, and high-resolution video. All of us now have, from an 1980's perspective, unimaginable superpowers in our pockets. And yet... many of the most popular ways that we connect and socialize with other humans using those powers feel kind of wrong.

If we've moved into a glorious era of the global village, why are we constantly talking about social media addiction, doomscrolling, digital detoxes, and getting pulled down rabbit holes of obsession, hate, and conspiracy? It doesn't feel like a village, full of possibility and human connection. Using social media doesn't feel like membership in a community.

To be less pessimistic, the shrinking of the world is truly incredible. There are indeed corners of the internet where you truly can find oases of your people.

But my experience has always been that these oases always feel fragile and limited – like the exception rather than the rule. Even platforms that start out feeling like engaging communities devolve into competitions for the fleeting attention of strangers and sources of “content” that’s more like mindless channel-surfing than discourse. And the ones that don’t embrace that model die off.

To take a few examples:

The old web bulletin board / forum format has been a mainstay of enthusiast communities, offering a lot of community features that work. As an example, for about 15 years I logged onto a forum for electronic makers and listeners before its main admin didn't want to deal with the burden. And that's often the fate of this format. The user interface doesn't translate well to mobile phones and they're a dedicated effort to setup and maintain, so few are created, and they slowly die off unless supported by an insular group of enthusiasts.

Reddit has tried to fill this niche with some success, but it's really designed more for a social news feed of highly topical, standalone "now look at this" posts rather than maintaining a cohesive community. When my music forum was trying to find a new home, Reddit felt like a huge step back and the group ended up just creating another web forum for us oldsters to haunt (shouts to the Keyosc crew).

MMO games have often been a haven for vigorous community, a bit like Ishar was in the pre-graphics days. When some old Ishar friends got into World of Warcraft and convinced me to join them, it refreshed some dormant friendships – and when I parted ways with the game, I lost touch again. And that also tends to be the shortcoming of these communities; they are so intimately tied to a particular game with a limited lifespan, and there is so much game fussiness involved in accessing them, that they never work as a purely social platform once you're done playing. Unless you get sucked into one of the surprising durable game worlds, with their very particular cultures, like Eve Online or Second Life... it's not where you're going to want to hang out and meet new people online.

Chat apps like WhatsApp offer some promise. I'm sure you've got a set of private chat groups in one (or many) of these. But these don't really go all the way either. If you've got a group of people who live in other cities, you probably swap links and happy birthdays, but the chat goes silent for long periods. When there's just that one "room" that everything goes into, getting into a lively discussion or sharing frequent updates about what you're doing can feel overbearing for a group of more than a handful of people. Chat groups don't feel rich enough to maintain a community, and there's no sensible built-in way to grow a community with members you don't already know.

As I've experimented with platform after platform over the years, nothing has recreated that real sense of satisfying, tangible community that I experienced on crude old Ishar, let alone surpassed it as we always expected the internet would. Despite being instantly connected 24/7, friends slowly drift apart other than a few messages and conversations here and there, as if we were still in the time of letters and phone calls. As I've worked in different parts of the world, really amazing and interesting people I've met say we're going to stay in touch, but there never feels like a good way to maintain the close group dynamic we had in person.

Why is this so hard?

I want to try to break it down to figure it out.

Social Media's Illusion of Community

If we fast forward through 30 years of social platform experimentation, the result today is two dominant social communication paradigms – two ways that we communicate human-to-human on the web: messaging and social media.

Messaging is the realm of things like SMS, WhatsApp, Messenger, Kakao, Telegram, Signal, WeChat, and LINE. The chats that we have there are certainly social, but going back to an earlier point, it's much less community than it is correspondence. It's all the stuff that, in an analogue age, was done by letter or phone call. We send notes, have brief chats with individuals or small groups, forward around links and memes, and "stay in touch" with people there between in-person gatherings.

Messaging is incredibly useful – a huge advance over what came before. But it's not a complete solution for all of the ways we want to socialize. It lacks the essential features of membership and participation in a wider community that we also crave.

That’s where a second paradigm has come to try to fill that need...

