Reporter Michael Lewis is the luckiest man to cover unlucky financial events.

In the days after FTX’s collapse, entertainment newsletter The Ankler reported that Lewis had been spending time with FTX Founder Sam Bankman-Fried for an upcoming book. 

Even if you don’t recognize his name, you know Michael Lewis. 

He wrote the book that became The Big Short starring Brad Pitt, Ryan Gosling, Christian Bale and Steve Carrell.  The Big Short tells the story of another massive financial collapse, of how the US mortgage industry became a massive speculative bubble that almost took down the entire global economy when it collapsed.

If you ask the typical American about crypto, the first name they will know is SBF. 

If you ask the typical American about mortgage backed securities, they will know about the 2008 financial crisis.  

So if you tell our typical American that you want to marry crypto and its SBF-laden craziness with real estate backed securities like those that touched off the Great Recession, they are liable to think you are a scammer or a nihilist.

When I first met Domingo and the Homebase team, that was my reaction, too.

But in the year that I’ve known them, I’ve gone from hostile to skeptical to true believer. Crypto is going to come for your home. 

And here’s the really crazy thing – you’re going to be glad that it did.

DeFi Today

When the crypto bubble burst (repeatedly) in 2022, commentators were quick to point out that its impacts seemed to be limited to the crypto economy. 

This was good news for the primary economy. But it also demonstrated that the crypto economy remained circular. A digital financial system for digital goods, or to be less charitable, made up money for made up assets. 

That’s not entirely fair – the stablecoin sector is worth in excess of $120B. But those stablecoins, though they represent real world value, are mostly chasing digital assets. 

In a report last month, BCG sized the value of “Real World Assets” on-chain at $310B. That represents roughly 20% of the entire crypto-space (not bad) or .2% the size of the 120T global securities market (not great).

All of this is to say – crypto has a long way to go if it is going to make a dent in the world of traditional finance. In An Unreal Primer on Digital Assets, Teej Ragsdale, Jack Chong and Mukund Venkatakrishnan argue that DeFi will first find product market fit on the long-tail of speculative assets that are not served by additional securities standards. That includes everything from digitally native products like collateralized-NFT protocols to developing markets’ debt to investments in DAOs or DeFi protocols.

Why?  Because it is easier for a new technology to integrate and provide a standard for net new assets than it is to convince existing products that are humming along to switch to a new, less-proven system.

Real estate, in many ways, is the king of assets.  US Mortgage backed securities alone account for $12 Trillion in assets. They are also, as 2008 taught us, one of the most sophisticated and therefore dangerous financial markets in the world. 

Securitization standards were created for loans in the United States in the early 1990s, and those standards powered a revolution – enabling cheaper loans for homes, for cars, for businesses, for. Everything. If you’re an institutional investor in real estate, today’s market functions well.  

So why would the real estate market move on-chain?  As with everything in life, the answer comes down to Removing Friction and Increasing Value. 

Removing Friction

Imagine that you are moving to a new town and would like to buy a home. Today that process looks a bit like this:

1. Finding a real estate agent. Agents are important because they have access to MLS (multiple listing service) which they use to look for homes that may not be on the market yet.

2. Scouring Zillow/Realtor.com for homes. As you find homes you like, you have to contact the sellers agent to setup a walkthrough of the house, either digitally or physically.

3. Making an offer. Once you find a home you like, you work through your agent to help you prepare and submit a buy offer. The seller’s agent is the one that receives the offer, shares it with the homeowner, who either will accept, reject, or counter your offer.

4. Negotiating with the seller. If the seller counters your offer, you and your agent will negotiate the terms of the sale until you reach an agreement.

5. Home Due Diligence. This typically involves getting a home inspection and checking liens on the property through a title company to make sure the property is in good condition.

6. Qualifying for a mortgage. This is typically the longest and most important step in the process. Most homes are financed via mortgages, where an owner puts a 20% down payment on the home and takes out the remaining 80% via bank loan. This process is easily the longest, requires weeks of bank due diligence to check your credit score, conduct an appraisal on the house to ultimately decide if you qualify for the loan.

7. Closing the sale. Once you’ve conducted your due diligence, you’re happy with the home, and you’ve secured your mortgage, you’ll sign relevant closing documents (such as deed of the home) to transfer ownership of the home and finalize the sale.

In a bit more detail that looks like this:

That’s a lot of friction.

Now - folks are still going to want to research and tour houses, so a world of “one-click-buy” homes is probably out of the question. But consider all the other frictions that happen once you decide to buy.

There’s asynchronous negotiation, a long mortgage process, a long diligence and verification process, and finally a long closing process. 

What if that could be handled instantly?

Imagine this world:

Home Title on Chain. The house deed could be placed entirely on-chain. This would eliminate the need for much of the manual work of finding, exchanging and custodying the home title. If that title included an ability for inspectors to record the results of diligence on-chain, then validators could inspect and provide diligence in advance of sale that would be certified for any potential bidders.

Mortgage. Today, mortgages are originated by banks, sold to servicers and eventually packaged as securities. But, imagine instead if a buyer could log-in to a platform with their digital wallet. That wallet could be connected to their existing financial credentials, importing their credit history, their income and any other financial data. Automated agents could then issue smart contract offers for a mortgage that the purchaser could accept or decline immediately. Once accepted, that smart contract would be in effect, as well as be instantly tokenizable.

Tokenization. Today, securitizing mortgages is a long and opaque process available only to institutional investors. Tomorrow, every mortgage could be represented by a transparent contract on-chain that could be subdivided and sold to individual retail investors via standard fungible tokens. This approach would allow massive pools of investors, and new capital, access to the market. It would allow individuals to own and invest in real estate according to their needs. It would allow owners to sell portions of their home, or use portions as collateral.

All three of these changes would work to reduce friction in the buying process.  That convenience is nice, in and of itself, but its second order potential is mind boggling.

After a period of low rates, interest rates rose this year. A 30-year mortgage for individuals with excellent credit is currently pegged at ~6.2%. This market price reflects both the demand of mortgage holders and the supply of capital via investors. 

By enabling tokenization, and introducing new forms of securitization, on-chain real estate will dramatically increase the amount of available capital, and the number of individuals and investors willing to furnish capital for real estate. The result could be a second revolution in financing, equivalent to the first securitization rush of the 1990s, that would dramatically lower rates for home buyers. Not to mention that enabling homebuyers to directly sell tokens representing home equity would provide yet another path toward making homes more affordable.

And that’s not all.  That’s just making the existing market more efficient.  Tokenization also has an exciting new possibility.  It can create entirely new markets.

Creating Value

Tokenization is not just about moving assets onto the blockchain. Because tokens are not just deeds, but are, themselves programmable, they can enable new forms of ownership that are not currently possible.  Here’s a few new types of ownership that could become reality:

Splitting the Bundle.  When you buy a home today, we say that you have acquired a bundle of rights. Those rights include the Right of Title (the right to a deed that says you own the house), the Right of Disposition (the right to sell the house), the Right of Enjoyment (the right to use the house as you see fit), the Right of Exclusion (the right to keep people off your property) and the Right of Control (the right to build on or alter the property).  Because homeownership is already so complex, those rights have always been bundled together. But in a world of tokenized ownership, it’s easy to imagine separating them and selling the different rights as distinct tokens.  A group might purchase and tokenize a house, then sell tokens that enable individuals to purchase shares of the Right to Enjoyment (creating a mini timeshare), but retaining the rights of Disposition, the Rights of Control and the Right of Title to themselves. Alternatively, they might auction off the Rights of Control and the Right of Enjoyment, but keep the other rights. Tokenization enables flexible ownership. That’s a totally new behavior.

Mutual Investment. Historically, the government has promoted homeownership both as a savings vehicle, and because owning a property invests individuals in their community. Imagine if tokenization could make that literal. When you purchase a home, you could purchase 90% of your home, and also hold a token representing a literal investment in an index fund of homes in your neighborhood. This type of arrangement encourages neighbors to work together to promote the welfare of the neighborhood as what is good for one of them becomes good for all of them.  

Multigenerational Ownership.  It is common, especially in poorer communities, for multiple households to live in a house. But today, it is difficult to enable multiple people from multiple generations to share legal rights over a home. Tokenization could make this process trivial, allowing each generation to own shares of a home, and allowing them to easily reconfigure these rights as a family grows and changes over time.

As a matter of principle, I like to think of myself as a “pragmatism maxi.”  I tend to avoid religious debates over which chain is the one-chain to rule them all. But I think, when it comes to this kind of a use case, the argument for Solana as the obvious L1 for real estate is pretty clear.  Securities innovation happens when the barriers to experimentation are low.  High gas fees, high friction to bridge assets across multiple chains – all of these are frictions. The ideal is clearly a simple, fast and cheap L1 with proven liquidity and battle tested infrastructure.

Of course, it might seem like any blockchain would dramatically reduce friction over the existing process. And that’s true. But there are a whole class of applications that become possible when friction moves from “lower” to “zero.”  

There’s a world where paying your monthly rent might directly entitle you to portions of equity – allowing renters to become buyers for under a cent of gas fees. 

There’s a world where home securities can be fractionalized and bundled by any possible heuristic at the drop of a hat.  That requires the ability to mint thousands of NFTs representing shares in fractions of a second – Solana’s compressed NFTs allow that for a fraction of the price of mass-minting. 

There’s even a world where owning shares of a property directly entitles you to buy other shares – for example, a primary buyer having the right to buy tokens back directly. That type of control is possible through code written in executable NFTs, a unique standard to Solana.

These technologies might be possible on other blockchains, but today … well, there’s a clear reason that HomebaseDAO and other Real World Assets are building on the Solana ecosystem. 

Systemic Questions

Crypto has a way of incentivizing speculation. And, of course, every new form of financial innovation that I have listed above has a potential for abuse. 

So why should we allow any of these types of new financial schemes in our housing industry?

The answer, ironically, is plain when you watch The Big Short.  

MICHAEL BURRY: I need you to get me the top 20 selling mortgage bonds. 

YOUNG ANALYST: So you want to know what the top 20 selling mortgage bonds are? MICHAEL BURRY: No. I want to know what mortgages are in each one.

YOUNG ANALYST: Wait, aren’t those bonds made up of thousands and thousands of mortgages? 

MICHAEL BURRY Yes. 

It is the utter opacity of the current real estate market that made bubbles so prominent. When everyone believes that a product is safe, and researching it is difficult, it is shockingly easy for risks to metastasize to systemic proportions.

But, if instead, all of the data about mortgages, all of the terms, all of the financial information was open and readily available on-chain, if all of that data was viewable on a block explorer, if it was analyzable with artificial intelligence programs, then we would expect that investors could bet for and against mortgages to ensure that the risk was priced appropriately.  Information asymmetries create bubbles. Transparency creates efficient markets.

And transparency in a world where LLMs can quickly answer any question about any particular property or any particular security … Well, that just might change everything.

Furthermore, in the event of bubbles or housing recessions, the government’s path toward intervening would become far more clear. One of the most potent critiques of the Bush and Obama administration’s response to the 2008 financial crisis was that the government bailed out banks rather than homeowners.  This is, of course, a simplification. The government bailed out banks to keep the markets operating to protect the interests of homeowners.

But a world with transparent, liquid markets could be protected directly. Rather than investing through banks, the government could pump investments directly into the market – protecting asset prices, purchasing toxic assets, and ensuring that the market operates smoothly. And it could do so without privileging the interests of large institutions over retail traders.

That might prevent Michael Lewis’s next big scoop.

And frankly, a world without more blockbuster worthy financial scandals is one that we should aspire to create. Even if it means less time spent with Ryan Gosling and Brad Pitt.

Working in the crypto industry is sometimes embarrassing.

In a time when artificial intelligence is being used to cure diseases and usher in an age of abundance, it seems like a waste of our talent and energies to focus on selling ape pictures.

But there are also moments – and they can be fleeting – when I’m proud to say that I work in crypto.  There are moments where the promise of this technology and its ability to aid both human liberation and human coordination feels urgent, feels righteous.

Holding space for both of these realities is exhausting.

Because while GPT4 changes workflows on a daily basis, many of the promised benefits of crypto - expanding financial inclusion, funding democratic political movements and enabling new types of communities – are often more theoretical than they are real.

But that’s not entirely true. Because these benefits of crypto are appearing in real life. They just are appearing outside of the United States. And that’s a problem for the work we do here in advancing the underlying technology.

It’s a problem because it allows crypto critics to ignore the benefits of crypto technology. And it’s a problem because it allows crypto ideologues to pretend that blockchains accomplish more than they actually do.

But when you look to markets where crypto is having a real and important impact, you come away with a nuanced story. You see a technology that is solving real problems. You see a technology that can have a massive impact.

But you also see a technology that is far, far from ready for primetime. So, no, we probably shouldn’t be hoping for Bitcoin to replace the US Dollar anytime soon.

Still if you want a glimpse of what a crypto future might look like, you can join me for a quick trip to Nigeria.

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Welcome to Nigeria

The first thing to know is that Nigeria has a lot going for it.  Nigeria has both the largest economy ($376B GDP) and largest population (213M people) in all of Africa.  

Nigeria’s economy is diverse.  While its largest export is oil, that industry accounts for only ~6% of GDP. Instead, farming and the service industry are the largest sources of income. It also has a strong creative industry – Nigeria’s film industry produces more films than Hollywood, and its tech sector has produced some winning fintech companies including Paystack (a 200M 2020 Stripe acquisition).  The large Nigerian diaspora also sends home massive amounts of money via remittances – almost contributing as much to GDP as the oil industry.

But those strengths should not obscure the very real crises – some natural, some manufactured through mismanagement– facing the Nigerian economy.

Nigeria’s problems started because it remains a massive net importer.  As a net importer, Nigeria’s Central Bank wants to keep the Naira (Nigeria’s currency) strong.  They have done this by enforcing an artificially high exchange rate.  In market conditions, the US Dollar is valued at roughly 760 Naira.  But the Central Bank of Nigeria forces banks and foreign governments to value 1 USD at 460 Naira. That means that the Naira’s government enforced exchange rate is 63% stronger than its actual true value.

Why would Nigeria do this?

Well, two reasons.

First, a strong currency is considered essential to attracting the kind of foreign investment that Nigeria needs to improve its agricultural practices and its manufacturing base. 

Second, a strong currency means that Nigerians can more cheaply purchase things from abroad. If the Dollar suddenly became worth 5 times as many Euros, we would all be buying a lot of things from Europe. Since Nigeria is a net-importer, this is a pretty important benefit for raising living standards.

But making importing cheaper is also dangerous for Nigeria’s domestic industries.  Because when things are cheap to import, there’s not much reason to buy domestic products. Hence why we don’t make many TVs in America anymore.

To support their domestic industries, Nigeria has implemented strict controls on imports. Here’s the US Department of Commerce describing those restrictions:

“Nigeria has an effective duty (tariff, levy, excise, and value added tax (VAT) where applicable) of 50% or more on over 80 tariff lines.  These include about 35 tariff lines whose effective duties exceed the 70% limit set by ECOWAS. Most of these items are luxury goods such as yachts, motorboats, and other vehicles for pleasure (75%), as well as on alcohol (75% to 95%) and tobacco products (95%). In addition, Nigeria places high effective duty rates on imports into strategic sectors to boost the competitiveness of the local industries. In agriculture, wheat (85%), sugar (75%), rice (70%), and tomato paste (50%). In the mining sector, salt (70%) and cement (55%).”

The results of these policies — an overvalued currency and strong import controls— is tragic and predictable. Most of Nigeria’s economy has moved into smuggling and underground activity to avoid government enforcement.

Nigeria has one of the largest black markets in the world. That black market does not just cater to drugs or contraband. It represents, according to the ILO in 2018, over 50% of Nigeria’s GDP and 93% of all employment. 

That’s insanity.  Nine out of every ten people that work in Nigeria are employed under-the-table.

On the one hand, that is a clear sign of economic mismanagement.  On the other hand, it’s pretty hard to correctly manage an economy when 90% of it is out of government reach.

How do regulators improve an economy when 90% of labor is not taxable, and 50% of the economy can safely ignore your monetary policy?

They can’t. They also can’t stand-up the basics of a functioning financial system.

That’s why only 3% of Nigerians have access to a credit card.  That’s why only 45% of Nigerians have a bank account.  That’s why, despite government intervention, inflation regularly exceeds 20% per year.

The government has taken big steps to try to improve its financial system. They have tried giant new initiatives to bring the black market out of the shadows. But those efforts have either been ignored or made things worse.

In 2021, the government introduced the eNaira (the world’s first large-scale Central Bank Digital Currency – real money on the blockchain) to increase financial inclusion.  Less than .5% of Nigerians adopted it.

In 2022, the government announced a new design for Naira notes to force Nigerians to bring in and exchange old currency at banks. They hoped this would force Nigerians to participate in the legitimate financial system. That caused a cash crunch and general panic. It has done an estimated $43B in damage to the economy so far this year.

All of this is to say: fiat currency is badly broken in Nigeria.

If only the people of Nigeria had an alternative to their broken fiat system.  

If only there were some kind of decentralized currency that could bypass unhelpful and ineffective policies that, in turn, would force the Central Bank to behave more responsibly.

If only there were a way for Nigerians to access currencies like the US Dollar or Euro that are more likely to keep their value so that they could save, build capital, invest and create a functioning financial system.

If only, the people of Nigeria had… well… I guess… crypto?

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The Bull Case

In our ideal world, the people of Nigeria would have a functional financial system with the following properties:

• A stable store-of-value currency that attracts investment and encourages saving.

• A financial technology stack that enables peer-to-peer transactions with both businesses and via remittances for low or zero cost.

• A set of market-appropriate financial services including credit products and investment products.

Clearly, Bitcoin and stablecoins are more attractive than the existing system.

This comparison isn’t theoretical.  It’s one that Nigerians are making every day.  And they are voting with their wallets.

Nigeria has the highest rate of per capita ownership of crypto (17-24%) anywhere in the world.  That’s incredible when you consider that only 51% of Nigerians have internet access. Put another way, 35-48% of all Nigerians with internet access use crypto. Only 40% of Americans with internet access have an Instagram account. 

That’s a lot of crypto owners.

But owning cryptocurrency does not mean that you are using it. In fact, in our world owning cryptocurrency just means that you are hoping someone else will buy it for more money than you did.  So are Nigerians actually doing anything with their currency?

Yes.

They are using it to save. When your currency is losing 20% of its value per year, and Bitcoin seems to gain value (albeit in a volatile way) while stablecoins seem to hold their value, crypto savings is safer than cash savings.