Social media is sustained by the community urge – it has become our "global village". Going by user numbers, apps like Instagram, Facebook, Tiktok, Snapchat, Threads, Twitter (I'm not calling it X), and Reddit dominate how people gather together in groups online. But despite the global popularity and many options, it's a struggle to find real community there.

Now it might seem ridiculous to say that the internet lacks community. When you're obsessively checking half a dozen social media apps, too much community might seem like the real problem. But I believe what we've ended up with is an illusion of community that absorbs all of our mental space for community socialization online while delivering something else.

Many times social media platforms launched on the promise of community – and maybe even delivered it early on. The basic concept of myspace, facebook, twitter, flickr, instagram and many more was this: connect with your friends, share what you're doing with those friends, and let them react. It's an appealing idea: on a single global platform, communities can emerge by people following each other, and they can all pop in to see what's going on with each other, discuss things, collaborate, and so forth.

But we have ended up using social media in practice isn't that. Usually we open the app and scroll through a feed. Maybe that feed has a little bit from your friends, but mostly you see content created by personalities and companies, either those you’ve followed or those served up algorithmically. Many social media apps started with the ability to see "just updates from friends" or to great little private sub-groups, but they've all drifted away from those options and have locked onto the feed as what you should be doing, and what's easiest to do. The latest apps like TikTok have fully embraced that approach, putting all of their tech into creating the most compelling feed possible so you there's always another surprisingly-relevant thing for you to burn a few more seconds on.

That's a very different dynamic from being a member of a community that gathers in the town square. We feel more like a faceless viewer in an audience of billions rather than a contributing and known community member.

What happened? We all have a deep need for real community, and we know the internet provides us with the tech to do it online. So why are we all mostly just scrolling through feeds of influencers and content creators who don't care who we are beyond our likes and follows?

There's a very long story for another day here about the underlying forces that got us here; I've come to believe it's part of the greatest shift in society since the printing press. But setting aside those reasons for now, the main problem with social media is this:

In a true community, all members are peers. While there may be differences in status or reputation or authority, the primary dynamic of interaction in a true community is communication, sharing, collaboration, and contribution among members whose individual identities are important.

Instead, the primary dynamic of interaction on social media is broadcast. In any interaction, you're either a broadcaster or you're the audience; the content creator or the content consumer; the one going for the likes or the one giving them. Rather than solving the problem of creating communities online, social media has ended up fully focused on democratizing access to global broadcast at a scale that previously was reserved for giant private or state-owned TV/radio stations, publishers, studios, and other entities with the means of distributing content to millions.

It is of course a revolutionary thing that the power of broadcast is no longer reserved for the few and the powerful – it's now available to all of us if we want it. But humanity has never had that power before, and we're discovering that a model of socialization that centers on millions of broadcasters gives the surface appearance of global community – a global village – while actually creating a very different result for us as individuals, and for the society we live in.

Maybe you've felt the effects of how this democratized broadcast dynamic has a strong community-like pull, but results in something much less satisfying. We can list out examples of what we need from real community, and what we get on social media instead:

Membership

We want to belong within a community, where we become known for who we are as we participate and contribute and a sense that we know (or can know) the other members of our community.

Social media promises membership not just in own personal communities of friends but the largest community possible – the global village. The FOMO of what the world is talking about is intense.

But on social media, the only mechanism of membership we have is the "follow" – to become part of a broadcaster’s audience. That means that the only sense of belonging social media delivers is the feeling of being one of many following the content creator(s). The broadcaster has to power to define the pseudo-community, its values, and its culture, and membership is contingent on echoing those values and culture. It replaces a sense of familiarity and fellowship with something even more primal: leader worship.

Reputation

We want to become known within our community and develop some status or respect, to become known for the uniqueness of our interests, skills, or just eccentricities. We also expect to have an opinion of the reputation of the other various members in our community because we know them and they matter to us. Reputation just happens naturally for all members.

Social media seems to provide a forum for us to present, day by day or minute by minute, a picture of who we are – to become known by a global community.

But in social media's broadcast model, your reputation is your content. Being known to an audience-community is only available to the broadcaster who gets views and follows. Reputation can only be earned with engagement, and if you're not a natural (and successful) exhibitionist you're left to be an anonymous follower of what everybody else is doing.