The Nigerian Diaspora is using it for remittances – the cross-border payment of income to friends and family back in Nigeria. That’s a big deal. Remittances in Nigeria account for as much GDP as their oil exports. And remittances are expensive. 

In 2020, Nigerians spent $2.94B in bank fees to send $34B of remittances to family back home, according to the World Bank.  In 2021, crypto remittances began to catch fire. In one survey of Americans, 23% of remittances sent from the United States (to any country) used cryptocurrency.  In 2022, when “official remittances” via banks dropped by ~$6B, most experts concluded that the $6B in remittances had not disappeared, it had just been sent via crypto instead.

Back home in Nigeria, it is also being used for daily transactions. Crypto transactions in Nigeria are 10x more likely to be used for actual peer-to-peer spending than they are in the United States. In H1 2022, Paxful, the largest platform at the time, reported that Nigerians transaction volume was $400M. That equated to 60% of crypto trading volume in the country ($700M). Daily transactions in crypto were nearly as common as crypto investing.

Crypto has not, however, created a functioning alternative banking system for most Nigerians. But there are early signs of promising, localized solutions that could offer credit and investment products to the 55% of the country that lacks a bank account.

Small peer savings groups, often called esusu, allow individuals in lower-income communities in Nigeria to access capital for opening businesses.  These groups allow members to pay part of their income into a shared pool for the opportunity to take turns accessing the shared pool and have been quick to adopt stablecoins as a way to ensure that members who take later-turns are not receiving less value due to inflation. 

And technical innovators are rushing to bring financial services via blockchain to the broader Nigerian unbanked. Tingo Group has partnered with the MELD protocol to enable small (~$20 USD) loans to farmers in their network, though data on that partnership has been limited thus far.

The Bear

That’s the promise of a crypto Nigeria.  But it’s never all good news.

Stablecoins, for example, are a key element of any future decentralized financial system operating in Nigeria. But many stablecoins are not… exactly… stable. Last May, for example, Terra was one of the most popular stablecoin options in Nigeria.  When it collapsed, it not only wiped out the speculative bets of American crypto bros, but the savings of the Nigerians who trusted it. Today, the most popular cryptocurrency in Nigeria is Tether.  And Tether is often called the ticking-time-bomb at the heart of crypto markets.

Furthermore, adoption, while surging in relative terms, remains low in absolute terms.  And Nigerians, in the midst of all of their other economic woes, now have to contend with choosing among 7 different currencies as their unit-of-exchange (USD, Tether, Bitcoin, old Naira (valued at official or parallel market rates) or new Naira (valued at official or parallel market rates)).  

The role of currency as a simple, shared mechanism for facilitating exchange is severely undermined in a world where multiple currencies are constantly shifting value against each other.

It’s also worth acknowledging that undermining government policies – even when they are incompetently executed – is not exactly an ideal outcome of cryptocurrency (unless you’re really an anarchocapitalist…). In Nigeria, the parallel market for blackmarket currency and cryptocurrency undermines the ability of an elected government to tax, to regulate, and to use monetary policy to achieve shared goals for the Nigerian people. 

At the same time, the presence of these parallel markets makes it far easier for opponents of Nigeria’s liberal government, including the dangerous terrorist group Boko Haram, to finance its operations.  To be very clear, money laundering and terrorist financing existed in the black market long before Satoshi implemented a blockchain.  But the continued growth of unregulated financial systems (even those where the government can view transactions, if not block them) makes the task of criminals easier. It might even make us long for the day where the most embarrassing thing about cryptocurrency was speculation on Ape JPEGs or literally anything Sam Bankman-Fried says or does.

Because here’s the thing – the promise of this technology is, in fact, transformative.  The open question is whether we’re transforming the world into a place that’s better than the world we have today. If Nigeria is any indication, we still have a long way to go.

The Power of Coffee

My girlfriend – let’s call her Taylor because she likes her privacy – long-ago disclosed that heading into our first date she was very worried that I would subject her to a jeremiad on the benefits of decentralized finance.

I had made the mistake of mentioning in our early texting that I was into crypto.

She– like most of my family, friends and fellow human beings– is not a crypto person.

But she is a coffee person.

So - partially as a joke, partially because she loves me and partially because she wanted to better understand my occasional rants about NFTs, she signed up for Starbucks Odyssey in December.  

Six weeks ago, she joined ~30,000 other Starbucks/NFT fans who were admitted into the Starbucks Odyssey beta.  

According to Starbucks, Odyssey is a “Revolutionary Web3 Experience” built in partnership with Polygon that will, and I quote, “ allow our members to access experiences and ownership that was not possible before (while) [...] transcending the foundational benefits that our Starbucks Rewards members have come to love.”  

So that sounds good.

On the other hand, according to Gizmodo (and most of the tech press), Odyssey is a “dumbass NFT program” that, rather than reward customers, gives them the opportunity to spend more money at Starbucks on things they don’t need in the Metaverse.

So that sounds bad.

Two months in, Taylor’s opinion has ended up somewhere in between.  

According to her, Odyssey is strangely addictive, surprisingly lucrative and an entertaining glimpse into NFT culture. And I have to say, while I was skeptical about a corporate NFT cash grab, I’m coming around to her point of view.

Odyssey is a tangible manifestation of the mechanics that make Web3 exciting.  For many people, including Taylor, it’s their first real exposure to this world. And these mechanics are what Taylor has found engaging. So engaging, in fact, that it’s something we now discuss almost daily.

If Web3 is going to realize its promise of democratizing data and economic tools, it will not do so on the backs of ideologues.

 Balaji can keep screaming about the end of the USD.  Pixelated punks can keep reminding you that all fiat currency is a Ponzi scheme.  But if web3 is going to win, if it is going to empower the many to own and operate digital economies, then it will do so on the backs of established brand partnerships.

That’s why it’s important to pay attention to the Starbucks of the world, who (along with Adidas, Square-Enix, Nike and Mercedes’) have been piloting their own NFT projects. These brands capture the imagination and participation of skeptics.  These are the experiences that can tangibly demonstrate the benefits of a user-owned digital economy.

Starbucks’ program is an update of the age-old loyalty program.  To prove its merit, Odyssey needs to do more than win on the ideology of a “decentralized web.”  It needs to win on use-cases.  

But to understand what the use-cases of a loyalty program are, and where Odyssey succeeds, we need to first take a brief tour through the history of the programs it is trying to replace. 

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A Brief History of Loyalty

In the United States, the modern loyalty program was a response to inflation.

Seriously.

During periods of inflation, people hoarded cash. This hit shopkeepers especially hard. People were not using currency to buy, and shopkeepers did not have a means to give change. So to stimulate demand they started offering their own coins as “gift certificate”-changes that could be spent at the store.

Yes, American shopkeepers seemingly invented the original money printer. But soon after they did, banks realized this was a convenient way to invent currency out-of-the-ether. So in the 1850s, the US government passed laws banning the minting of private currencies.

This limited shopkeepers’ ability to call their loyalty tokens “money,” but it did not stop the innovative among them from continuing to incentivize repeat customers.

BT Babbit, a soap manufacturer, started the “box top” system.  He told customers to cut out “trade marks'' from their boxes which could then be redeemed for prizes from his company’s prize-catalog.  

In 1912, his company went even further – they allowed their customers to redeem their box tops for profit shares, following a model of “co-op tokens” that began in 19th Century England.

For most of the 20th Century, box-tops and other kinds of customer rewards were limited to the grocery store and other household goods. But that changed when the US government deregulated airlines in the late-1970s. For the first time, airlines had to compete freely over every route. Each airline needed a way to differentiate themselves and to keep their customers flying only with them. 

So in 1981, American Airlines launched a first-of-its-kind Frequent Flier program. AA’s system rewarded customers for “miles” flown. It then allowed them to spend these miles either on repeat travel or on status perks – like first class upgrades. This system of a private reward currency was a step backward to the time of shopkeeper currencies. But it had dramatic results for American and inspired instant copycats. Within a week of launching, United launched a copycat program. By the end of the decade, every airline in America had its own frequent flier program.

And for good reason.  Loyalty programs work.

In a 2019 study of loyalty programs across industries, Malika Chaudhuri found that “firms that introduced an LP (loyalty program) in our sample experienced an average increase of 7% in total sales and 6% in gross profits in the first year following the introduction compared to a matched set of control firms. Three years after the introduction of the LP, firms experienced an 11% increase in total sales and 6% increase in gross profits relative to the same set of control firms.”

Yet, if loyalty programs have a drawback it’s that they are one-dimensional. You spend money, you get rewards. But spending money is not the only thing that brands, today, want from their customers. They want them to become emotionally invested in the company. They want them to become advocates. They don’t just want customers, they want champions.

Which brings us back to coffee. 

Setting Sail on the Odyssey

At first glance, Starbucks Odyssey seems like any other loyalty program – no crypto required. 

Buy Starbucks products, get free stuff.

But that’s not the whole story.

Starbucks Odyssey is not just a loyalty program. It’s a corporate-branded open world game. In an open-world game, a player does not need to follow a linear sequence of story events or actions, but is instead free to pursue any challenges or quests that appeal to them. 

As a result, no two players are likely to have the same experience – a critical point that makes Odyssey work.

You see, Starbucks offers a variety of Journeys that users can choose to follow:

Take, for instance, the “Doing Good” Journey. To complete this Journey, you need to visit a Starbucks and buy drinks in your own refillable mug three times, order two non-dairy drinks and complete a lesson about Starbucks sustainability efforts.

When you successfully complete one of these quests, you receive an NFT Stamp from Starbucks. Each Journey offers a different NFT with different benefits. And each NFT might open up a new set of Journeys only available to its holders.

This means that each player will likely earn different NFTs.  You may earn NFTs that have benefits you really like. You might earn ones that reward you in ways you couldn’t care less about. That’s what makes this system work. 

Because in any system where some players win rewards that other people value more than they do, there’s an opportunity for trade. Most traditional loyalty programs prevent you from selling Miles or other benefits. But where Starbucks Odyssey differs from these programs is that you are not only allowed to sell your rewards, you’re encouraged to do so.

Here is the key innovation:  Starbucks has integrated an open crypto economy to supercharge its (let’s be honest, kind-of-boring customer loyalty game) with an NFT Flywheel.

That flywheel has three components.  It works like this:

Exclusivity.  Today there are ~30,000 members participating in Starbucks Odyssey (compared to 29M in the traditional rewards program). The limited nature of the beta inherently creates a novelty and a sense of being in on-the-ground early testing something new. 

Economy.  Starbucks stamps have demonstrable scarcity as a limited number of NFTs are minted for each Journey. Because the items are NFTs, they can be freely traded on any NFT marketplace for cash. So you are not just playing to earn rewards, you are playing to earn something that can make you money.  We’ll return to that in a moment.

Community. In a traditional loyalty program, like say American Airlines Frequent Fliers, I have no reason to interact with other frequent fliers and if I have to interact with AA, it’s usually because something has gone wrong. But Odyssey changes this and necessitates the development of an incentive-aligned community. Announcements about benefits and upcoming releases are made in the Odyssey Discord. 

Players congregate there to ask each other questions about completing quests, to seek out NFT trading partners or to give the moderators feedback. The pseudonymity of Discord makes the space comfortable for strangers to interact, while the tight-grip of moderators keeps things from spiraling.

More importantly, this community works because of the economy attached to their Stamps. Each member has an incentive to work together to promote Starbucks Odyssey. After all, the more people that are excited about Stamps and Starbucks benefits, the more demand there will be for the Stamps that they own and sell on Nifty Gateway and Opensea. Thus even in a world where players are trying to compete to earn Stamps, a positive sum ethos reigns.

To see how this works, in practice, we can look at the experience Taylor and I had with Starbucks’ Sirens.  Sirens were Odyssey’s first paid drop.  For $100-a-piece, 2,000 members of the program could purchase a Starbucks Siren NFT.  What were the benefits of this NFT? Honestly, unknown. No, seriously. Starbucks plans to announce the benefits to the community tomorrow – one month after their first release.

So naturally, we bought two. Taylor’s parents asked her, “Is this really how you spend your money?” 

But we weren’t too concerned.  Because what happened next was eminently predictable.

First, people were pissed in the Discord that they were not able to purchase on.  

(A note for crypto people: real-world humans care not-at-all about your entitlement or your “right” to get things from a free program you happened to be lucky enough to try. You’re making the rest of us look bad.)

And their disappointment helped build a story online that got picked up by media outlets.

Which, of course, drove demand even higher.

The secondary market for Sirens began to surge.  People who couldn’t buy these stamps – because they were not in the beta, or because they were unlucky in the release – started paying multiples of their original value. 

Our net-profit on two pieces of Starbucks branded digital art was $1,200.

So, if nothing else, this program may help us buy a Peloton for our new apartment. 

Now, this is the type of thing that makes most people roll their eyes.  

But I think these profits are actually the thing we need to pay attention to here.  Because making money gets people excited. And it kicks off this virtuous flywheel. **

Exclusivity creates memetic demand. High prices attract speculators and more attention. The community proliferates this attention. This increases the sense of exclusivity and again drives up demand which raises prices… 

Is it all a bit silly? Yes. 

But, frankly, what non-essential luxury goods aren't somewhat silly?

We buy things that make us happy. And if we have something that will make someone else happier, we exchange it for the things that make us happy. That’s how economies are supposed to work.

Now, there’s a fair criticism to be leveled here that those experiences should just go to the people who love Starbucks the most, no speculation attached. I’m sympathetic to that. But that isn’t actually Starbucks’ goal here.  Starbucks is not in the business of showering super-fans with free-love. They are in the business of selling coffee and building their brand. They give away rewards to help achieve that end.

And this system achieves that end with powerful efficiency that maximizes everyone’s well-being. Starbucks-lovers can buy their experiences. Starbucks gets their brand out there. And customers who just want cash back, can earn that cash by playing.

This is the speculative engine that works for native NFT communities.  And it also, seemingly, works for Starbucks.  I can’t say I am confident that this will scale.  When everyone can buy NFT stamps, I am not convinced that the market for Starbucks NFTs will be incredibly liquid, or as likely to result in big cash rewards.  

After all, if you’re not in early, you’re just the person left holding the bag at the end.  That’s just a reality of the NFT game.  

But as for today, we’re just excited to be part of the Coffee Vanguard. 

As I write this, I’m drinking my Starbucks Drip Coffee in a Refillable Mug (Completing two journeys in one!) to help us qualify for a stamp-gated NFT drop.  Taylor just texted me to confirm I completed today’s Journey for us. 

We have coffee to drink and a Peloton to buy.

So for today, at least, we’re both crypto people. 

Brands Are Toasted

What is a brand?

In the pilot episode of Mad Men, a young advertising executive named Don Draper sits silently in a meeting with a cigarette company.

The FDA has just told cigarette companies they cannot advertise that their cigarettes are healthy. So the companies need a new pitch to sell their product. And since their “filtered tips” were the primary way they differentiated their product before, the companies all need a new story to sell. The only problem: every cigarette is functionally identical. So what do you say to differentiate Marlboro from Lucky Strike?

Finally, Don looks up and says to the meeting: “This is the greatest advertising opportunity since the invention of cereal. We have six identical companies making six identical products. We can say anything we want."

This might seem cynical, but what’s more remarkable than Don’s glibness about selling snake oil is that this is really how brands were invented.

After all: what is a brand?

On one level, a brand is just a way to differentiate one product from another. It’s a name on a box. It’s a logo on a website. It’s an ad campaign that tells you why to buy this shoe rather than that one.

But on another level, a brand is modern alchemy. By telling a story about a company, about its products, about who buys it - you can transform a commoditized good into something extremely valuable. You don’t buy Nike sneakers because you know, for a fact, that they are a better quality shoe than a generic brand you can buy online. You don’t buy Apple AirPods because they are the best headphone on the market. 

You buy them because Apple and Nike have told a story that makes their product uniquely valuable compared to competitors. 

They have turned a common element into gold.

This is a distinctly modern phenomenon.

In the mid-1800s, the early consumer packaged goods companies got their start selling goods like soap. Their advantage, in the beginning, was that they had a superior and consistent product. Over time, they built massive distribution networks. From New York to San Francisco, Proctor and Gamble sold the same product in every store. 

But by the 1900s, that playbook was starting to wear thin. Their patents had run out. Competitors could match their quality. And startups had cracked into their distribution advantage. 

So rather than having a monopolist's advantage, P&G was now selling identical products to its competitors at higher prices. How could they justify that?

They stopped selling the soap itself. They started selling a story about what the soap meant about you as a consumer. Tide wasn’t just about cleaning your clothes. It was a statement that you cared that your family was clean.

In the 1960s, American enterprises transitioned from masters of product and distribution to master storytellers. Rather than utilizing the mass transit afforded by railroads, they started utilizing the mass media afforded by television. Mass Media gave rise to Mass Brands.

Brands spent billions on telling a consistent story on TV and in print about who they were, what they made and what it said about the buyer. 

It's a magical and meticulous misdirection. Pay less attention to the product, and more attention to its story. 

In one amazing example, Dawn dish soap introduced an ad campaign in 2002 highlighting how Dawn was not just the best-selling dish soap, but was so powerful and gentle, that wildlife groups were actually using Dawn to rescue ducks from oil spills. What does that have to do with its suitability for cleaning your dishes? Very little. But the ad worked. One report found that Dawn had a 337% ROI on ad spend on the campaign.

As Don Draper explains in his pitch, “Other cigarettes cause cancer. Lucky Strike is toasted.”

For 100 years, brands have worked like this. A team of marketing professionals crafted a story. They fed that story through the media platform of the moment. They sold products in-line with that story. They created value by using their stories to sell more goods at a higher price point than their competitors. 

But the internet shifted who controlled the brand’s story. Rather than speaking with a single voice, a brand’s customers started shaping the narrative.

They complained on Twitter about a bad flight. They evangelized the power of their iPhone camera via social media posts. The celebrities who wore a product in real life, rather than just in commercials, communicated what that product was about. 

But things have gotten stranger than that.

In their 2019 piece, Laura Lotti, Sam Hart and Toby Shorin wrote about Headless Brands using Bitcoin as their primary example. In the 1960s, there might have been a Bitcoin Corporation who would pay an ad agency to explain what Bitcoin was useful for and who should buy it.

But there is no Bitcoin Corporation. The founder has disappeared. There is no central marketing push. And yet – Bitcoin is known worldwide. How?

A community of true believers were inventing the story of Bitcoin as they went. Bitcoin’s brand was an emergent construction of its community. And that story changed over time. It was magical internet money for buying drugs. It was an inflation hedge. It was the investment opportunity of a lifetime. It was a tool for fighting tyranny. It was digital gold. Bitcoin’s brand is a collage of its users’ stories – told ceaselessly across the web and the wider world.

But it’s not just cryptocurrency. Consider the modern Republican Party.  In 2015, the “brand executives” at the RNC thought they controlled what it meant to be a Republican. And that meant to be someone like George W Bush, John McCain or Mitt Romney. Then came Donald Trump. The party elite viewed him as an aberration. If they were a centrally managed brand, Donald Trump would have been thrown out the door. But the Republican Party’s brand was not controlled by a party elite, it was controlled by the party electorate. And that electorate decided the Republican Party was now the Party of Trump. Except that wasn’t quite right either – not even Donald Trump controls what his party represents. 

At a rally in 2021, Donald Trump proudly took credit for the success of COVID vaccines. His supporters booed him. MAGA was an emergent construction. It no longer needed to attach its values or its brand to a single man. 

In the decades to come, communities – not marketing committees – will create the brands that matter. 

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Meet the Nouns

We can draw a through line connecting the three major projects that shaped the modern NFT space.

First, there was Cryptopunks. Punks, launched in 2017, consisted of 10,000 pixelated, computer-generated pieces of art. Their buyers started using them as profile pictures. Punks became an identity and a status symbol.

Then there was the Bored Ape Yacht Club. Apes differed from Punks in that they went a bit beyond status symbols. Buying a Bored Ape was not just a status symbol, it also granted access to a community of other high status owners. Bored Apes added community to the identity value of Punks.

Then there were the Nouns. Punks was a standalone status symbol. Apes offered a community and the promise that the founding company, Yuga Labs, would create cool projects for the community. Nouns went a step further. Rather than having a company control the project’s proceeds and determine how to spend it, they handed the treasury over to the community itself. Nouns’ members get to choose how to spend the profits from Nouns.

On June 1, Punk 4156 (not coincidentally a cryptopunk holder) outlined the contours of the project. “Initial supply of 0. One randomly generated Noun (avatar) auctioned per day, until the end of time. Auction proceeds are trustlessly donated to the Nouns DAO, providing the community with a perpetual source of capital from new members. Each Noun is one membership in the Nouns DAO.”

To put it even more simply, Nouns works like this:

Everyday Nouns auction off a single image of a computer generated character. Whoever bought that Noun would receive the digital art and become a member of the Nouns DAO. Whatever amount they paid would go into the Nouns DAO treasury. Only members of the DAO (those people who had purchased a Noun) would be able to vote on how to spend the treasury.

While the original launch provided little guidance for what the DAO should do or how its Treasury should be spent, it soon found its raison d'être: to support the growth of the Nouns brand.

The bet is simple. The larger the imprint of Nouns – the more people see and value the brand of these computer generated characters – the more valuable every member’s NFT will be. The better work they do together to create a Nouns brand, the more money they make.

We’re used to brands being something that tells a story about a product or set of products. But Nouns flips the script entirely. It asks the question: What if the brand comes first?

That’s not as crazy an idea as it may sound. Before she was the CEO of a billion dollar company, Rihanna was a singer. Rihanna’s brand meant something about style before she ever launched a single makeup product. 

In a world where attention is the scarcest commodity, the Nouns community is focused on trying to find ways to get attention. Products and services can follow from that.

To figure out what Nouns stands for, what its characters will become the brand of, the community has decided to cast the widest possible net. They have addressed the question of What do we do? With a collective shrug. In the place of guiding principles or guiding value propositions, they have a set of guidelines for ensuring that as many ideas as possible can take root, and the best flowers will bloom. 

The Nouns System works like this:

• CC0 Rights – The Nouns Project has the least restrictive copyrights on all of its artwork. Anyone – internal to the project or external – may use Nouns branding however they want.

• Open Treasury – Anyone can pitch the Nouns community to fund any project that they think will resonate. 

• Daily Auctions – Every day, the DAO auctions off a new NFT to help fund its treasury and welcome one new member. If it does its work well, the value of membership will increase over time thereby rewarding early adopters.

• Founder Rewards – Noun founders do not receive any royalty or have any special rights other than ownership of 10% of the Noun supply for the first five years. This aligns their incentives – their Nouns are only valuable if yours are – with the community.

So what does this look like in practice? 

Well, it looks a lot like a giant treasure chest for community funded arts projects featuring Nouns. So far, the community has funded (among other things):

• Giant bronze statues of Nouns (for 5 Eth)

• A Comic Book featuring Nouns (4.5 Eth)

• Sending a Nouns NFT to the International Space Station

• Placing Nouns in a Budweiser ad at the Super Bowl (free)

• A Coloring Book Series (11.13 ETH)

• A Nouns movie (115 Eth)

• A Rose Bowl Parade Float (62 Eth)

• (Pending) Creating a Nouns Franchise Restaurant

For artists and creators, Nouns is a phenomenal partner. As one put it in a YouTube interview, “It’s like an incubator of weird. Well, if you were to apply for an arts grant, my lord, the paperwork, and this and that and the waiting time, and you don’t know who’s voting, and you to got to get nominated… So to have something that’s a ton more nimble in terms of its funding processes, it’s fantastic for artists.”

The bet of the DAO is fund interesting people doing interesting things featuring Nouns. 

To enable that, the Nouns community has focused on making finding and funding artists extremely easy. 

To find more artists, Nouns has done something that few other crypto communities have – it has deleted its Discord. In doing so, it flushed its members into the wider world to connect. Ostensibly, this was about ensuring a few members didn’t exert outsized influence. In practice, it’s been an effective way to ensure that Nouns community discussions happen on Twitter or other places where the wider world might hear what’s going on.

To fund more artists, the community has built infrastructure to streamline the time it takes to go from idea to funding. Major projects are proposed through the entire DAO through Treasury Votes. These votes can take a month end-to-end – still pretty fast for the world of b2b contracts or art funding. But smaller projects move even faster. They are funded by quick popularity votes in response to themes/prompts posted by the community. Nouns has even made the tool they use to fund these projects open source to other communities. It’s called prop.house.

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Results

If the goal is to make the Nouns price go up, then the record of success is… mixed. 

After an initial speculative spike for early holders, the NFTs have settled in at a daily price point of ~30ETH. That’s only ~20% of the value in ETH that it was commanding in its early days. 

But this is a matter of perspective. Even in the middle of crypto winter – while Bitcoin and Ethereum traded at fractions of their usual value – the community is managing to sustainably add $45,000 per day in pure profit to its warchest. I know many startups that would be thrilled to say they were doing the same so that’s not bad for a media brand with no products to speak of.

Whether Nouns will ultimately build an enduring brand or collapse in on itself is an open question.

The newly funded Nouns movie could work. It could spark a new narrative ecosystem – a Marvel or a Disney or a Simpsons extended universe of Nouns characters that makes owning a character and a vote on its future direction extremely valuable. 

Their restaurant model could work – Nouns could end up with a chain of coffee shops/delis with its branding across Australia. And all of these things could make owning a Noun – owning part of the brand and its future – even more valuable.

But Nouns is very different than any business that operates in the world today. Brands make money by closing themselves off and licensing their imprint to products to make them more valuable. Nouns gives that value away for free. Instead, it monetizes by selling the right to join in their brand building story. You win if their brand equity grows.

If that model fails – if people just don’t really care about the Nouns brand or making a productless brand grow, then Nouns will just be one more weird experimental chapter in the history of the world wide web.

But even if Nouns itself fails, the model seems to be catching on. There are already a few hundred – mostly crypto native – projects that have imitated the Nouns model. There’s Lil Nouns which offers a more affordable entry point (read: $200 rather than $45000 characters) into the Nouns brand. There’s PurpleDAO which sells membership in a fund supporting an unrelated web3 project called Farcaster.

Extrapolations

If the ideas of crypto stay in the world of crypto, then all we’ve done is built an expensive echo chamber.  But the promise of Nouns is that it could change the way we build brands in the real world. 

Imagine, instead of Nouns characters, there was a daily auction of new sneaker drops for a limited collection of designer shoes from a hot new designer– with a shared treasury that would pay to promote the sneaker brand through pop up events, creator partnerships and other brand activations. Try to tell me those sneakers wouldn’t become a hot status symbol.

Imagine Taylor Swift auctioning off memberships to her fan club, with one new member allowed to join per day, and a treasury that helps to promote Taylor’s catalog through fan club events and brand activations. Imagine Swifties fighting over access to Taylor’s official fan club, and voting together on funding fan-made videos, fan events and designing official fan club merchandise to spread the Swift brand. Try to tell me that you don’t know a millennial who would jump at that opportunity. 

Sitting in that conference room, Don Draper tells the cigarette executives that when crafting the story of their brand, “We can say whatever we want.”

Don’s still partially right. The only difference is now his “we” refers to all of us.  

The story of the next great brand isn’t being written by ad executives during an afternoon meeting on Madison Avenue.  It’s being written by every one of us, from wherever we open our phones or sign-on to our computers.

What is a brand?

It’s the stories that we tell about the (small-n) nouns – the products, the artists, the ideas – that matter to us.

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 “Power resides where men believe it to reside. It’s a trick. A shadow on the wall.”  - Lord Varys, Game of Thrones

The Emperor’s New Clothes is one of those stories you know even if you’ve never read the whole thing. 

An Emperor hires two “weavers” to make him a new coat. 

The weavers tell him their coat has a magical property.  It is invisible to anyone unworthy of their office. 

The Emperor loves the idea of being able to discern who is competent and who is not based on who can see his brilliant new coat. 

Word spreads about the Emperor’s magical new coat. And every single bureaucrat in his court is terrified that they are the only one who can’t see the magical garment. So they all pretend to see it. 

Until one day, the Emperor goes out for a parade “wearing” his magical coat. And at that moment, a child cries out, “But the emperor is not wearing anything at all!” Now emboldened by the child (and realizing that the way to high status has flipped!) all the townspeople echo, “But he’s not wearing anything at all!”

It’s a great story about speaking truth to power, about the risk of con men selling snake oil, and about the innocent truth-telling of youth.

But honestly, I feel like the coat makers are getting a bum wrap when we call them “conmen”.  

No, they didn’t make a coat. But didn’t they deliver the exact value that the Emperor asked for from that coat?

By seeing who would tell him the truth and who cowered before power, the Emperor’s New Clothes revealed exactly who was competent and who was not.  

Isn’t that exactly what the coat makers promised?  

Any tailor can make a coat, but a shibboleth that can discern character traits… well, that’s truly special.

There was a time when the primary value of our clothes was that they protected us from the elements. But surely that time has long passed. From clothes to art to our exercise classes to our real estate, the value of goods has gradually shifted from their material attributes to their immaterial ones. 

The value that our King wanted was not a material coat.  It was the immaterial gifts that that coat would offer.  So if that end could be achieved without a single inch of thread, well – so much the better.

A Game as Old as Art

If you’ve never seen it, but have any interest in NFTs, art or even human psychology, I can’t recommend the documentary The Lost Leonardo highly enough.  It tells the story of a painting by (maybe) Leonardo DaVinci, the Christ Salvator Mundi.

I say “maybe” because the provenance of the painting in question is the real subject of the documentary. In 2005, two art dealers bought a painting in New Orleans for $1,175.  While having it restored, they discovered that the painting - buried under layers of other paint -  employed certain techniques associated with the work of Leonardo Da Vinci. They send it to London to have it inspected by experts.

The experts cannot reach a conclusion on whether it is by DaVinci, a student of his or just happens to share certain stylistic techniques.  And the stakes of that debate are massive. If done by a random contemporary of DaVinci, the painting is worth the thousand it was initially bought for.  If it was by DaVinci’s student, it could be worth hundreds of thousands. But if this was done by the master himself, the experts tell us, the painting is damn near priceless - or worth hundreds of millions - whichever you prefer. 

While the debate rages on, the market for the piece heats up.

The painting sells to a Russian oligarch for $127 Million. Then Christie’s re-sells it for a record $400Million to a secret buyer, rumored to be the Crown Prince of Saudi Arabia, Mohammed bin Salman Al Saud.

Now - unlike our poor Emperor, there is a real material painting here with actual canvas and paint (though much of the visible paint has been applied during “retouchings”). But, let’s be honest, is there anyway that that canvas is actually worth $400 Million?

Surely, there’s nothing about the material object that justifies that valuation. After all, why would that same painting – with all the same properties – be worth $1000 before it was a known “Da Vinci” and 4 million times as much when a few wealthy people said that it was by the old master?

It can’t be because of the material of the art itself.

It’s because of its immaterial properties.

It’s because owning something created by someone so famous is an incredible statement of one’s status.

Like our Emperor, it’s not the art itself that’s valuable.  It’s what the art communicates about the buyer and about the people who recognize its value.  It’s a status game, through and through.

A Better Mousetrap

But as a status object, art and clothes both lack certain properties you would want.

Art is expensive to display, protect and maintain. And while certain people in the know might realize you own the painting, most people who research the artwork will just see the artist’s work. Your ownership will be a footnote. 

Fashion, meanwhile, is easier to associate with your person. But you won’t wear a single item every day. The most expensive statement pieces are usually worn once in a lifetime.

But, imagine instead, if there existed a cultural artifact that was consistently affixed to you as an eminent marker of your social status.  Imagine if that same artifact was indestructible and infinitely viewable by everyone on the planet.  Imagine if that item could be used to instantly access private clubs and events open only to other holders of high status cultural artifacts.

And imagine that all you had to sacrifice for that better fulfillment of your status objectives was some colorful fabric. That sounds like a better mousetrap.

This is what I think people misunderstand about NFTs when they cry, “It’s not even a physical canvas! It’s just a JPEG!”

But it’s never the thing that has value. 

 It’s always the story we tell about that thing. 

We just bundled an object and its status benefits together.  But when you unbundle them, and you ask yourself, “What is the best way to sell the status associated with cultural objects?” You open up some rather interesting possibilities. 

And that’s the power of NFTs.  NFTs allow us to dispose of the lie that the physical object is the valuable part of a status good.  After all, anyone can google Christ Salvator Mundi and see a painstaking representation of it.  In fact, you can even Right-Click-Save a JPEG of it. 

But when we dispose of the lie that access to a physical good is the valuable thing about owning art, we can then really focus on the actual status benefits of owning such a good.

And those status benefit for art, as for NFTs, comes from a few places:

• Access to a Community - The key innovation of the Bored Apes community was providing a private chatroom and now, private events, for holders of Bored Ape NFTs.

• Access to the Artists - If I buy a DaVinci, I can’t talk to DaVinci. But once I buy a Beeple piece, I can directly interact with the artist to ask questions about the work.

• Ego/Identity Benefits - Oh, you can display a painting in your foyer?  It’s my Twitter profile picture seen by thousands every day. Just by holding it, I convey legitimacy to the broader community. 

• Reflected Glory - As part of tying my identity to that cultural movement, I can be seen as someone with their pulse on which art is valuable. I can go from talent purchaser to tastemaker, just by virtue of signaling my ownership of cultural artifacts online. 

Now, we might be uncomfortable with how NFTs strip the status game of any pretense of…materiality.  We might just not like such naked displays of status signaling. 

And that’s totally fine. Raw social signaling makes people uncomfortable. It feels gauche.  

But we shouldn’t pretend that we don’t all play status games.  If you’ve ever bought fashion or makeup, art or a nice car, you’ve participated in a status game. 

And that’s okay! It doesn’t make you a bad person. It just makes you a person. Status games are a natural part of being human.

But the next time you criticize someone’s NFT for not being real, remember the real lesson of that little fairy tale: the Emperor might be naked, but it was really never about the cloth anyway.

Three Crises

On February 13, 2023, the CDC released a shocking report about teenage girls.  Nearly 3 in 5 had experienced persistent sadness or hopelessness in 2021.  30% had seriously contemplated suicide.

On March 6, 2023, the United States hit yet another awful milestone in its losing battle with gun violence.  By the 64^th day of the year, there had been 100 mass shootings in the USA – a feat that had taken till March 19 in 2021 and March 22 in 2022.

On March 10, 2023, Silicon Valley Bank collapsed after a bank run. It was the second largest bank failure in US history.  It could be a blip, but it could also be the state of a financial crisis.

On the surface, these three crises have little to do with each other.

Indeed, it could be in poor taste to associate them with another.  After all, each would seem to demand a different intervention.  Bankers might need therapy or benefit from gun control, but that’s it for common ground, right?

I disagree. 

These are not isolated crises.  They are crises that are arising at the same time for a reason.

Each of them – from spreading teen depression to financial panic – is a direct consequence of the information ecosystem that we have constructed for ourselves.  But it is not as simple as saying “social media good!” or “social media bad!”  Humans, it turns out, have always been vulnerable to outbreaks of hysteria.

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Dancing Ourselves to Death

If you read enough history, you occasionally come across something that really fucks with your head.

“The year was 1374. In dozens of medieval towns scattered along the valley of the River Rhine hundreds of people were seized by an agonizing (sic) compulsion to dance. Scarcely pausing to rest or eat, they danced for hours or even days in succession. They were victims of one of the strangest afflictions in Western history. Within weeks the mania had engulfed large areas of north-eastern France and the Netherlands, and only after several months did the epidemic subside. In the following century there were only a few isolated outbreaks of compulsive dancing. Then it reappeared, explosively, in the city of Strasbourg in 1518. Chronicles indicate that it then consumed about 400 men, women and children, causing dozens of deaths.” (From John Waller’s A Forgotten Plague: Making Sense of Dancing Mania)

Who were these people that saw people dancing who couldn’t stop and then joined in themselves?

It sounds unbelievable.

Until you learn about what happened in January 2021.

Across America, England, Australia and Canada teenagers starting coming into emergency rooms with a similar sit of symptoms.  The kids, seemingly healthy, had all developed tics commonly associated with Tourette’s syndrome.  To the disbelief of their family, they had started uncontrollably swinging their arms and shouting loudly.  

The common thread, researchers realized, was this:  all of them had been watching TikTok influencers with Tourette’s. Their brains had seen the tics and subconsciously starting mimicking it.

Yes, really.

We already have a loose sense that information can act like a virus.  We call videos that spread quickly “viral videos” after all.  We talk about “spreading memes” or people being “vectors for the disease of misinformation.”

But we think of those phrases as metaphors.  Viruses might take over our body for their own ends, but information?  Our minds are our own, surely.

Except those metaphors are closer to the gospel truth than we might like to admit.

In his 1976 book, The Selfish Gene, biologist Richard Dawkins coined the term “meme” as a cultural analog to a “gene.”  A meme, like a gene, was a bit of raw information that contained content – an idea, a belief, a cultural norm, a value judgment – and like genes, these bits of information were subject to natural selection.