Meaningful forms of reputation like respect and credibility are replaced by raw popularity – how many followers and likes you've got. Your reputation is that you're an influencer with a tribal following or you're nobody.

Competition

We want to have the opportunity to show off our talents and abilities a bit, to add to our reputation by demonstrating that we're the best at something within our community. If you have a competitive streak, what could be more exciting than competing on a global scale with everyone on social media?

Social media provides a “community” in the form of a global audience that only knows you by your ability to draw engagement, and very few can achieve anything that draws that engagement when competing on a global scale. Worse even than the old broadcast era's urge to win your 15 minutes of fame, there is a constant pressure to win fame by capturing the attention of a global audience for that critical few seconds – in every post, by any means necessary. Simply being known as the one who's pretty good at something within a group of people you care about is lost in the global feed, and you're left feeling mediocre.

Sharing

We want a forum to share our experiences, creations, ideas, fears, and all the other things that add up to our lives. Sharing within a community of people we care about gives us a sounding board, a source of comfort or encouragement, a place to find accountability, and a source of valuable feedback from those who know you. It encourages discussion, understanding, and closeness.

Social media thrives on providing tools for frictionless, constant sharing. It promises that you can easily create a constant connection with your friends while your ideas can spread further and your creativity can find its fan base.

But in the social media broadcast model, every share is pushed into the same pipeline of engagement-driven content. It's difficult or impossible to share specific things contextually with the right set of people, and everything is depersonalized and reduced to something that exists to get a quick like as people scroll by. It feels like your only options are either performing an exaggerated life, set of opinions, and creative output that triggers the algorithm and chases the latest trends – or else have it all be irrelevant to share with anyone.

Collaboration

We want real community that gives us access to a pool of potential collaborators and a place in which to explore and create and build together closely.

Social media feels like the ideal place to find like-minded collaborators wherever they might be.

The foundation of collaboration is building up familiarity and trust, which flourishes naturally in real community, but is nearly impossible to create in the broadcast/audience social media model. Everything you post has to already be clickworthy and monetization-ready, and the natural mode is dog-eat-dog not collaborative.

Contribution

We want fulfillment by finding ways to contribute to and support our community and its members – to give back, and to improve.

Social media seems to offer a global forum to contribute to the most important causes.

In reality, when broadcast and engagement are the only available forms of participation, the only form of contribution you're left with is "raising awareness". The only thing that seems to have impact is to seek the viral feedback loop of rapidly amplifying the latest cause that is attracting attention within the tribal "community" that we inhabit. And when you’re competing for impact via clicks, only simple absolutes rise to the top, encouraging a kind of exaggerated performative contribution – usually in the form of easily re-shared outrage, ridicule, and echoing tribal values.

In short, rather than bring community into the digital age, social media has invented something new using the newly-possible democratized broadcaster-audience technology. It’s a form of global social interaction where you’re either a broadcaster competing with millions of others for engagement, or you’re the audience scrolling content as if clicking the remote control on a TV with millions of potential channels, each one only showing the highlights.

As an audience member, it’s channel-surfing that pushes our brain’s community buttons. Social media is inherently impersonal, but the feed presents us with content tuned to feel like it’s just for us. We may not know the content creator or almost anybody else liking or posting a quick comment, but it provides a zero-effort satisfaction of that urge to be part of the group. And even if the content is broadcast to millions, because it’s created by individuals rather than centralized broadcasters, it feels more like authentic personal 1-to-1 communication.

But Why?

If we can see that social media gives us a poisoned illusion of the community we really want, why aren't there alternatives – or at least why aren't they more popular? Democratized broadcast certainly has its place, but why has it so completely coopted our need for real community?

As I've searched for answers in my quest for community online, I've realized that the root cause isn't as simple as badly designed platforms or evil social media CEOs.

I think we're seeing the internet unleashing a fundamental and irresistible transition in society that hasn't been seen since the invention of the printing press. As the guy who coined "global village" put it: the medium is the message. The internet, and social media, gives humanity a new and immensely powerful medium that is nearly unlimited in the communication it enables, and we're seeing what happens when that global-scale power is opened up to human beings with a village-scale desire for belonging and status. And then there's that desire for profit too...