Any new idea or observation could be replicated by being spread – much like a gene in reproduction – and just like a gene, it would be tested by the environment. Many would die off, but the “most fit” would survive, replicate, mutate and mix with other memes to create the “fittest” ideas.

In the marketplace of ideas, we choose the ideas.  In the evolutionary ecosystem of the “meme,” it’s not the best ideas that win but those that are best able to demonstrate fitness – the capacity to spread through hosts.

But even if this is true, it’s been true forever.

So why would there suddenly be crises? We have millions of years of evolution-designed hardware to do battle with the fittest ideas.  And we have hundreds of thousands of years of developing social tribes and  governing systems to process information and discard those memes that are not useful.  We were well equipped for the Darwinian wars of yesteryear.

But we are not fighting the last war anymore.

We have removed ourselves from the pond of local social interaction, ideas filtered through local and comfortable norms that our ancestors inhabited, and dove head first into the ocean of a new information ecosystem that operates with a pace and ruthlessness that rivals the prehistoric savannah.

Why Information is like COVID

In the last three years, we have all become relatively comfortable with understanding the spread of viruses.  So let’s apply that model to our information ecosystem.  After all, a person – when confronted with a bit of information (whether virus or meme) can reject the information before it takes root, we can host it but defeat it before spreading it, or become a vector for spreading it ourselves.

Thus, the same models we use for understanding the spread of an infection can be used to model the spread of an idea.

In epidemiology, this model is defined by two variables:  R₀ and R_E. 

R₀ measures the propensity of a virus to spread among a naïve population that has no immunity.  If a virus has an R₀ of 2, then each person can be expected to infect 2 others.

R_E measures the propensity of a virus to spread among a population in real life.  If a virus has an R₀ of 2, but half of the population is immune to it – from prior exposure or vaccination - then its R_E is half of its R₀ and each person can be expected to infect only 1 other.

Information spread can be modeled in the same way.  A particularly “infectious” idea – whether a really funny video, a signal of virtue, or a fear response – should have a very high R₀.  Even more dangerously, repeated exposures to an idea – if not corrected – makes it more likely to stick. It’s as if every time you got COVID, you became more infectious.

Now, we fought COVID the way we fight all viruses – by making it harder to spread.  The thing is – we’ve been doing the exact opposite with information.

In the early days of humanity, ideas spread orally, so you could only learn of them from someone speaking to you directly.  Then we had writing, which allowed a bit bigger of a vector for spreading ideas.  But the internet has lowered the cost of putting content into the world to zero – and it is literally available for anyone on the world to see or consume.  We simply have a far larger amount of memes out there than ever before!

And then we needed a way to sort through all this spreading information to find the ones that we cared about.  So we deputized giant machine learning models to help serve the role that our social tribes once played – filtering through the noise to find our personal version of signal.  And in doing so, we’ve created an infrastructure that maximizes the speed at which information can spread and that can ensure the fittest ideas get maximum exposure. 

Trending algorithms, like those on Twitter, find the memes that are most viral at any given time and funnel more people to them.  It’s like if there were a COVID outbreak in a town so rather than isolating them, we tried to cram as many people into the space as possible. 

Ranking algorithms, like this on TikTok or Instagram, find the memes that are most likely to take root in an individual and deliver them directly to a host. 

This need not bad.  Most of the information we share is good.  We share the things that make us human – our families, our struggles, our hobbies.  We also share causes that can change the world for the better.  Human rights are a pretty good meme and we should spread it.  Democracy is also pretty solid, IMO. 

But evolution – whether biological or memetic – cares little about what is “good” or “true” or “helpful” to its hosts.  It cares about what can survive and spread. It generates strong ideas that can exploit the hosts most vulnerable to its fitness adaptations.

So when it comes to questions of identity or insecurity or social isolation, it finds a willing population of teenage girls to spread among.  When it comes to violent crime, we send news about violence to mentally unstable individuals.  When it comes to financial panic, we send it to Very Online VCs like David Sacks.

And just like a virus – the meme’s success does not depend on the thriving of its hosts.  It is happy to infect, spread and move on.  If the human being that listened is left damaged, well… that’s just nature baby.

It's not an accident that we use the same word “contagion” to describe how suicide begets more suicide in local areas, or how mass shootings spawn imitators or how a bank run at a single bank seemingly spawns similar runs at totally unrelated banks.  Human see, human do.

We are not powerless in the face of nature.  We escaped the War of All Against All once and we can do it again.  Friedrich Hayek famously wrote that capitalism succeeds because it does what no other system can – it enables the effective use of information by all members of society.  That is our challenge once more, to build systems that can turn a waterfall of information into a power source rather than a devastating flood.

Viral Interventions

In the American and Chinese response to COVID, we can glimpse two paths for civilizations to confront threats that spread like viruses and grow exponentially.

China used a top down system as a blunt instrument. They shut down dissent and shut down vectors of transmission. They succeeded in the short term, but with a heavy long term cost. China’s population remained utterly naïve. Because they had not been exposed to the virus, when they finally “let it rip,” it may have killed up to 1.5Million people.  All while threatening their economy and political stability. Authoritarian interventions work in the short term, but fail to build any kind of durable resilience.

The American System, in contrast, is best defined by – well the lack of a system.  America is both small-c and large-C constitutionally incapable of a Chinese response.  We do not abide being ordered.  The results of our non-system were not pretty.  Over 350,000 Americans died in just the first year of the pandemic.  But the longer term results – well – are a bit more balanced.  Americans developed resilience in the face of the pandemic.  Getting COVID in America today is inconvenient, but it is hardly catastrophic for the lion’s share of citizens.  Our population developed interventions – vaccines, new treatments, masks and personal spacing – and life returned to normal.

China’s control works in the short-term, but breeds long-term fragility. America’s is short-term painful, but breeds long-term resilience.  The lesson for our information ecosystem is also clear – we want to minimize short term pain while maximizing the gains of long-term resilience.  And we have tools to do that.

We can start by getting eyes on the potential spread of dangerous memes. Today our best view of the spread of “memes” comes from Twitter’s trending page.  But this is personalized to us, and lacks huge amounts of important context on the spread of a meme – where is it spreading? Who is spreading it? How quickly is it growing?  And just as importantly, is it causing dangerous consequences? 

Viral video of a banker falling on a street – good.  Viral video of a banker falling as they are overrun by fearful depositors – maybe, less good.

If we develop a set of open and transparent tools for viewing the emergence of information, we will be able to understand when interventions are worth deploying.  I don’t pretend to know who should deploy them – the state, the companies or the emergent digital organizations in blockchain-land building a collectively-owned commons.

But whoever gets their hand on the lever should know that they have a few tools in their toolbox: interventions, inoculations, circuit breakers and cooperation.  Not every tool is right for every situation. Many can be abused. But the goal in managing any sufficiently complex system isn’t to find a silver bullet – it’s to have a variety of scalpels handy.

We need to propagate interventions that work to empower and build resilience in populations. Think of these as our “medication” for information viruses.  Today, good interventions are lost in a sea of bad information.  Today social media content on mental health is driven by the “trauma influencers.”  These accounts, some pseudo-therapists, some just nihilist meme-makers, emphasize emotional validation rather than actual existing constructive therapies that, while they share some of the language around trauma and triggering, ultimately move beyond validation to teach coping skills.  Effective therapies exist – I’m a personal fan of ACT, CBT and dynamic modes-- but these interventions are more difficult to put into a viral meme. 

We need to inoculate individuals against harmful memes.  Studies on misinformation show that individuals exposed to a “weaker” version of an idea can build up resistance to that meme. So that when they are exposed to it, they are less likely to adopt and spread it widely.  We should be teaching people about the types of memes that play on their built-in biases to trigger emotional responses that are unhelpful to their personal goals – panic, fear, hate, depression, etc.

We also need to consider when it might be helpful to implement a variety of circuit breakers in our system.  Today, when the stock market falls rapidly, circuit-breakers are triggered that temporarily suspend trading.  Individuals remain in control of their equities, and they can begin trading again after a pause.  But a “circuit breaker” response to overheating memes that temporarily restricts or delays sharing, could prove helpful for breaking panic loops that trigger things like bank runs.  (Though admittedly, this capacity has a great risk of being abused).

Finally, we might look to our ancestors. 

They understood that one of the best systems for confronting dangerous new ecosystems was to band together.  Tribes are an evolutionary adaptation so that humans can cooperate to put a stop to threats.  But our modes of cooperation are often slow and involve too much counterparty risk.  For example, during the bank run, many VCs tweeted about standing by SVB, but without the ability to credibly organize, each had to fear that another VC would defect and they would be left holding the bag.  Smart contracts – with their ability to create self-enforcing mechanisms for cooperation online – should fix this by enabling these banks to coordinate and credibly commit, in immutable code, to stand together if sufficient thresholds are met.

Then, whatever memes may come in our new world – whether they make us dance, make us depressed or make us withdraw all our money from the bank – we can at least have a fighting chance to do what us humans have always done: work together to survive.

Changing the world is hard work. 

Noted doer-of-things and coke fiend, Thomas Edison described success as 1% inspiration, 99% perspiration, and honestly, that might have been too generous to inspiration. Vision, without execution, he said, is just hallucination.

Implicit to Edison’s point is this:  your idea isn’t worth what you think it is. Ideas are nice. They feel good when you have them. They are also worth zero.

Whether people understand this concept is a useful shibboleth for the type of builder they are.

Those that don’t have much experience in building technology, but have seen movies like The Social Network, tend to think that the idea is the thing.

So when novices have a great idea, and they want to start a business, they ask people to do things like sign an NDA. Those of us who have built products tend to find this amusing (and kind of annoying).

All of this is to say: with proper respect to the dreamers, it’s the doers that really matter.  

While bull markets are great for dreamers, it’s only in the bear that you find out who has the fortitude to chew glass and do.  And doing, it  turns out, is hard in crypto.

I tend to think of building communities in crypto as a ladder of difficulty.

At the bottom of that ladder, you have communities that have organized around digital assets. NFT profile picture projects. Gaming guilds. Token traders.

One level up from that, you have people who are providing real world utility to their community. This usually involves some kind of real world asset, but often one – like in-person experiences or a property – that can be purchased by anyone with money.  The challenge here comes from building a bridge between the digital, self-referential world of blockchain to the “real economy.” (Quotes provided with appropriate sarcasm)

At the top of the hierarchy are those brave few who go one step further. Not only do they have to interface with real world assets and the accompanying legal morass, they have to participate in permissioned real world assets. That means, they not only need the capital, they need to convince someone – legislators, regulators or status gatekeepers – that they deserve a seat the table.

As I’ve quoted before from Billions – the hardest asset class to own in the United States is a major sports franchise. It remains the closest thing to knighthood we have in America.

Earlier this year, I wrote a piece on Krause House DAO and their vision to become a minority owner in an NBA team.  It’s an awesome vision, and one that I expect a community will bring to fruition in the next decade. But like I said before – having the vision and being able to execute on it are two different things.

That’s why I was pleasantly surprised when Commodore, one of two pseudonymous founders of Krause House, reached out to me two weeks ago. He told me that the community had recently gotten within spitting distance of becoming a minority owner of the Phoenix Suns. He has since written up that story, and it’s worth reading, if for no other reason than to see the level of hustle these founders display in texting acquaintances if they have a connection to people like Bob Iger.

And even though this was not a successful effort, there’s often better learnings in close failures than there are in successes.  ConsitutionDAO, for example, demonstrated both the potential of DAOs to raise capital at lightning speeds from a community, while also revealing the legal and operational gaps that keep those communities from being able to compete.

So when I spoke to Commodore, I wanted to focus on what he had learned through this process.  His lessons for the broader DAO community (lightly edited to make our message thread more parsable) follows:

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Alex: Something that comes through in your description of events is the need for secrecy. Bidders join together in private, construct bids in private and even interact with sellers privately.  How does that work in a community-model like DAOs that are built on transparency?

Commodore: We saw what happened with Constitution DAO’s transparent treasury balance & their aspirations of winning a bidding war. A lot of the work that spiraled out of that failure was the promise of ZK proofs solutions.   

(Alex note: A ZK proof solution would allow bidders to demonstrate that they have sufficient assets without revealing the exact maximum they can bid.)

A lot of the earliest DAOs were DeFi in nature which could exist more naturally in an adversarial environment. Social DAOs are something different, they partially exist because of trust. For us, the goal of collective ownership is the ultimate.

We need to conform to the strategies that achieve that goal & stay compliant with NBA by-laws, but it’s certainly a challenge to balance.

Alex:  Theoretically, one of the superpowers of DAOs should be leveraging the networks of the community. Did this change the way you guys think about building a community/recruiting members that can put you in a good place to join bids later on? Or do you think the 'open to everyone' path is still the right one to take?

Commodore:  In our case, the power of the DAO’s network has been predominantly the “network of networks” value. It’s really interesting applying a DAO network to such a small list of human beings (NBA owners) that we need to connect with.

Coincidentally, my co-creator Flex & I’s personal networks have fueled a vast majority of the owner introductions.

With that being said, we’re exploring all models of introduction paths.

Alex:  In your conversations, what kind of capital was needed to be taken seriously?

Commodore: A big innovation we’ve been quietly working on is the forming of Krause House Capital, which is a private equity firm created by Krause House DAO.

This gives us the ability to backstop our bids at much larger amounts. NBA by-laws require at least a 1% stake & most valuations are now north of $2b, so you have to be looking at $20m+.

But you also take 1 of 25 ownership slots & a private equity slot. To answer your question, it’s at a minimum $20m but ideally you’re well north of $100m.

Alex:  The NBA has a reputation for being innovative, but this is still an international media brand so I have to imagine some degree of conservativeness.  How was your association with DAOs/NFTs received (especially in a bear market)?  Was this a pro (because of potential innovation/fan engagement) or a con (because of crypto’s somewhat toxic brand)?

Commodore:  It’s important to get into the mind of the owner & use language that’s relevant to them.

The actual object that will sit on their cap table is a private equity fund. That fund is made up of LPs that are Jerrys (NFT holders). We’ll build experiences for all of their current & future fans, regardless if they’re LPs.

What most owners understand is that crypto can be (and should be) thought of as infrastructure. What we say to the average fan might be language like “digital pass”, but it might be backed by a custodial wallet that’s holding a NFT. We make it a point to say that we’re more than willing to start with “web2.1” if that eases their anxieties. The unfortunate reality is that the crypto bear market & FTX’s collapse have left a very sour taste to only the staunchest believers. With that said, they see the immense possibility of it — just need to be very careful & conservative in the implementation of it.

Alex:   What other lessons do you think communities trying to engage with buying important real world assets and appealing to traditional owners should consider?

Commodore: I think the most important part is understanding what the first principle issues that are challenging the problem are paramount.

A lot of us in the crypto ecosystem are here because we see this incredible technology that has the opportunity to make material changes to the world. However, that can cause us to sometimes to work from a solutions-first view; rather than a problems-first view.

That is what's really powerful about Krause House's mission. We have a problem: fan ownership. A DAO is a tool. A private equity fund is a tool. Discord is a tool. When you're able to take a step back and look at each technology as a tool & apply them to our shared goal — the solution space really opens up.

So when I see DAOs step into the real world with real world assets, they can struggle with where to be flexible and where not to be — because they're applying their solution first. The other big unlock that I think many DAOs miss is the idea of delegation across all dimensions, not just governance.

Any time a majority owner / governor has control over a dimension — crypto has the tendency to throw their hands up... "it's not decentralized enough". While that principle is true, very few things in the real world work in this way. The legal system & capitalist system have developed many ways of delegated control.

By embracing this reality, we can novel solutions & experiences for our shared goal. To me, this is paramount as we build out successful use cases that we can point to others as evidence to give DAOs even more responsibility... over time.

“The press acts like information's a dirty word. Everyone has access to the information. We just know how to analyze it better.” - Bobby Axelrod, Billions

When I started writing Charterless, I thought it would be hard to get a good handle on these new DAOs – I had a limited network since I was new to the space. 

But the beauty of Web3, I soon discovered, was its legibility. 

If I wanted to understand the rise of a new, hot project and which influencers were pumping it, I could see the entire transaction history on Etherscan or track user adoption on an open-community dashboard.

If I wanted to understand the major debates inside a new organization, I could read their Discord or their debates on Discourse.

If I wanted to understand a contentious issue, I could see how their members voted on Snapshot.

If I wanted to know who the key players were, I could find them on Twitter or Discord and DM them.

Just by having access to the internet, I had the keys to the whole kingdom.  

It’s hard to imagine a similar level of access for stealth startups or even large publicly traded corporations.  Even on earnings calls, well-credentialed Wall Street analysts have limited access to roadmaps, public plans or the data underlying top-line numbers.

If there’s something powerful about blockchain it can be found in the promise of this openness. Open data + open community + open planning compounded + open source software  = a positive sum economy.  #WAGMI, indeed.

And yet, the on chain remains rife with accusations of nepotism, insider trading, insider dealing, and gatekeeping.  So what gives? Has the vision failed or are we still not getting the right information?

My hunch is that we’re still not getting the right information.  But it’s not just a problem of what data is available on chain – it’s about what we’re doing with that information. Blockchain currently provides unprecedented access to financial reporting. But it provides little direct signal on the actual work that that capital enables.

(Insert Web3 skeptic joke about how there’s no actual work being done…)

This means that Web3 is financially open, but operationally closed.  It’s easy to know who is trading which token. It’s easy to know the result after a vote happens. But it’s far harder to get involved and participate in building the digital economy.

That’s a problem for Web3 because its theoretical promise is to harness the collective wisdom of the open internet.  And that’s a problem for builders because, it turns out, economic outcomes are just as much a function of an inequality in information as they are an inequality of capital or talent.

Where does that execution information live today?

It is tightly held by the world’s legacy behemoths. 

Facebook and Google control a digital ads duopoly because they maintain the world’s most comprehensive information on our desires.  The use of that information is available to users for a fee.

Bloomberg does the same for stock markets. If you want a terminal, you can fork over $25,000. 

Or, if you’re in the B2B game and want information on where to look for leads you can turn to LinkedIn or ZoomInfo for a few hundred or thousand dollars per seat. 

If you want the best information, you have to pay top dollar. 

Economists make a lot of simplifying assumptions on their way to concluding that markets are the best system for managing an economy. But one that’s particularly important is that everyone in the market has perfect information on what they want, what’s available to buy and what it should cost. Asymmetries in information cause frictions that keep the economy from operating well.

Imagine how much easier your job in R&D would be if you had access to data on your customers’ habits and needs. Imagine how much easier your job in sales would be if you knew what your customers were already buying and what their goals were.