There's much more to say about this transition, its effects, and its historical precedents – but that's a story for another day. For now, maybe we can all just be a little more aware of what real community means and try to seek it out where we can – online or not. And maybe we can scroll through the feed a bit less, if we recognize its FOMO siren song and see what it isn't giving us in return.

✍️ Articles on The Foolish Generalist are always written without AI. Here’s why.

A Quick Introduction

One of my reasons for starting this blog was a hunger to build a little more digital community with all of the interesting people I've connected with over the years. I've always had a strong desire to be part of a global community. The further the places I go, the more interesting the people, ideas, and viewpoints I encounter – and it's addicting. That desire has led me to push my career in directions that naturally get me out into the world, and as a result I've been very fortunate to get to know and work with some really interesting people from a lot of places.

But somehow, despite being instantly "connected" with all of those people around the world on various chat and social apps, it never quite feels like real digital community. After 30 years of internet technology advancement, something important feels missing on today's standard form of connecting with people online: social media. Maybe you've also felt the pit in your stomach as you scroll through your feeds and tap like.

I've long found this frustrating because I have experienced real community online in the early days of the public internet (and pre-internet) when it was first possible to be instantly and digitally "connected". What have we lost, and how did we end up here?

In trying to answer those questions, I've discovered that the difficulty in finding satisfying community online is just one symptom of a much larger and quite profound change in human society that been accelerating across the last 30 years since we first start moving online. That change is so large-scale that it's extremely difficult to see in whole, even through the symptoms we feel in many parts of our lives are very familiar. As just a single example, we live in a time when we can watch first-hand as real geopolitics are conducted between the most powerful nations on earth in public over Twitter; that sure wasn't the case even 10 years ago, and it would have been unthinkable 20 years ago. I think many of us have the sense, with increasing panic, that the world has been knocked out of balance in some way, and it at least has something to do with social media.

I want to explore that big society shift. But to paint some background first, I want to tell you about the strange experience of growing up while making the leap from a fully analog world into some of the very earliest and vibrant forms of digital community and how that early promise has been lost in the world of social media today.

(If you want to skip the slightly self-indulgent GenX geek nostalgia, you might consider skipping straight to part 2. I won’t be mad.)

The End of a Disconnected World

I was born in 1977, the year of the Apple ][ and the TRS-80 and right when the first mainframes were being connected via TCP/IP to become the embryonic internet. Those two technological advancements – the personal computer and the internet – would mature and come together in the 1990s, exponentially increasing each other's power to create the beginnings of a world-remaking revolution.

Those years of the 80s leading up to a revolution were, in retrospect, the last years of a disconnected world. It's a difficult mindset to recall now, but prior to the devices and platforms that would remake our lives in the 90s and beyond, our whole lives in the 80s were largely defined by the contents of a bubble of physical territory that we could easily walk or drive to.

Of course we weren't completely cut off from the world. The technology available in the 80s could bring you information from outside your bubble – but slowly and from a limited set of broadcasters and publishers with access to the mechanisms of mass media. You had to tune into your local evening news broadcast, get delivery of a daily newspaper, borrow a book from the library, or visit the local auto club for a map. You were aware of the world out there, but it still felt distant.

Your actual experience of living was inherently local. Specifically, your community – the people you talked to, worked with, shared with, sought approval from, and more – could realistically only be drawn from the people in your walkable/drivable bubble that you could meet and spend time with in person.

But didn't we still have options in the world of the 1980s for 2-way communication outside our bubble?

Sure, you could send a letter or (expensively) make a call to somebody on the other side of the country or world. But that's just correspondence, a single conversation. You could have a group of people living in different cities united by a common interest or family ties, but the only way they were held together as a community was to meet up somewhere in person once in a while. Those in-person gatherings were where individuals became known members and engaged in the real business of sharing, discussing, arguing, contributing, and competing. Afterward you all went home to your local communities and promised to "stay in touch" until the next time you got together to take the community out of suspended animation.

Discovering Pre-internet Digital Community

Within that world, as a kid and a congenital geek, computers were exciting. Fortunately I had the extreme good luck to grow up in Southern California around JPL engineers and scientists, and with access to early personal computing hardware. When I had to choose summer classes, my finger slid straight to computer programming (LOGO and BASIC). A government-issued "portable" PC came home with my dad at one point and was instantly annexed by me to write simple programs, tap out ASCII art, and play text games like ZORK.

When the movie WarGames came out in 1983 and Matthew Broderick connected his computer over a phone line using a modem (!!) to a government system (with an AI no less!), nerd minds blew. I may have written a script to simulate me hacking into a DoD mainframe and launching Global Thermonuclear War.

Nothing felt more crackling with potential to me than the idea of connecting my computer to other computers used by other people in distant places.

Consumer modems first became available years before the internet became widely accessible. The main use was dialing into private corporate systems, but quickly people created something else you could dial into: bulletin-board systems (or BBS's). So of course as soon as one friend's dad brought home a modem for work, he managed to get his hands on a list of BBS phone numbers around LA and we started dialing. And what did we find?

Digital communities. And wild ones.

Each BBS was the home for a group of people who used "handles" instead of real names, but they were known within their community by what they said and created and shared. They posted ideas and rants to a common message board. They sent private messages to each other. As a group, they created a shared repository of stories and art and demo code (and, er, less noble things) often created by the members themselves.

They had bitter arguments, they found friendships, they formed cliques and collectives, and they fed off each other's creativity and competed with each other. Anyone could dial in to a BBS fresh, but a new user often had to earn acceptance into the community – either by raw contributions to the commons, or sometimes by demonstrating they were a reasonably interesting person to talk to, not just a leech.

BBSes were still largely local, however. They drew their denizens from within local borders drawn by the AT&T company because nobody wanted to pay ludicrous long-distance fees for their modem to stay connected for hours. But for a teenage geek in the early 90s, you could suddenly find (or even create) a community of your people not just from your school, but from all of the schools of your area code (hundreds, if you were in Los Angeles at the time like me). And you were more likely to find a lot more of your people there because kids who were drawn to dialing in to BBS's tended to have some, er, commonalities of personality and interests (which might not make them so popular at their respective schools).

The revelatory impact of experiencing this new form of community is hard to explain.

The Importance of Community

Community is an incredibly powerful thing; the desire for it seems wired into us at a genetic level. We have a need to belong to groups where we are known for who we are and what we've achieved, where we can share thoughts and worries and ideas with others we know, where we can collaborate and discuss common interests, and where we can contribute something back to the group and see its impact.

The urge for community is so strong that it has been encoded into the physical structure of the encampments, villages, towns, and cities that humans have built and inhabited for eons. Need to get a dose of community? Head to the campfire, the pub, the city square. There you can find a group of people to chat with, stand up to declaim your passion, tack something to the message post, discover that someone has a problem that you might help solve, create a society of the like-minded, or plan how you'll make your local mark and be remembered by your community.

That full, rich sense of membership in a community is deeply important and valuable to us. It can give us purpose and motivation, comfort and camaraderie. I would argue that civilization has been built from strong individual units of community, like societal bricks, and when those bricks begin to dissolve, the structure tumbles down. (But that's a story for another day...)

Until around the 1980's, there was exactly one way to get that full community experience: in person. Your community was made of the people you could touch.

The BBS was, I believe, the first technology in history that made it possible to get some form of true fully-formed community between physically separated people. It offered all the elements of community that had always been provided exclusively by local in-person groups, clubs, meetings, parties, pubs, and town squares.

(If you're interested, you can get a feel for what they were like here...)

If you knew what was up, the BBS wasn't just digital correspondence, it was the embryonic form of community in cyberspace, man. It was the stuff of sci-fi, where human stories could play out in a purely digital "place" between digital avatars of all description, controlled by people sitting in darkened rooms around the world. We joked about the cliches of being "jacked in", but it was undeniably cool.

An Accidental Prototype for Digital Community

The BBS I spent by far most of my time on was called (not kidding) Cyberverse.