So what if we could transcend that information gap? What if a combination of blockchain’s open information and AI’s ability to sift through it for signals could provide us with a truly perfect, open market free of information frictions?

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The Promise of Perfect Information

Hiring Help

I worked with some of the smartest people I have ever met at Facebook. I also worked with some real lemons. These two groups had shockingly similar resumes. They both could perform reasonably well in interviews.  The company invested a lot into recruiting and evaluating its practices – and yet, it was almost impossible to actually get reliable information on who would be successful and who would fail in their role.

Let’s imagine I’m running a firm.  How can I decide who I should hire and how much I should pay them?  I create a process, hire some people, then fire the ones that don’t work out.

But this is a pretty expensive way to vet talent. It essentially introduces a tax on my hiring since I need to bake in a certain expectation of failure in any new hire. (Worth mentioning that I could also hire someone surprisingly great. That would be great for me! But then I would likely be underpaying them unless I decide to be generous with bonuses…) 

And since this information gap increases the price of acquiring the talent, I am likely to buy less of it. Put another way: I will hire less people. And that’s what economists find.

This is, fundamentally, a problem that the signals we use for hiring – school attended, companies worked for, selected references, performance in a 30 minutes interview – are poor proxies for the work to be done. So what if, instead of looking at someone’s LinkedIn, we could actually look directly at their contributions? 

With on-chain code and Github, we can see who contributed directly to projects, how they contributed and what the eventual impact of their work was. Increasingly, this is why open source contributions are a pathway to work for coders. By lowering the cost to assess candidates,  perfect information makes labor markets more effective.

Pricing and Expanding Trade

But it’s not just labor markets!

Better information leads to more trade of goods and services.  And this has been true from the telegraph to the internet. 

In 1886, telegraph wires connected to the New York and London cotton markets for the first time.  Up until then, prices between the two markets would fluctuate widely, according to data assembled by Claudia Steinwender.  After the telegraph connected the markets, prices equalized across the American and British markets.

This reduced the opportunity for arbitrage, but it also gave merchants more confidence in their trades.  The result of better information was better trade.  Steinwender finds that the overall volume of trade increased by 6% thanks to more trustworthy price signals.

Not bad for sending dots and dashes under the ocean.

And the internet does much the same.  A 2011 study by McKinsey looked at the power of connecting small businesses in developing countries to the internet.  What they found was that access to list their goods on global markets and receive purchase orders directly led them to double exports. That had a profound effect – businesses connected to the internet grew at twice the speed of their competitors.

So imagine if there were a global market for goods and services, complete with reputation mechanisms, where companies could list wares and compete with any manufacturer worldwide. Imagine that all of that data – including sales – were available to every firm, every seller, every person in the world.

The closest we have today is Amazon.  And Amazon is great, but … well… sellers are less sanguine about it.  Because Amazon owns the platform, they have the best data about what is selling and will often undercut their own sellers or create copycat products.

There’s nothing wrong with competition. But when only one company has perfect data, no other company can hope to compete with them.

Lead Discovery

Or, consider the case of ZoomInfo and LinkedIn Sales Navigator.  

Both of these products command over ~$1B in annual revenue by augmenting publicly available data to help connect sellers with firms that will buy their goods.  

Imagine instead if there were an open database of officers and purchasers at various companies complete with a set of open RFPs. That would enable competitors to bid on pretty much any contract and build relationships with any buyer.

It would enable firms to find new clients, and clients to find new useful products and services.  By eliminating the cost of finding customers, open ledgers can make the economy operate far more efficiently - and put more money/value in each of our pockets.

The Perils of Perfect Information

Unfortunately, perfect information is not a cure-all.

To begin with, there’s the privacy implications.  Most of us are generally uneasy about large corporations like Google or Facebook having detailed records of our lives. So now imagine if anyone could search your entire work and purchase history?  Gross.

There are steps we could take to limit the damages.  There are privacy protecting “mixers” that allow us to send transactions privately when we need to – like an incognito browser for our wallet (though, the current controversy over Tornado Cash makes that defense problematic).  There’s also the option of using aliases for our online entities – this is why so many folks in the crypto community operate behind cartoon avatars.  

But perhaps the best solution will be the widespread adoption of Zero Knowledge Proofs.  This technology allows private transactions on public blockchains. It is likely we will enter a future where many of our personal transactions are private while our economic transactions – especially those made by public firms – are publicly reported on-chain.

But more troubling than privacy implications are the fraud implications.

In a 2018 paper, Benedikt Notheisen and Christof Weinhardt argued that while, in the short term, perfect information leads to better trade, in the long-run it becomes another vector that bad actors can exploit.  As they show in their model, in a truly open economy, bad actors learn the signals that good actors watch to make their decisions. They learn to mimic these quality signals, and then make it even harder to catch them.

Private information on assessment criteria, it turns out, limits the ability of bad actors to deceive. 

And this brings us back to our good friend, Sam Bankman-Fried.  SBF was able to watch the cryptomarkets play out. He knew why typical customers didn’t trust the first generation of crypto-barons.  

They were too ideological, they were too hostile to regulators, they spoke too much about shaking up the world order, they dressed and drove around ostentatiously while giving nothing to charity.  So Sam invented a more compelling character.  SBF was an ideological “effective altruist”, he came from the right schools and family, he worked credulously with regulators.  He was the trustworthy player in a game of thieves.

And it worked.  To the tune of 30-some-billion dollars.

Because Sam understood that the evaluation criteria of his audience was not about what was going on in his books – it was about the character that he created.  And this system worked.

Which brings us to an important warning about perfect information – it’s always an illusion. We simply don’t have the attention to look at all the data or the ability to capture every actor’s private intent.  This should remind us, even in the face of overwhelming data, to stay humble about our ability to discern the truth.

Perhaps the best thing we can say about open data is that – like a bug in open source software – enough eyes on enough types of data will make any threat shallow.  We can do more to make a dark world legible, but safety – safety is always an illusion.

When Cars Were Illegal

There are decades when nothing happens and then there are weeks when decades happen.

This past week has felt like a decade for the strained relationship between Washington DC and Silicon Valley. From SEC actions on crypto to Supreme Court cases on Section 230, it’s clear that the two coasts of the American empire are locked on a collision course. And that’s before we even consider how to regulate artificial intelligence.

The relationship between DC and SF is painted by Elon, Thiel and their disciples as inherently antagonistic. How could it be anything but? Silicon Valley moves fast and breaks things. DC moves slowly and tries to clean things up – while maybe wrecking more things in the process.

But that simple fairy tale belies a more interesting reality. Government is not the enemy of innovation. Government basic research often provides the seeds that become disruptive companies. Good regulation - like externality pricing, infant industry protections and consumer transparency measures - can help markets operate efficiently. But bad regulation is well… bad.   

The problem is that it’s often hard to know which is which in the easiest of circumstances. When it comes to new technologies that provide seismic shocks to our social and economic order, well… it gets damn near impossible.

But that doesn’t stop us from trying. Take, for example, the history of the humble automobile.

On June 3, 1900, the New York Times reported on a little-known provision of state law: Penal Code 640. That provision provided that New Yorkers could be fined up to $500 (~$18,000 today) and imprisoned for a year for driving a car without having a second “operator” waving a red flag at least ⅛ mile ahead of the vehicle.

The law had been passed before automobiles were really invented. It was intended to accommodate new steam engines that were starting to move outside of tracks.  But every lawyer that the NY Times consulted with agreed that it could be enforced against cars – if any regulator was brazen enough to try. None did in New York.

But in England, things were different. The UK had a similar Red Flag law - it required the red flag alert system, but also demanded that three people operate any vehicle and that no vehicle travel over 4 mph lest they scare livestock.

And the result was predictable. While America led the way in automobile manufacturing, England lagged behind until they eventually reformed their laws in the early 20th century.

One lesson of the Red Flag Laws is that vaguely worded old regulation can be a dangerous tool in the hands of imperious regulators with a savior complex. 

But, again, it’s not so simple.

Regulation also saved the automobile industry from itself.

In the 1920s, cars were selling quickly. But fatal accidents were ascending just as fast. Drunk driving, reckless driving, speeding – all of it was leading to surge in traffic fatalities. The public was excited about cars, but also kind of terrified. Because say what you want about horse-drawn-carriages, but the risk of dying in a horse crash is well… low.

So the industry worked with the government to create programs for licensing drivers, for eliminating drunk and reckless driving, and for instituting speed limits. The public’s faith in automobiles stabilized. And the American automobile went on to become a cultural and economic behemoth. By the 1970s, 1 in every 5 American jobs depended on the industry.

Bad regulation that fails to anticipate and evolve with technology is bad. Good regulation that creates trust, transparency and accountability accelerates progress.

So how do we find the right balance? How can we maximize the benefits of this really exciting era of progress while not creating our own dystopian hellhole? 

We can start by remembering what regulation is intended to do.

Crafting Good Regulation

With all due respect to my socialist friends, the market is a pretty phenomenal way to make decisions. Rather than allowing any particular powerful actor to say what is “good” or “right” or “valuable”, we crowdsource the decision to individuals who - in a thousand purchase or not-purchase decisions - reveal what they actually value.

And yet – the market fails us all the time. It does so when our impulses lead us into a race to the bottom or when information and power imbalances cloud our judgements. The project of regulation, then, is not to substitute decentralized decision-making for that of a bureaucrat, but to keep us from falling into these traps. 

This is, of course, a subtle art. It usually requires a light touch. The best regulations are those that are easily understood, easily acted upon, and frankly - those that easily fade into the background.

That’s why the list of good reasons to regulate businesses is actually pretty small. Even as a self-described liberal, I’ve got only four. 

1. The Moloch Problem. In certain cases, the incentives of the market force us to make choices that can seem optimal, but actually lead to everyone being worse off. This is what Scott Alexander calls the Moloch problem. Consider the current choices facing OpenAI, Google and Microsoft. Each would be better off - and users would, too - if they went slowly to work out the kinks of their AIs. But each also knows that there is a first-mover advantage - and can’t be sure that a competitor won’t release first. So now it’s a race - to release an unvetted AI that might damage their business or consumers, but might also let them hog the spotlight of launching first. Absent a regulator who can appropriately tax the harm created by a bad AI, the three companies will have no choice but to risk catastrophic harms in their pursuit of first-mover advantage.

2. The Externality Problem. This is the classic failure of liberal economics. Imagine a factory that makes widgets. It sells these widgets for $10, that covers its costs and a tidy profit. But to make the widget, they also pollute the public river causing harm to the health of the community and to fishing and tourism businesses that depend on clean water. Without regulation, there is no incentive for the business to pay to clean up its pollution or stop polluting altogether. Absent consumers who suddenly care about a polluted lake, the lake will become toxic at roughly the same rate that the business thrives. That negative impact is an externality of the business. Good regulation forces a producer to account for externalities. It would require the polluter to pay for its impacts that are not represented in a simple widget transaction.

3. The Asymmetry Problem. Decentralized decisions are usually better than a single person deciding what is right and wrong. But good decision making requires each decision maker to have accurate information. Imagine that a firm intends to perpetrate a Ponzi scheme, but the customer has no way to know whether the returns and investments the firm is claiming to make are legitimate. Or, imagine that you are deciding to buy cigarettes in the 1950s while the cigarette companies conceal from you that it might cause you cancer. Without good information, you can’t make good decisions. Without good decisions, the market is just a test in who can run the most effective fraud. Good regulation - that provides customers valuable information on which to base their decisions - is essential to a healthy market.

4. The Power Imbalance Problem. A well-running market also depends on competition to regulate firms. If I can buy a widget from many people, none of them can overcharge me or sell a misleading, shitty widget. But when one firm dominates the market, and controls the supply of a critical good – say, electricity – then I have no choice but to pay whatever they demand and to accept whatever quality of service they offer. Let’s call this the “Comcast” problem. 

So good regulation is designed to help markets do their job more effectively. But even the best intentions can cause terrible outcomes if that regulation is not implemented consistently and clearly. And, uh, the United States has some work to do on that front.

Consider the lingering controversy over Section 230.

Section 230: How America Got It Right and then Fell Asleep at the Wheel

On Tuesday, the Supreme Court heard arguments in Gonzalez vs. Google to consider whether Google should be liable for its machine learning recommendations of terrorist content. This is a case of terrifying externalities. Google profits off of delivering relevant content to its users, but sometimes those users get radicalized and murder other people.

Which, y’know, is not ideal for everyone. 

But, interestingly, the US Congress has previously passed laws that basically shield Google from liability. That law, sometimes called “The 26 words that birthed the internet,” is Section 230 of the US Code:

“No provider or user of an interactive computer service shall be treated as the publisher or speaker of any information provided by another information content provider.”

In this law, Congress weighed the potential of user generated content on the internet and realized that if a platform was to be liable for what its users said, they could never hope to provide an open-forum to millions of people. So Congress acted to protect them while simultaneously enumerating the exact types of content that platforms had to police - child pornography and copyright infringement chief among them.

This approach enabled the entire Web 2.0 revolution. Without it, there would be no messaging apps, no YouTube, no TikTok, no Facebook, no Instagram, no Substack, etc. This was a case of Congress seeing a new technology and giving it the regulatory clarity it needed to develop.

In some ways, Section 230 is a phenomenal example of what good regulation looks like. A democratically accountable legislature weighed benefits and harms, and chose a course that would maximize the former and minimize the latter. USA! USA!

But 230 also demonstrates the limitations of the US regulatory system. In an era of increasing partisan polarization, Congress has not been able to act to clarify the role of algorithms online. When the law was passed thirty years ago, no one understood the power of personalized ranking algorithms. But Congress, today, is too polarized to weigh in on the shape of our digital world.

Justice Kagan herself seemed bemused by this reality, noting that the Court are hardly the nine best experts on the internet (then again, Orrin Hatch asking Mark Zuckerberg how Facebook makes money suggests that Congress is also hardly full of digital heavyweights…).

To their credit, the Supreme Court seems uneasy with having to decide what is in-bounds and out-of-bounds on the internet. They are (in this circumstance) showing some respect for the limits of their authority. Unfortunately, Congress’s other way of avoiding responsibility for decisions is delegating powers to regulatory agencies. And regulators have no such qualms about the limits of their power.  

The SEC vs. Crypto: When Agencies Take Over for Congress

Let’s say you’re the Chair of the SEC. Your duties are to maintain fair and orderly securities markets, to facilitate capital formation and to protect investors. After 90 years, you’ve got a pretty good handle on the capital markets. Sure - people complain about stock manipulation or fraud here-and-there, and no one likes that American companies have to spend ~$4B per year on compliance paperwork, but hey… things could be worse.

Then a new thing comes along. Blockchain technology seems to allow rapid formation of capital, and it’s theoretically transparent. That’s good! But it brings with it a whole host of new fraud and fairness concerns. That’s bad.

And what’s worse is that it seems to fall into a regulatory gray area. 

You think you have a responsibility to regulate it. But many members of Congress disagree. And other federal agencies seem to think it falls under their jurisdiction, as well. That’s annoying, but as long as no one is getting hurt, the debate is largely theoretical. You’ve got a market to manage. 

But then things get sketchy. A massive project collapses. Then another. And finally, a firm that you’ve been consulting with on the development of new rules and regulations gets wrapped up in some serious fraud. 

Suddenly, the people you serve are mad. They want action. They want heads on pikes. And you have some free pikes. 

So you start announcing your intention to pursue actions against whoever you please. You know that fighting your charges will be costly and risky for new entrepreneurs, so you bank on them settling with you. That will establish a precedent in the industry and solidify your claim to regulatory authority without ever having to consult a judge or an elected representative.

This is called regulation by enforcement. Rather than setting clear rules, you create clear examples. It’s also rule by fiat rather than rule of law. It’s in bad taste, even if you set out to protect people. But more than just being irritating - it’s bad regulation. 

In fact, it actively harms the development of good, clean productive markets. 

Good actors lack clarity on how to proceed so they avoid the market entirely. This creates adverse selection - only the sketchy enter the market, at all. This harms consumers and harms the cause of capital formation. 

But it gets worse! To win settlements, regulators focus on technicalities rather than the spirit of the law. Blockchain projects have two ways to achieve the consensus their technology depends on. One is called Proof-of-Work - it’s an expensive, carbon destructive process used by Bitcoin. The other is called Proof-of-Stake, it’s used by pretty much every other blockchain and is far cleaner and cheaper. It is unequivocally better for consumers. But it also might run afoul of technicalities of security law. So in enforcing the law, the regulators create massive negative carbon externalities. Clean legislation would prevent this, but regulation by enforcement can’t avoid it.

And if that weren’t bad enough, regulation by enforcement inherently exacerbates power inequalities in the market. Large firms with large legal teams or well-connected lobbying operations can operate freely, while small firms and new entrants are excluded. That’s the exact opposite of what good antitrust regulation achieves, and it is an inevitable consequence of an unclear regulation by enforcement regime.

In other words, the SEC has chosen the worst of all possible modes of regulation. 

The 800-GPU Gorilla

Look - I get that you might hate crypto or Facebook. And so you look at these two areas, and you say, “Yeah, but so what?” Who really cares if we sell less monkey JPEGs or if Zuckerberg loses a few more zeroes on his net worth?  

That’s fine. You’re entitled to that view. But what should scare you is that these look like the only two channels available for regulating AI. The single most important technology that humans have developed in 100 years will likely be regulated by… outdated laws interpreted in courts or bureaucrats fighting to assert control over new turf. That’s dangerous.

So the question of how to regulate effectively is important. And we need to solve it now. We need to develop an approach that provide a degree of safety for innovators and consumers, while also empowering our government to respond to emergent harms. 

There are no shortage of good ideas. Frankly, many of them were proposed in previous crypto legislation. The challenge is actually implementing them. Here’s a few to get us started:

1. Set clear policy goals. Technologies are going to change. Specific tactical details of regulation will need to change, too. The role of policy is to express intent and objectives clearly. We may not know the mechanism that AI will use to cause harm, but we know that we need to prevent it. Legislating the “spirit” of the law is far more useful than specific proclamations on LLMs or other technology.

2. Set lightweight registration requirements. The joke of last week’s enforcement action against Kraken was that the SEC claimed all that Kraken had to do was fill out a form on their website. The Kraken CEO and an SEC commissioner pointed out that no such form existed. Today’s reporting requirements – appropriate for a pre-digital and pre-blockchain world where disclosures were the only source of information – are often so onerous that they deter companies from going public or even getting started altogether. That’s a major problem.

3. Charter a Self-Regulatory Organization. An SRO enables industry operators to have a first pass at regulating their own industry, and in doing so, to avoid Moloch-traps, while allowing governments the right to intervene if industry self-regulation does not get the job done.