Cyberverse had all of the typical BBS features, but also a special one: it had a MUD. I won't even explain what MUD stands for, but the basic idea is that it's like an MMORPG, but instead of graphics, it's 100% prose – text, like a first-person fantasy novel, describing what you're "looking at" and what you're "doing" (by typing). It was like ZORK but rather than a world frozen on a floppy disk for a single player, it was a shared virtual space for many players to explore and hang out in together.

The particular MUD running on Cyberverse was one built and written from scratch called Ishar.

Ishar's world translated all of the physical features of a real (that is, magical fantasy) medieval world into the digital. Its main town had a central plaza that people would pop into like the local pub, message boards with the latest topics of discussion and drama, and all sorts of places to not just battle creatures but generally hang out with other people. It included commands called "socials" – canned phrases conveying all the sorts of non-verbal messages we take for granted in reality, like a more literary version of emojis. Ishar was even was designed so that particularly creative players could add to the world itself from within.

With a players base measured in dozens, you became known (by your handle) for your deeds and personality and fell into one or another social group there as you played and conversed. A genuinely new player was a noteworthy event – How did you find us? Where are you from? Need any help getting started?

It was awesome. When I was 16, awkwardly exploring social connections and finding my place, Cyberverse and Ishar suddenly expanded the scope of my world, out of my local neighborhood and into the virtual. Despite being text in a terminal window, it immediately felt more full of potential than the physical forms of community I had access to. Ishar sunk into my brain instantly like a drug – as it did for others who also grew up in the disconnected world but were now eagerly exploring virtual ones.

I added to my friends a set of people scattered around greater Los Angeles and my modem stayed dialed in for most evenings and weekends as I hung out with them in a world built of hackishly enthusiastic fantasy prose. Once we had mostly played through the fantasy game that was the notional purpose of Ishar, we took up residence and stayed there anyway because it was simply a great "place" to be, accessible 24/7 from any computer terminal.

From time to time, there would be a "MUD meet" where people would get together physically to hang out. Those gatherings had a strange flatness; they seemed almost unnecessary when we were constantly hanging out virtually anyway, and out here in meatspace we didn't even have the magical powers and convenient tools that we were used to. Usually the meets ended with us finding computer terminals to sit down at, to find out what was going on in the real community in the virtual world.

We took it as a given that Ishar was a prototype of the future – a future of digital community. Of course new technology would eventually make all information available instantly at our fingertips, but that wasn't even the best part. Digital community was a concept that could expand to remake how the people around the world connected with each other, without restrictions.

As more people got online, we expected virtual worlds to grow and expand and become ever more rich and compelling. Of course local physical community would remain important, but we would each also find new communities within the vast electronic realm, like citizens of a metropolis of billions. Us Isharians were already inhabiting a virtual place that, even in crude and highly imperfect form, enabled real community without the hard limits of physical separation that had held since the beginning of time.

(Ishar still exists, by the way, connected to the internet. A community lives on there – with none of the original members, but retaining a continuity of community encoded in the digital world and its history and lore. It's a testament to the draw of community, even when the mechanism has become incredibly outdated.)

Opening of the Internet's Wild West

It was around this time that Cyberverse added a new thing for us users to do: the Internet.

Initially, "the Internet" was literally a menu option within the Cyberverse BBS interface, giving access to various internet protocols that did very specific things. In many ways, it still felt like a global expansion of the BBS experience and its various functions. Early internet software protocols provided individually useful concepts like sending mail (Email), serving collections of files (FTP, Archie, Gopher), live chat (talk, IRC), and posting of messages to topical groups (Usenet). After choosing a given protocol, you could type in the addresses of servers around the world, and see what they had to offer.

It was undoubtedly clunky, but back then it was hard to envision what the "right" way to make use of the internet was. The capability of the network itself was mind-blowing: instant, global communication, to be used however you see fit! But it was like giving steam-age engineers access to a nuclear power plant with bare electrical terminals mounted on the outside... what sort of thing even makes sense to build and connect to this immense power?