4. Create Sandboxes. Allow innovators to experiment freely, up to a certain scale, and thus, ensure that regulators can both encourage innovation and study potential harms before they reach critical scale.

5. Assign Clear Regulatory Authority. In the absence of clear ownership of regulatory authority, competitive bureaucratic creep will require entrepreneurs to kiss many rings to get their products launched. That’s a recipe for corruption and for stagnation.

Otherwise – well – we can always make someone wave a red flag on your screen before you interact with an AI.

“If you could make God bleed, people will cease to believe in Him… there will be blood in the water, and the sharks will come.” - Iron Man 2

My Dad tells this story about when he “got” the internet.  My brother was doing a school report on the Civil War and Jefferson Davis. It was hard to find books about Davis in our local library. So my Dad typed “Jefferson Davis” into our family’s AOL search and ten thousand results came up. 

It must have been 1996 or 1997.  

Google might have existed, but it was just one among many mediocre search engines, including our treasured AOL.  And then overnight, through its genius use of backlinks to curate the content of the web, Google became the only search engine that mattered.  That’s been true for close to 25 years.

But 25 years of peace breeds complacency. Paranoia is just not a part of Google culture in the way that it is at Facebook. When I joined in 2013, the onboarding manuals there included this directive: “If we don’t create the thing that kills Facebook, someone else will.”

But honestly, why should Google have worried?

The internet has consistently organized around two mediums for serving you from its infinite content-well: a-type-of-feed to push content to you and search to help you retrieve it.

Facebook once owned Feed. But that medium was innovated on by private messaging, by stories and now, by short-form-video.  Each of these offered a way to push content to you that a newsfeed could not match.

But search – search was already the seeming end state of directed content retrieval.

What could be better, after all, then typing in a few words to see all the relevant information ever generated in the world?  

The answer that always lurked in the wings – even as far back as Ask Jeeves – was that you could just ask the internet a question and get an answer. So Google invested heavily in the very AI technology that would power this with its knowledge graph and AI efforts.

And their project worked! Google invented Large Language Models…. They just didn’t bother to productize them. So like a spate of corporate labs before them - Bell inventing Unix, Xerox PARC inventing the GUI - Google is liable to be eaten by the revolution they helped birth.

At least that’s the story, right?  AI defeats Google?  Honestly, this seems wrongheaded.

The biggest threat to Google isn’t that GPT3 is going to replace search.  It’s really not - we don’t just search to generate an answer to a discrete question. The real threat to Google is that Microsoft and ChatGPT have made Google bleed. 

The God of Mountain View is mortal! The blood is in the water and the sharks are coming out. That means it’s game on for Silicon Valley to kill its greatest creation of the last 30 years. The solved problem of search is suddenly looking a little bit unsolved. That’s good news for innovators and bad news for Google. 

Because the reputation of immortality was papering over some pretty big cracks in El Goog’s armor. 

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The Growing Deep Web:  Google’s Content Quality Problem

When I interned at Google, there was a mural on our office wall of a beach and a giant wave coming toward it.  This painting was called Emerald Sea.  The office I was in had been the epicenter of Google’s Google+ strategy one year before – that project was codenamed Emerald Sea.  

I was told that the team had chosen the moniker because of what it depicted – a placid beach with a giant tsunami brewing on the horizon.  The metaphorical storm was forming just down 101 at Facebook’s HQ.

I could tell you that the lesson of that moment is that Google is wrong to fear a shiny challenger. There’s plenty of room for multiple companies to thrive (as long as Apple chooses to allow them to exist). But that’s not the lesson of Google+. The useful insight is why Google was scared. 

It had nothing to do with Google wanting to be the place you share cat memes or your Uncle shares his problematic opinions. 

Google was scared because Facebook’s content and profiles were not accessible from Google search.  

Google had won Web1 because it could index and traverse all of the world’s information better than any rival, but the advent of a password-gated universe of content portended a threat that could prove existential. For the first time, there was a giant walled garden that Google could not index.  And that walled-garden is where most of the world was creating content.  It was not inconceivable that Facebook would end up with a better set of content than the rest of the World Wide Web combined.

That future didn’t happen… for Facebook. But it’s still happening for Google. Because in truth, much of the internet has always been outside of Google’s grasp.  A 2001 estimate said that, at the time, the scale of the “deep web” of unindexed content was 450-500x the public internet. 

That was a world before paywalls or subscription gated content or private APIs or social networks. So the percentage of the internet that Google cannot touch has only risen with each passing year.  That’s bad enough. But it turns out, Google is locked in a vicious cycle that makes it even worse. 

Google is an incredibly valuable traffic source for most web pages that monetize based on ads. There is a lot of money to be made in surfacing shit content that can rank highly in Google. Google knows this so it occasionally changes up the rules of the game by shifting its algorithm. But this just creates a neverending game of cat-and-mouse. So it also tries a different tactic.

It builds out a curated knowledge graph that culls through trustworthy information to surface it directly on the search results page (no clicking required!). GPT3 uses this trick, too. But this takes away traffic from the sites that do actually have good content.  

By eliminating the incentives to game search for ad money, Google has also eliminated the free-and-ad-supported business model that powered the open web. So more and more sites have to restrict their content from the prying robots of Google.

If Google will take their content without paying, then they need to keep Google out.  They need a password gate.  They need to charge for subscriptions.  

This starts a race to the bottom. 

Google fights spammers but in a way that disincentivizes the best content from being available on search. This forces good actors out of the system altogether leaving Google with more noise and ever-less signal. 

Is it any wonder that by 2019, 76% of American news outlets had joined the academic world in implementing paywalls?  Today the best content from news, to music, to streaming, to academic research, is gated behind password protected paywalls where Google can’t access it. And if current trends in culture are any indication - from OnlyFans to Patreon to NFT-gated Discords and Events - this inaccessible deep web is only going to grow.

Google’s business is directly dependent on having the best content available to index.  

But it becomes increasingly hard to index the world’s information when the world is actively hiding the best stuff from your indexers.

If the Open Web is going to fade in importance then so will its chief navigation system. 

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Fragmentation

Imagine that you’re an entrepreneur who wants to disrupt Google.

You could try a full-frontal assault.  

You could try to compete head-on on search quality like Bing.  

You could attack Google on privacy like DuckDuckGo.  

You could aim at a higher-no-ads quality like Neeva.  

But you would have a long road to walk.  Google’s moat and reams of data ensure that it is always going to be very, very good at crawling the broad reaches of the open web.

But there’s another strategy available where Google is already getting its ass-kicked.  From commerce to finding people to searching for bars and restaurants, Google is fighting brutal battles with other search engines.  You just don’t think of their competitors as search engines.

Here’s one:  Amazon.com is the place that 74% of users start their searches for buying things online.  When you consider that eCommerce is bread-and-butter for Google’s ads business that’s uh… scary for El goog.

Or how about this: Facebook and LinkedIn are the best places to find people you know in-real-life online.  People search is basically unusable on Google except to route you to one of those services.

Then there’s Yelp for Local, Kayak/Expedia for travel, Twitter for news, Spotify for music etc. 

And we haven’t even talked about the Youths and their hatred of text content!

Instagram and TikTok are the first stop for searching for 40% of Gen-Z .

Google’s model is predicated on being a horizontal search engine.  It is designed to be the one-stop shop for searching across every intent. But as the internet has grown more and more complex, it’s not clear that a single horizontal search engine can actually dominate across intents.  And so bit by bit, use case by use case, content type by content type,  Google is losing pieces of its empire.

It’s hard to be the best at both universal and specific use cases. Consider Amazon again.  When I search for a pair of sunglasses on Amazon, I get this:

Amazon knows that I came here to buy sunglasses so it lets me start filtering that down. I can filter by brand or by rating or by delivery type or by fashion type.  It uses its knowledge of my very specific search intent to build a verticalized, focused experience.

Google is less confident that I’m searching to buy sunglasses.  I see ads for stores.  I see a link to Amazon.  I see suggested other searches I could make, or some marketing blog posts about sunglass brands. Google isn’t sure if I’m looking to shop, to research, or to learn more about sunglasses (where’s that Wikipedia link?!), it has to offer me lots of options.  

Google goes broad to satisfy any possible intent.  Amazon sells me sunglasses.

The problem for Google is that when I have a frequent intent – like shopping, reading news or looking for a person – I learn overtime that Google is inferior to a specific search intent.  

Google is still my default for less common queries.  That’s good for traffic, but it’s not nearly as defensible a position as being my most-favored-tool for a high-frequency intent.

The Platform Shifts 

The tech world has been starving for the next disruptive platform since the halcyon days of mobile.  A16z bet big on it being crypto (TBD).  OpenAI and Microsoft have bet big on it being AI.  Meta and (sometimes maybe?) Apple has bet big on it being AR/VR. 

 The uncertainty about “What comes next?” is challenging for large tech companies that have massive capabilities to explore, but lots of difficulty in turning their whole battleship toward a trend.

In 2010, Google confronted this threat with mobile.  As they saw mobile searches rise, and Apple’s iPhone taking off with its gated apps, Google saw an existential threat. If the old, decentralized web did not adopt the core innovations of mobile – location-aware, touch and small-screen friendly, sharing and app integrations – then Google was going to have to get them there.  If the web was behind, then so was Google.

The revolution…. took time and lots of capital.  

Google nudged things along by pioneering and pushing Android, then mobile wallets on Android, then giving web developers better tools to make mobile friendly sites.  Then finally they took out the big guns and said that their search algorithm would start to prioritize websites that treated mobile as a first-class-citizen in their design and feature set.

By 2017, over 60% of Google’s revenue came from mobile devices.

Google succeeded in keeping the web, and thus search at the center of the mobile internet universe.  They had limited the risk that everything would become a native app.  But can they pull off the same trick on the next platform pivot?

If Facebook or Apple really create an immersive 3d, live-in metaverse, is Google search going to be the core tool?  By owning the platform, Apple and Facebook will get the first bite at that apple.  And neither has much love loss with Google. 

If AI is truly the next platform, is keyword search and the “document-index” model of the web really valuable?  It doesn’t seem like it.

If crypto and web3 wins, with its decentralized, token-gated data-stack, can Google be sure that they will be the best tool for finding entries on an encrypted global database?  

Any of these shifts could be devastatingly disruptive to Google.  And companies aren’t great at split focus.  So Google needs to pick correctly and bet big.  The problem is – there’s also no guarantee that only one of these trends disrupts everything. 

Even if they’re right on one, the others could pose a massive threat.  Google was designed for the golden era of the web.  But if that era is ending, Google might just end with it.

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What happens now…

Google’s problems are the product of an unstable digital equilibrium.  Today’s web – with open, indexable content, relatively few specialized competitors and a stable set of platforms – is in flux.

Once upon a time, Google was so dominant, its grip on attention and talent so strong, and its coffers so deep that it could fight any war.  But their empire has aged.  It has stumbled. It has shown the world that it can be beaten – even in fields that it pioneered. There’s a reason no company remains on top forever.

Time – and the creative destruction that it enables– is undefeated.

Is it going to be chat-interface sidebar that kills the Giant of Mountain View? Almost certainly not. The technology is too new, the users too unfamiliar and the design paradigm too tacked-on. 

But Google has shown that it no longer has its finger on every vein of technological progress.  That means it’s finally sensible to bet on businesses that could kill them. Heavy is the head that wears the crown. 

In a world where only the paranoid survive, Google has found its fear at a late hour.  Is it too late? We’re about to find out.

The Crisis Point

It was 8:46 AM in Manhattan when the first plane hit the North Tower of the World Trade Center.  Within 90 minutes, three more planes had crashed in the Northeastern United States.

In the face of all the emotions that confronted the US and the world after that day – anger, grief, resolve – I think we often overlook a particularly important one: confusion.

Today, our collective memory of 9/11 immediately transports us from the NY Skyline to the caves of Afghanistan. We parse the tragedy concurrently with the confident and certain action that followed it.

But on that day, there was no certainty to be had. It’s hard to overstate the moment’s collective confusion.  There were no immediate claims of responsibility.  No sense that the attacks were over.  No information on who had survived, who had died.  No certainty at all.

Humans, you see, are surprisingly resilient in the face of certainty. But confusion, uncertainty, paranoia - those are the things of trauma. And collective trauma is disorienting.

Most societies are not effectively equipped to process trauma.  The journey from confusion to sense-making to processing to resolution is long and fraught.  There was (probably for the better) no Twitter that day to aid in instantaneous internet sleuthing. 

But there was another tool that emerged as the gathering place for collective sense-making.

On September 11, 2001, Wikipedia was just nine months old.  It was primarily a hobby-horse for teenagers and young men with too much time on their hands.  But the crisis changed that.  A nation and a world were reeling from a massive traumatic event.

 A link on Yahoo! To the Wikipedia 9/11 page set off a virtuous cycle.  As concerned Americans, with free time, a newly found altruistic impulse, and a desire for sense-making, poured into the site to read and edit the record of that day.  

In the words of one volunteer editor that lived in New York:

“I live in New York City, and this is the small way I can do something in honor of the thousands of people who died, including the 350 firefighters who died because they rushed in to save people, and in respect for the thousands of people working until they drop, exhausted, after literally days without sleep, digging through the rubbish, cutting through the twisted steel, and getting this city back on its feet. . . . And it’s important that we do get back to normal—but also that we don’t forget what happened. And the only way to prevent that is through the preservation and dissemination of knowledge, the reason for something like Wikipedia.”

In the aftermath of one of the most tragic days in American history, Wikipedia connected to something deep in the collective psyche of America’s 140M internet users.  It attached itself to the human need to make-sense, to tell stories, to shape our understanding of the chaos around us. 

In doing so, it found its early missionaries.  It has never looked back.  

Wiki to Web3

Why do we Web3?

Why do we put up with the assholes who shill tokens on Twitter? Why do we not turn away in the face of the judgment of friends and family who ask why we bother with monkey JPEGs? 

We do it because we believe that the thing that has made the greatest difference to humans is finding new ways to work together, to trust each other, to build great things.  We do it because we believe that human coordination is the most important design space that has ever or will ever exist.  We do it because projects like Wikipedia remind us that humans, when brought together by common purpose and the right technologies, can create so much more than any single individual.

But Web3 mistakes itself when it thinks that it somehow invented internet coordination.  The most impressive, most enduring, most important internet community that creates untold value out of the ether is not Bitcoin or Ethereum. 

It’s Wikipedia.

Wikipedia is the single-most up-to-date, exhaustively curated collection of human knowledge ever created.  It has 6.6Million English articles and continues to add 17,000 new articles every month.  If published in the same style as the Encyclopedia Britannica, it’s estimated that Wikipedia would require 3220 volumes. 

And all of that that content is added exclusively by volunteers.  Not a single person is paid for editing or contributing to Wikipedia.  But for some reason, 130,000 people edit it every month.

By any rational model of human productivity, Wikipedia shouldn’t exist. 

Sure, I can construct a model as to why people would contribute to one of the most trafficked websites in the world today.  But how does it get started? 

Wikipedia is the perfect trap for a cold-start problem.  No one should have wanted to be one of the first 100 people contributing to this thing. Why would I invest time in writing one of the first articles on a website that gets very few visitors? Why would I bet that I am contributing to something that could be of earth-shattering importance? Who stays up at night thinking it would be fun to write an encyclopedia? 

No economist would have a good answer for that. It’s totally irrational. And the orthodox thought of the Web3 community agrees.

In one of the most influential essays for Web3, Chris Dixon of A16z argues that the superpower of Web3 is that we can use financial incentives (in the forms of tokenized ownership) to encourage our initial users to bootstrap a network. More concretely: Chris suggests we could pay the first 100 users to kickstart Wikipedia.  Over time, the value of our Wiki can become self-sustaining so the token incentives can taper off:

This theory is derived from the success of Bitcoin. Early users of Bitcoin received massive amounts of token and were incentivized to use them and spread the gospel of Bitcoin to make the value of their treasuries grow.  

So, dutifully, hundreds of new crypto projects each year airdrop tokens to early adopters hoping to start spinning that flywheel.  Consider, for example, an interesting project that A16z invested in called Helium.

Helium used the promise of financial rewards to get over 1 Million internet/data hotspots installed around the world.And yet… only $6,500 worth of Helium credits were purchased to use that same network as of July 2022.  

The natives of the Helium network have grown restless as their token subsidies dropped and the promised users never materialized.  This is because Helium is fundamentally a community of mercenaries.  And mercenaries may help to augment the ranks of true believers, but they are not a substitute. 

If you want to change the world, you have to persuade people that you are imagining a world worth building.  And that’s the real lesson that Wikipedia has for Web3.

A Brief History of the Wiki: From Nu to New

In 1995, Ward Cunningham was helping to maintain a community of 500 web developers on the Portland Pattern Repository.  He wanted to offer the developers a way to easily add their own content to the site. So he created a way to directly edit text on the website. Cunningham remembered that Wiki meant quick in Hawaiian and he liked that Wiki Wiki Web matched the “WWW” of the Worldwide Web.  The Wiki was born.

Four years later, Jimmy Wales had been experimenting with Web Rings in his startup.  Web Rings were user-curated lists of links.  Kind of like an open source Yahoo! Directory.  But Jimmy had a different idea.  What if, rather than just curating links, people actually built out pages about the topics that they knew about?  What would an open source encyclopedia look like?

Naturally, Jimmy thought, quality would be a massive concern.  So when he launched Nupedia, he hired a PhD candidate to oversee a seven-step editing process.  It would be like peer review for the internet.  Anyone could edit, but the process would ensure only the highest quality content got through to end-users.

It was a flop. 

In its first year, it had 21 articles. So the company tried a different experiment to drum up more content as a “feeder” for Nupedia.  They adopted the “wiki” tech to let anyone directly edit pages. 

They called this side-project Wikipedia. It was considered by the Nupedia team an unserious, if interesting experiment. But it took off. In its first month, January 2001, it had already 10x the articles of Nupedia. 

In its first year, it had 18,000 articles.

After 9/11, Wikipedia never looked back. Communities formed to write and edit articles covering every conceivable topic.  Just as impressive, Wikipedia has largely avoided the disinformation controversies that plague other Web2 giants like Facebook, YouTube and Twitter.  

It does so because its engaged community of editors scrupulously debate to ensure something approximating neutrality.  The contributors of Wikipedia are on a mission to collect and curate human knowledge. They are not interested in making a Wiki-token number go up.

Whereas the profit incentives of Web2 networks reward virality and outrage, Wikipedia’s strong mission-focus and the adoption of that mission by its community of editors keeps the website pointed at its true north.

Missionaries > Mercenaries.