Nonetheless, despite the clunkiness (maybe even because of it for a tech-head), the sudden extension of reach was heady for us Cyberverse users. Now our bubble wasn't just weirdos around Los Angeles, it was weirdos (and a bunch of universities) around the world. Places on the other side of the planet ceased to be abstractions seen on the TV news, but places holding real people we could talk to and trade files with, instantly.

Even at this point in the mid-90s, there were millions of people online from distant places, but it still felt a bit like a small community. To start, there were still a lot of natural commonalities between the kinds of people who managed to get online then. And, like the lists of BBS phone numbers that got around, you managed to find groups of people on various usenet groups, mailing lists, and IRC channels where you could get that feeling of membership in a community that wasn't too big to get to know you. The interface sometimes felt a little disappointing to us Ishar users, but the global scope was worth the tradeoff.

So in 1995 or so, it still seemed to everyone that virtual community would be a big part of what we would do with the raw capability the internet gave us. A modem company even called themselves Global Village, echoing the vibe of the times: we were on the verge of a predicted transition to a more personal world! The more wide-eyed folks imagined that, like in cyberpunk novels, everything could happen within an immersive simulated 3D world where you would interact with people, systems, and information "physically". A few tenuous attempts were even made in that direction, like GopherVR which attempted to represent a network of servers and documents in a 3D environment.

The Internet Becomes the Web

Despite the raw capabilities of the early internet protocols, ease of use is always king. A proliferation of separate protocols, each with their own unique software to learn, was confusing and burdensome (and it was vastly premature to try for a VR-style physical UI paradigm – 30 years later it still doesn't quite make sense). The way forward was convenience, and that meant putting everything into a window with a simple, unified point-and-click interface.

The protocol that figured it out was HTTP – the basis of the World Wide Web – with its paradigm of a "browser" and living documents that could be connected to each other in a web of information.

Across 30 years, HTTP has become the primary unified protocol behind the huge variety of websites, services, and apps that we think of as "the internet". It works so well in large part because the "webpage" concept is so flexible. It isn't like the old protocols designed for a very specific and narrow function. HTTP makes it simple to make generic requests for data, making it easy for a developer to adapt it to their own purposes with their own user interfaces. Initially the user interfaces were simple HTML pages, but the underlying protocol was easily extended almost endlessly.

So when the Web came along, the energy drained from the proliferation of specialized protocols. The protocol question was now settled, and the real exploration of how the internet would remake the world got started in earnest. We headed into successive waves of exploration and development: the dot-com gold rush to put everything on the web, the user content generation push of Web 2.0, the rise of smartphones and the app-ification of everything, and finally the dominance of pervasive social media.

Finding my global community would be on the web, but it didn’t go how I expected.

Click here to go on to part 2, where I pick up the story of the web taking over everything, social media swallowing how we socialize online, and how an illusion of community is actually pushing us apart.

✍️ Articles on The Foolish Generalist are always written without AI. Here’s why.

Somehow you've landed on this blog, despite me being neither famous nor especially successful. Weird.

What's this about?

Being a generalist here in the mid-21st century is a profoundly foolish thing to do. The name of the game is to specialize, maximize and monetize.

Be that as it may, thinking like a generalist is a powerful thing – especially in an incredibly complex and rapidly changing world. It means to step back, try to understand the similarities and connections between seemingly different things, and work to see the world as a whole in which the most interesting and valuable insights don't fit into a neat category.

Anyway, this is all just to say that I find a lot of stuff interesting, and I want to share what I find with other folks.

Who's this for?

First and foremost, it's for the interesting people I've met on my journey. If you're here, there's a good chance that's you. I'd like to create a little bit of community between myself and you folks (which, incidentally, is one of the topics I want to write about). Maybe you’d even like to write something here.

So I'm doing things a little differently than the typical substack.

Most importantly:

If I know you, please reach out and I'll make you a subscriber for free!

Mostly this just lets me keep the comments and chat high quality by enabling them only for subscribers. I'll be thrilled if you take a moment to make a comment, or share what you've been thinking about in the chat.

Did you just happened to stumble here and are curious? Well, I'm not going to try to convince you that Ia subscription will deliver good value for money, but I'm not going to stop you either. I mostly aim to make what I write public, but I may share early drafts with subscribers first for feedback.

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