It’s reasonable to ask, of course, if the altruistic motivations of 9/11 editors would wither and die in the decades since that day.  There has been a longstanding debate over the motivations for why people, for example, contribute to open-source projects.  Many economists point to the reputation building or network building effects of contributing to prominent projects.

But research on Wikipedia suggests something different.

In a 2007 survey, Wikipedia contributors were asked to select among six possible motivations for their work on Wikipedia.  The typical contributor (overwhelmingly young and male) was spending an average of 8.27 hours per week contributing. 

While ideology and values were important to initially getting involved, the most important determinants of who contributed their time and energy to Wikipedia was how fun they found it, how much it helped them achieve understanding, and how much it made them feel needed.

Fun. Mastery. Feeling Needed.  

By appealing to these human needs, Wikipedia has built an army of missionaries. No token required. 

Lessons for DAOs

All well-and-good, you might say, but wouldn’t Wikipedia also grow faster if it paid its most valued editors?  Couldn’t they just do an airdrop or set up some quests to offer edit-to-earn rewards?

Well, not so fast.  Volunteers, it turns out, don’t respond well to being treated like mercenaries. 

In their 1999 paper, Does Pay Motivate Volunteers?, University of Zurich Professors Bruno S. Frey and Lorenz Goette analyze Swiss data that looks at charitable work done by volunteers versus paid contributors.  What they find is that pay can encourage higher contribution than altruistic volunteering – but only when it crosses a very high threshold. When workers are rewarded with small amounts of money, it crowds out the self-esteem boost they get from doing volunteer work.

Put another way, the “mission” has a high value to people.  When you pay them, you undermine the value they get from contributing to that mission.  You reduce missionaries to mercenaries, and they don’t love that.

So what does this tell us?

It tells us that Dixon’s model needs an update.  To bootstrap a network, you need to either provide early adopters a massive financial stake – (sup Web3 VCs) – or you need to offer them non-monetary value.  You need to convert them into missionaries.  

In truth, this is the real lesson of the most successful Web3 communities.  

Bitcoin, for example, did not start as a way to make bags of cash on Robinhood.  It started as a libertarian, privacy-aware, computer science experiment.  It gained traction in this community of true-believers first.  Then it spread to users in adjacent markets who felt these needs.  Then it attracted the speculators who helped scale the network by shilling their own holdings.

Look, those speculators played an important role in scaling the network.  Bitcoin would not operate nearly as smoothly without the capital investments of profit-motivated miners.  But a set of mercenary miners without a missionary core would have been DOA.

There’s just no substitute for the alchemy of true intrinsic motivation.  Man does not live on tokens alone.  Instead, the most successful online communities understand that their project is to create initiatives that excite our souls, that make us feel needed and like we’re part of something great.

The money, it turns out, is just a sweetener.

Paul Krugman’s Ghost

In 1998, Paul Krugman infamously predicted that, “By 2005 or so, it will become clear that the Internet's impact on the economy has been no greater than the fax machine's."

This quote gets bandied around anytime Krugman (a Nobel laureate) has the gall to suggest he might know a thing or two about how the future might play out.

There’s a lesson here: predictions on the future impact of technology are a fools’ errand. No matter your future success, these predictions will be retrieved thirty years in the future to demonstrate that 1. you are dumb and 2. That no one should take your predictions seriously.

And yet - I can’t help following in Krugman’s footsteps.

Sigh.

Okay enough throat clearing.

Here’s my prediction: when the dust settles, we will see that GPT3 - far from heralding the start of AGI and the singularity and whatever other dreams may come - has been as impactful to the world as the invention of the humble calculator.

The Electronic Calculator

This is not actually a knock on GPT3.  

Calculators, while commonplace today, were an incredibly important technology! And, like AI, they took a while to reach their present form. Mechanical calculators were invented in the 17th Century by Blaise Pascal. An 1857 GQ review of the hot-new Arithmometer celebrated:

“A multiplication of eight figures by eight others is made in eighteen seconds(!); a division of sixteen figures by eight figures, in twenty four seconds; and in one minute and a quarter one can extract the square root of sixteen figures, and also prove the accuracy of the calculation. [...] It is not matter producing material effects, but matter which thinks, reflects, reasons, calculates, and executes all the most difficult and complicated arithmetical operations with a rapidity and infallibility which defies all the calculators in the world.”

But these devices were not modern calculators. They were more like powerful abacuses.

Things became more interesting with the first mainframe computers in the 1940s. Now we had digital calculators – even if they were the size of a garage. By 1961, the first office-sized electric calculators were sold in the United States for a whopping $2200. 

This is where things start to mimic our moment. Because the digital calculator touched off a panic. The NYT wrote, in 1950, that these electric brains were going to eliminate the need for human labor. In February 1962, President Kennedy claimed that automation was the job problem of the 1960s. See, you might trust your handy calculator app now, but at the time – that robot brain was coming for human jobs!

But at least those computers were massive and inconvenient. And then in 1969 TI introduced the Cal Tech, a calculator that could fit in the palm of your hand. By the early 1970s, the modern handheld calculator was available for a few hundred dollars. 

By the end of the decade, the price had fallen to under $10.

Accountants, human computers, engineers – all must tremble before the mighty power of the calculator and its command of mathematics! 

But the thing is – the automation apocalypse didn’t happen. 

At least not really. Because the calculator augmented rather than supplanted human capabilities. It provided a simple, accessible tool to automate the rote work for workers in quant fields. It was no more and no less than a productivity tool.

Productivity tools are important. They should and do change the way we work, the way we teach and lay the groundwork for emergent revolutions. The calculator did all three. 

Education

In 1986, Connecticut became the first state in the Union to require the use of calculators on state exams. The discussions had been contentious. Many educators believed that American students were already numerically illiterate. In an echo of Plato’s critique of writing, they believed that students who used calculators would never learn to calculate themselves. 

Parents joined their chorus – after all, the way they learned math had been good enough for them! Their kids were just going to type in numbers and get all the answers? 

No way. Not my kids. Not in my country. This is America.

But the State School Board saw it differently.

By allowing students to focus on problem solving rather than computation, schools could shift the focus of education to learning how and when to apply calculations. 

The State’s Mathematics Department Head, Mr. Steven Leinwald, told the NY Times that: “teachers will be able to move beyond pencil-and-paper drills that teach rote computation skills such as addition, subtraction, multiplication and division. Instead, they could focus on the more complex problems, such as problem-solving and estimation, which are areas in which national and state tests have indicated that students are in dire need of learning.”

Education had to change because the world had changed. Of course, this shows up again today as we debate if GPT3 necessitates a change to writing college papers. Which.. Duh.. of course it does. 

There are certain writing skills – formulating an argument, summarizing a point – that can and should be tested in classrooms (just as certain math exams do not allow calculators). But the beauty of the new technology is that it accelerates the boring part of the work to help us focus on the parts that still require human experience. Indeed, it helps us focus in on what actually adds value in modern writing – connecting disparate ideas, generating novel insights, connecting to personal or social experience to make your text relatable.

Just like the calculator, the advent of LLMs allow us to get past the basics of writing and research, to do the more thoughtful work underneath. The five paragraph essay may be consigned to the dustbin of history. But would that really be a bad thing? 

The Industry Impact

If you’ve seen Hidden Figures, you know that NASA once depended on literal human-computers to get us to the moon. Astronauts didn’t trust slow and onerous machine calculations. They wanted humans doing the work and checking machine calculations. 

But this work wasn’t done by NASA’s top engineers. NASA’s brass considered themselves above mere calculations. They entrusted the work to the employees they called “computers.”

As electronic calculators and computers matured, those jobs died out. But it was not a pure loss. Many of the more talented “calculators” moved into engineering where their skills – often overlooked in favor of their calculating ability – could be put to better use.

Now - this is not a purely rosy story. Many jobs were eliminated. Talented engineers – who could now do the calculating work and the engineering work – were even more valuable than before. Lower-skilled workers who performed the automatable tasks lost their jobs. The rich became richer, and the poor poorer.

But the mix-shift is more complicated than that. The diffusion of calculating technology into related fields accelerated the growth of math service jobs. Between 1970 and 1990, the fastest growing relative sectors of the US economy were in finance, insurance and real estate. The democratization of calculation helped power the financialization of the American workforce. 

Those jobs were new and they were higher paying. Inequality increased as we eliminated a middle-class segment of knowledge workers, but unemployment did not. 

We should expect a similar transition in a post-GPT3 world. The number of artists and writers who can produce high-quality work through a combination of leveraging technology, leveraging their taste and creating work that can connect with an audience will see their earnings and their impact rise. Those who crank out machine-quality output are likely to be displaced. 

And increased inequality will likely result. But the rise of these technologies will also empower a new generation of careers – artists who lack fine-motor skills, writers who can build immersive universes of fully realized characters – that will boost overall economic well-being.

The Adjacencies Boom

Perhaps the most profound impact of the calculator boom was not about calculators at all. 

It was about the potential other uses of their insides. In the race to develop better personal calculators, computing technology matured. The first use of transistors outside of audio engineering was in electronic calculators. TI and HP developed programmable pocket calculators that introduced a generation of kids to programming. And perhaps most importantly – the calculator era was critical to the rise of a startup called Intel.

The Japanese company, Nippon Calculating Machine, wanted a versatile chip that could be used in all sorts of calculators. They heard about a young, scrappy startup called Intel and asked them if they could meet the design spec. Intel lied (they had never done anything like that before) and said that they could. But in trying to realize their promise, they ended up inventing the first computer on a chip – or as we know it today, a microprocessor. 

Those microprocessors – made of silicon – would give their name to the region which would take the small dreams of the calculator and turn it into a computer revolution: Silicon Valley.

But it all started with a calculator.

So… what comes next? From Turing Test to Turing Completeness (Again).

All of this is to say, GPT3 is not the revolution itself. It is the starting gun. It is a taste of what is to come.

LLM advocates like to say that this is moving the goalposts. GPT3, after all, is probably the first artificial intelligence that can really be said to pass Alan Turing’s famous test.

But Turing’s test was itself, a product of its time and a limited view of human intelligence that focused on our capacity for language. The ability to generate “correct” sounding language, while impressive, is not sufficient to really count as “intelligence.” Language is a set of symbolic representations that we use to communicate the underlying concepts that exist in our brain. It is a translation mechanism that transforms concepts into recognizable symbols and back again.

GPT3 has built that communication layer. But it still lacks understanding.

This objection is most famously formulated as Searles’ Chinese Room. Searle imagines a human asked questions in Chinese while hiding, concealed in a room. Our hidden human is fed answers in Chinese by a machine. The human is thus able to always produce a right enough answer without understanding anything of what he is saying. This, Searle argues, is the problem with Turing’s test. Just because a machine can give you the right words in Chinese, doesn’t mean you can speak Chinese. 

But how do we model understanding? Turing reduced the thinking question to a speaking question. What is a similar useful test to parse what comes next? 

Turing also wrote another paper in which he developed a concept called Turing Completeness. To be Turing Complete, a computer needs to be able to represent any abstract symbolic logical system completely in a step-by-step algorithm.

Turing Completeness is what separates a computer from a calculator. A calculator can perform a set of discrete mathematical functions – addition, multiplication, subtraction, division, etc. But it cannot manipulate symbols in an arbitrary set of logical transformations forever. For that it needs the ability to test conditions, to change variables, to iterate or recur through functions. 

A computer that has those properties can complete any arbitrary calculation and is said to be Turing Complete. Every modern computer is Turing Complete. 

To separate GPT3 and LLMs from the more general intelligence technology that could really change the way we do all work, we need a similar test. We need software that can understand – not because it can perform generative tricks – but because it can represent and manipulate underlying concepts with arbitrary precision.

I am not an AI research scientist. So I can’t tell you if an LLM with an order of magnitude more parameters could achieve this goal – but I tend to doubt it. Humans have multiple forms of intelligence. We can manipulate logic, we can use language, we can test and discern, we can learn through embodied physical experience.

My strong hunch is that we will need to develop an LLM that can generate individual insights, then use other intellectual capacities – classical logic and causal reasoning, skeptical adversarial testing, and yes, the capacity for language to translate and generate symbolic representations – to achieve the general purpose intelligence that GPT3 and Stable Diffusion hint at. 

The calculator is great, but the microprocessors it inspired and the computers that they powered – well, those really changed the world. They just took a little longer to arrive.

Of Birds, Crocodiles and Frogs

On January 13, 2022, a handful of popular third-party Twitter apps silently stopped working.  

TweetBot and Twitterific might be little known to your typical Twitter user. But for many of the media-types that dominate Twitter, they were essential tools.  And the developers of those apps had no idea what was happening.  Some assumed it must be a temporary outage.

When word came, the news was not good.  Apps that replicated any part of the Twitter experience would no longer be tolerated.  

In a way, the move makes a lot of sense. Twitter is an advertising business. When eyeballs are not on Twitter apps, Twitter loses money. But the move reads as ungrateful for a company that, in many ways, has its third-party developers to thank for its growth.

Twitter’s first mobile apps came from third-party developers. The Twitter bird came from Twitterific, as did the word “tweet” and the invention of replies/comments. Twitter’s cultural impact and its technical development relied heavily on the work of independent developers. 

But those developers forgot the lesson of The Crocodile and the Frog.

“There once was a frog who longed to cross a fast-flowing river filled with snakes. He hopped along the bank, searching for a fallen log or narrow point, but found nothing. After many days, a crocodile appeared. He listened sympathetically to the frog's story, then offered him a ride.

"You'd eat me, or leave me in the water where the snakes would eat me," the frog said. The crocodile insisted his motives were benign. "If you're worried, ride on my tail."

That sounded reasonable, so the frog hopped on the crocodile's tail. But it soon became apparent that the crocodile needed its tail as a rudder. "Hop onto my back so I can steer properly," the crocodile said. The frog moved up and they made good progress. "Why don't you hop on my head?" the crocodile asked. "The view is better."

This made the frog nervous. The crocodile dismissed his fears. "Surely you don't think I'd eat you when we're halfway across." So the frog climbed to the top of the crocodile's head.

Then the crocodile complained that something was tickling his nose. "Would you check?" he asked. "I'm afraid I'll sneeze and send you flying,"

The frog hopped onto the crocodile's snout and, in one gulp, he was gone.”

Twitter’s decision puts an exclamation point on a truth little acknowledged, but quietly understood by startups – that the giants of Silicon Valley may offer you passage across the river, but they also won’t hesitate to gulp you down if it serves them.

Web2: Create, Exchange, and Extract

Web 2.0 wasn’t supposed to be this way.

Tim O’Reilly articulated the promise of the new era when he explained that while Web1 was built on delivering services to millions of users, Web2 was about leveraging the web’s capacity for collective intelligence.  

Google succeeded because it leveraged links created by users for its PageRank.  eBay aggregated the listings of thousands of sellers and their rankings/reviews. Social Media was starting to do the same as we shared photos, blog posts, and gradually everything else online.  The secret to the new internet was collaborating with your users and other developers to build an ecosystem.

The playbook that emerged - for Facebook, for Google, for YouTube, for Amazon’s Web Services and yes, for Twitter - was straightforward, if hard to execute.

It worked something like this: 

The new company built a new tool with some kind of novel functionality.  It used that novelty to attract users’ attention and data.  The company then turned around and licensed access to that attention or data via an API. This enabled other developers or content creators to generate novelty on the hosting platform, which would in turn, generate more attention and data while growing the new feature.

New startups offered novelty to established businesses in exchange for that business’s attention and data-stores. These virtuous networks of exchange powered the exponential growth of many new products – like Zynga and Instagram (which grew on the back of Facebook) and, more recently Substack and Clubhouse (which grew on the back of Twitter).

But, there was a time-bomb lurking just out of sight that threatened to end this infinite game of trade. That would be monetization. 

Growth was positive sum – many platforms could succeed together.  But value extraction was zero sum. If I give attention to your product, I can’t turn it into profits myself.

Suddenly, the assets collected by the major platforms – attention, data and functionality — were not goods-for-exchange. They were leverage to extract rents.  These assets could no longer be given away for free or next-to-nothing in a virtuous exchange.  

Attention had to be traded for ad dollars.  Data and functionality had to be traded for developers’ dollars. Facebook shut down Open Graph. Twitter restricted access to its firehose API. And Amazon did the same with its Marketplace APIs.

The builders and the VCs of the era paid attention.  When it became clear that any major platform could and would shut down a business that depended on their services, it became impossible to invest in the developers building on these platforms.

The Web2 model is a tragedy of game theory.  Because a firm needs to eventually generate monopoly profits, they have to eventually restrict access to the very same open-assets that helped them build their empire.  And once firms demonstrate that this is the inevitable path, no one will bother to build on newer platforms.  The result is a cycle of under-investment, under-innovation and stagnation. Rather than a composable web, we end up with a stagnant one.

This dynamic even threatens AI startups, the buzziest space of our present moment. OpenAI has out-innovated large companies to debut some of the most impressive tech we’ve seen in a decade.  But businesses that want to build on this platform are not venture investable.  After all, if OpenAI owns the platform, and they can raise API prices or restrict access at any time, how will a new business ever be able to extract sufficient profits to justify venture returns?

In contrast, the open protocols continually mint new Unicorns. Humble email continues to offer a substrate for startups like Superhuman, MailChimp and Substack some fifty years after the original development of electronic mail.  

The Third Way 

If Web3 works, and that is a big if, it will be because its approach to building platform technology offers a way out of this negative Nash equilibrium.  Web3 provides a way for developers of new technologies to credibly promise not to change the rules of the game when they need to make money later.  

This is, of course, what confuses so many commentators about Web3.  It is not a technical solution to a technical problem.  It is a technical solution to the social problem of credible commitments.

Twitter’s API can do anything that a blockchain can do and it can do it faster.  What that API can’t do is make credible commitments not to revoke access or to raise prices.

Smart contracts are APIs. But they are immutable once deployed to a blockchain.  This means that an API that works a certain way, at a certain price point will have to work that way forever. 

This allows developers to make open-ended commitments to the people who build on their technology. And that means that businesses built on these platforms are long-term viable for investment. It opens the door for applications that compose these platforms together, not because of novel technology, but because of novel mechanisms for trust.

This is, of course, just a lot of buzzwords.  So let’s get concrete about the types of businesses that could be built on Web3 platforms. 

1. Clients/Aggregators A reliable Twitter API with blockchain encoded access-points would allow the development of better Twitter clients – much like it did with Twitter’s first mobile app.  They could also breakdown the barriers between different services altogether.  Today, apps are hacking ways to interoperate with existing networks – like Texts.com, but these depend on somewhat illicit backdoors. The dream of a singular inbox that can solve our app fatigue has been intractable in the dynamic world of Web2.  But Web3 protocols and trustable smart contracts might finally make it come true.

2. Composable “Custom Games” In 2003, Blizzard released the third title in its popular Warcraft series: Warcraft 3.  The game was a smash hit, becoming the fastest selling video game of all time.  Warcraft 3 was a simple real-time strategy game – build a city, build an army, go to war.  But what made Warcraft 3 iconic was its Custom Games feature. It enabled hobbyists to easily design custom maps, set new rules and otherwise build totally new games – some of which created entirely new gaming genres: Tower Defense and DotA.

   

   
   
   But Blizzard also forbade developers from selling or profiting off of these custom games.  So rather than spawning a sustainable ecosystem of new games-within-the-game, companies copied these game concepts wholesale and launched them as independent titles. It was a loss for players (who invested time and energy into the early games on Warcraft) and for the developers who designed them.

But it’s not all great news. 

Web3 solves one of the Web2 platform problems with credible commitments.  But it does so in a way that limits the rents that entrepreneurs can extract.  And while that might be good for users, it’s not great for speculators or would-be Mark Zuckerbergs.

There lies the paradox at the heart of Web3:  millions of speculators are betting on ecosystems that can only realize their paper valuations if they, too, can extract monopoly profits.  But the Utopian promise of Web3 is predicated on building in a way that will prevent that extraction.  

Web2 turned away from its idealistic promises when it was time to make money.  Web3 has slammed the door on this Web2 escape path. But it doesn’t have a viable alternative for empire builders.

One path, of course, is to own the substrate on which the new technologies are used – that’s why there are so many blockchains like Ethereum, Solana, Polkadot, Aptos, Sui, etc. competing for shares of the pie.

But for app developers, the path is more circumscribed.  For all the money made on Web3 speculation, it remains a mostly unsolved problem.  There are a few concepts gaining currency with builders:

1. The Hyperstructure Model  - Popularized by Jacob Horne of Zora, “Hyperstructures” are a model of value extraction wherein ownership is valuable because a community could activate a fee-switch.  The desire of other users and stakeholders to stop them from doing so gives share ownership value.
   

2. The Support/Convenience Model.  Many open source software products profit by offering a version of their platform with tech support for enterprise customers or hosting or a better UX.  For example, Word Press is a free and open platform for building websites.  WordPress.com, however, offers hosting, and a friendlier UI for fees.

Of course, Web3 could also follow an altogether different path than Web2.  Maybe Web3 businesses will be uninvestable precisely because they have succeeded at preventing rent extraction.  If that’s the case, and Web3 succeeds anyway, it will be all the more remarkable for creating an internet where independent developers, rather than VCs and unicorns dominate.

After all, the only trustable crocodile is one whose mouth has been bound shut.

I spent this weekend bingeing The Traitors on Peacock.

A group of 20 contestants tries to suss out three traitors amongst them while living in a dreary castle in Scotland.  The traitors “kill” one of the contestants every night.  If the “faithful” find and vanish the traitors before the traitors kill them all, they win a $250,000 prize. If not, the Traitors split the prize.  It’s like Mafia, Werewolf and Among Us had a love child with MacBeth.  It’s wonderful.

Each episode, the paranoid contestants are grasping at straws to find a traitor. Every gesture, every sentence is rendered meaningful.  There are no coincidences to the paranoid mind. 

And today’s internet – above all else – is paranoid.  That paranoia might have started on the fringes – in QAnon forums and 9/11 Truth websites – but it has moved decisively into the mainstream.  It has even infected many of the internet’s main characters.

Elon Musk got in on the fun in October when he implied that Paul Pelosi had not been attacked by a crazed extremist but was, instead, a victim of a lovers’ tiff with a male escort, writing: “There is a tiny possibility there might be more to this story than meets the eye.” He linked to a story containing the claim.

Elon-friend, investor and inventor of the modern browser, Marc Andreesen, also tweeted: 

I find this trend fascinating (if, y’know, terrifying).

Because this season of Twitter and this season of Traitors both highlight that we’ve been lied to about who believes conspiracy theories.

For years, the dominant narrative has been that conspiracy theories prey on society’s most vulnerable.  The internet, we’re told, profits off these poor souls’ fears by spreading extreme paranoia and mass-delusion to generate ad clicks.  

Bad, Facebook.  Bad, Twitter.  

If you work on digital coordination technologies – like social networks or DAOs – this should give you pause.  I subscribe to a baseline optimistic view of human nature. I believe that online communities are overwhelmingly a public good. I believe that giving online communities tools to translate their values into real world impact is a profoundly positive step for humanity that will lead to a world that better aligns with the angels of human nature.

But if I’m wrong – if people are crazy and social networks are making them craziers, then the invention of online community tools and tools for turning belief into capital and capital into action (like crypto and DAOs) are likely to lead to more events like January 6 or the riots in Brasilia this month.

Considering this question – whether the internet makes dangerous conspiracy theories more dangerous and if that impact can be tamed – has become one that keeps me up at night.  This week, I decided to share what I’ve learned.

The Paranoid Style in American Politics

“American politics has often been an arena for angry minds,” Richard Hofstadter wrote in Harper’s. “In recent years we have seen angry minds at work mainly among extreme right-wingers, who have now demonstrated in the Trump movement how much political leverage can be got out of the animosities and passions of a small minority.” 

This essay isn’t recent.  It was written in November 1964.  The only word I changed was replacing the name “Goldwater” with the name “Trump”.  

And even then Hofstadter’s point was that the “paranoid style” was a persistent feature of American politics.  

In 1951, Joseph McCarthy blamed the “perilous” standing of the United States on communist infiltration. In 1895, the Populist party complained that an international cabal of gold speculators was manipulating markets and holding the working class hostage.  Before that, it was fear of Catholics, Masons and the Illuminati infiltrating the country and steering the ship of state.

Deep state. QAnon. It’s all the same story. It’s a paranoid delusion as old as the Republic itself.

But, if that’s the case, we still need to reckon with why these conspiracies seem so prominent today.  Isn’t the internet fanning the flames of these conspiracies?  Isn’t it the case that a fringe media can increase its distribution and further radicalize good, honest Americans?

It’s a good story.  But the problem is… it’s just not supported by the data.

In a July 2022 study, Joseph Uscinski, et al. published an analysis of surveys tracking beliefs in various conspiracy theories over time.  The time horizons ranged from several months (in the case of COVID conspiracy theories) to several decades (in the case of JFK-assassination theories).  

What is new – what has changed – is that we are focusing on these stories with increased urgency.  That’s partially because we had a President who openly flirted with them.  It’s also because – through the magic of social media – we are finally able to see what our fellow countrymen believe en masse.  And it turns out, people be crazy.

So what looks like internet virality is really just internet transparency.  For the first time, we can actually see how crazy our fellow countrymen are.  And the answers are just a bit shocking.

Which prompts two questions for me:

1. If Americans have always been conspiracy theorists, then why is it that we are so vulnerable to conspiracy thinking?

2. If we can finally see all these conspiracy theories operating in the open, then can we learn how to protect ourselves from them?

Question 1:  Why are we so vulnerable to conspiracy theories?

In a separate paper, published last month in Nature, Uscinski analyzes the characteristics that correlate with beliefs in conspiracy theories. 

There are some obvious influential personality traits – populism (distrust of authority), Manichaeism (belief in absolute good and evil), and the dark triad: psychopathy, Machiavellianism and narcissism. 

 It seems unsurprising that people that believe in absolute good/evil and have dark personality traits are likely to believe in conspiracy theories.  Psych 101 tells us that we see things as we are not as they are.  

People who believe in good/evil and have a tendency toward manipulation and anti-social behavior themselves are likely to project those traits onto everything they see.  

I like to think of this as the “Michael Jordan” theory of conspiratorial thinking.  As Jordan was famously memed (and misquoted) as saying:

People with narcissistic traits believe every slight is about them.  If an unfavorable news story is published (Elon), you’ll tend to believe that there’s a conspiracy against you.  If globalization has eliminated your job, it must be because someone wants to destroy your community.

People with their own anti-social traits are likely to imagine that they would do something sinister with power, and thus are likely to see sinister intent in other powerful people.  To the paranoid mind, there are no coincidences, only personal attacks.  Like Michael Jordan, the paranoid mind invents a pretext for revenge and anger.  Unlike Michael Jordan, they take to the internet rather than the basketball court.  

If I dislike someone, I’m more likely to believe or want to believe they’re doing something sinister.  But it’s here that an important tactic of conspiracy theory growth comes into play – guided apophenia.  It is best described by game designer, Reed Berkowtiz, describing an early game of his that involved a treasure hunt:

“The object they were looking for was barely hidden and the clue was easy. [...[

As the participants started searching for the hidden object, on the dirt floor, were little random scraps of wood.

How could that be a problem!?

It was a problem because three of the pieces made the shape of a perfect arrow pointing right at a blank wall. It was uncanny. It had to be a clue. The investigators stopped and stared at the wall and were determined to figure out what the clue meant and they were not going one step further until they did. The whole game was derailed.[...]

I stared in horror because it all fit so well. It was better and more obvious than the clue I had hidden. I could see it. It was all random chance but I could see the connections that had been made were all completely logical. [...]

These were normal people and their assumptions were normal and logical and completely wrong. [...]

QAnon grows on the wild misinterpretation of random data, presented in a suggestive fashion in a milieu designed to help the users come to the intended misunderstanding. Maybe “guided apophenia” is a better phrase. Guided because the puppet masters are directly involved in hinting about the desired conclusions. They have pre-seeded the conclusions.” 

What’s new about the internet isn’t that it spreads beliefs in questionable ideas.  That happened long before we invented dial-up.  What’s new is the ease with which individuals can “do their own research” to confirm misleading clues laid out for them by a puppet master.  And we believe things we research for ourselves, especially when it aligns with our preferred worldview.  Confirmation bias, after all, is a hell of a drug.

In a 2021 letter published in Journal of the American Medical Association, researchers analyzed public Facebook groups that were spreading COVID misinformation.  They expected to find scientific illiteracy.  Instead, they found a surprising degree of savvy.  People were deploying statistical techniques on public datasets to “unskew” data to arrive at their preferred conclusions.  

The people who believe in conspiracy theories aren’t dumb.  They’re motivated reasoners.  That distinction is critical when we think about how to combat misinformation.

Question 2:  How can we protect ourselves from believing in conspiracy theories?

The internet has actually provided us a tremendous gift for fighting misinformation.  For the first time, we can see the tactics used to evangelize.  In the process of spreading, these systems of belief make themselves legible to us, and in doing so, they expose ways to protect ourselves from their corrosive effects.  Social media is not just a vector of infection, it’s the microscope that lets us see the virus and visualize its weaknesses.

So far we’ve spotted two strategies to intervene.

The Best Medicine is More of the Disease

If there’s one ironclad finding on how to combat conspiracy theories, it’s this: you can’t persuade someone by showing them evidence that they’re wrong.  Why?  Because attacking someone’s beliefs is perceived by the mind as an attack on the individual themselves.  

In 2016, researchers Kaplan, Gimbel and Harris published an article in Nature, showing that you could literally see the brain shutdown its networks for processing new information and changing beliefs when threatening counter-evidence to a core belief was offered.

So what do we do instead? 

According to an NPR interview with Diane Benscoter, a former cult member who now helps deprogram conspiracy theory believers, the first step is to make the other person feel safe. Then you build on the idea of “doing their own research.”

Instead of offering an alternative rendering of the facts, you can start seeding some ideas that enable the person to do their own research.  If a person talked themselves into a conspiracy, they’re going to have to talk themselves out of it.   And the best way to do that is to gradually guide them to poke holes in the conspiratorial trap.

Inoculation

The best defense is preventing the disease from taking root at all.  Most researchers advocate techniques they call “inoculation.”  

Just like its biological cousin, misinformation inoculation exposes individuals to weakened versions of misinformation to train our psychological immune system to recognize techniques used to manipulate our beliefs by teaching people about the rhetorical strategies that bad actors employ – emotionally manipulative language, common logical fallacies, false dichotomies and scapegoating.  

The early results of this approach are promising.  An article published in Science tested the efficacy of a series of YouTube videos on training people to recognize and refute misinformation.  Showing the videos as ads on YouTube, and then testing the viewers’ ability to discern misinformation, showed that viewing a single video could move misinformation recognition by ~9%.  

That’s not enough to end the Paranoid Style in our politics.  But it’s a sign that we might not be doomed to a world of QAnon fantasies forever. 

Every year, thousands of college freshmen are introduced to Francis Fukuyama.  In his 1989 paper, The End of History, Fukuyama argued that after the Cold War, the ideological struggles of our time had ended. 

Fascism was dead. Socialism was buried. Liberal democracy had won.  Its triumphant spread might not be smooth, but it would be inevitable.

But then the Great Recession, a surging China, Russian imperialism (the time they took Crimea), Brexit, Trump, Hungary, Turkey, COVID, racial riots, QAnon Shamans, Jan 6, the withdrawal from Afghanistan, surging inflation…

And suddenly liberalism’s ascent was less certain.

Not a great fifteen years for Francis. 

But the thing is: challenges to liberalism are nothing new.  The Big 3 Problems with Liberalism have been known for over a century:

1. The Spiritual Problem.  Liberal democracy works best when we leave thorny questions like the “meaning of life” or “God’s Will” outside of government.  This is good. Religious wars and religious oppression are bad.  But it also creates a spiritual vacuum.  The focus of domestic policy becomes wealth creation because everyone agrees GDP Number Go Up is probably good.  But buying shit doesn’t provide people with a durable purpose.  A good government system should aspire to do more than reduce human beings to economic actors.

2. The Capital Capture Problem. It also costs a lot of money to run for office.  So the governing class of liberal democracy tend to be funded by the very wealthy.  The very wealthy, in turn, tend to like policies that protect their wealth at the expense of trivial things like the rights of other human beings. 

3. The Interest Group Problem.  As new interest groups organize in a democracy, they issue vetoes over valuable public policy or demand appropriations from the government in exchange for their support (Olson 1982).  These narrow interests undermine the collective good - think homeowners blocking new construction or industries lobbying for protectionist tariffs.

The 20th Century provided two (terrible) answers to these three problems: socialism and fascism. Socialism and Fascism are both authoritarian systems that override the interest group problem.  Fascism does so to solve the spiritual problem by telling citizens their purpose is national glory.  Socialism does so to solve the capital capture problem by eliminating the capital class.

But it has been 80 years since the fascist powers lost World War II.  It’s been thirty years since the Soviet Union collapsed (and longer since China stopped being really communist).

So perhaps the best reason to believe Mr. Fukuyama’s thesis is that uh… there don’t seem to be any other systems on offer?  Is it really the case that, as Winston Churchill said, democracy is just “the worst system except for the others”?  Is there room for improvement?    

A Silicon Valley truism is that today, building is the best way to complain.  One of the joys of the internet is that decentralized technology and the open-exchange of information (and increasingly value) allow for today’s Thomas Jefferson and James Madison to try radical experiments in new political systems online.  So I thought it would be fun to check in on some experiments that are testing alternatives to representative democracy.  

New year, new government.  

Choose-Your-King: The Dark Enlightenment and the Marketplace for Dictators

To a certain set of Very-Online-Humans (™), Urbit is a phenomenally interesting project to re-architect the internet from the ground-up by replacing the client-server architecture of the modern net with a peer-to-peer system.  To most of us that live in the real-world, that sentence is utterly meaningless.

So let’s make the differences inherent to a peer-to-peer internet tangible.  If I want to chat with you today, we both sign onto our texting app.  I send a message, it goes through a centrally owned server and arrives on your phone.  That’s the cient-server model.  Client: phone. Server: … er, server. 

But, imagine instead of using a shared server, I “hosted” our chat.  If you wanted to talk to me, you connected to my computer and sent me a message directly on it.  Now there’s no central server holding our information or determining if our message is appropriate.  There’s just you dropping by to say hey.  That’s a peer-to-peer model.

Got it?  Cool.

Now we don’t do this p2p thing today because managing your own server is terribly annoying and also chat works fine for 99.9% of people just by using Google or Apple or Facebook’s server. 

But Urbit is right that anytime there’s a middleman, there’s a potential for censorship, tyranny etc.  We just kind of ignore those trade-offs in our quest for convenience.  But if you are a true political believer than those trade-offs might be unacceptable.

And that’s why it’s notable that Urbit was founded by Curtis Yarvin, the court philosopher of Peter Thiel and the guiding voice of the Dark Enlightenment movement. 

The Dark Enlightenment is sometimes called neo-fascism and sometimes literally accused of wanting to bring back Kings and Queens.  But while it shares fascism and monarchy’s obsession with a strong, singular executive, it really is not totalitarian.  Just like Marx wanted a strong-central government to bridge people to socialism, Yarvin and his ilk want a strong central authority to ring in an anarcho capitalist era.

Like most libertarian fantasies, this works well if you are rich or powerful, and not so well if you are poor or weak.  It, therefore, ignores the class complaints that animated the socialist critique of liberal democracy.  It also has no place for spiritual musing – Yarvin detests the common masses that fascism sought to suppress individualism in favor of. Instead, Yarvin’s movement takes aim at the sclerosis of modern liberalism and seeks to replace it with something far more nimble – like a marketplace where you can choose a strongman that aligns with your tastes. 

And this is where the connection with Urbit is important.

Urbit decentralizes power and preserves individual choice…. To serf for any digital lord of your choosing. Indeed, Urbit sometimes describes its addresses (think of them like an email/IP address for your server) as digital land.  This land is allocated by a cascading system of “Lords.”  As Yarvin explained in 2013:

“Since there is contention for civil forts, some central party must allocate them.  Since the SFN is an SFN, there is only one way to do this: there has to be a root public key in the SFN. This uber-key is the root of all certificate chains. The rules for signing forts are simple:

  Pawn P is signed by lord (P & 0xffffffff)

  Lord L is signed by earl (L & 0xffff)

  Earl E is signed by duke (E & 0xff)

  Duke D is signed by duke 1 (the first duke)

  Duke 1 is hardcoded in the SFN.

The master of this public key is the *prince*.”

Each fiefdom carries its own rules, its own services and its own fees.  The idea is to create a competitive market of digital feudal lords. Digital citizens then vote with their digital feet.  Now, this is interesting stuff for a fringe network.  

But what’s more interesting is that this idea is jumping the chasm to the mainstream internet. 

For a long time, the digital social networks – Facebook, Twitter, YouTube – styled themselves as neutral platforms.  This was always somewhat a fiction, but it was a useful one.  Then Elon Musk’s Twitter gave up the game.  Elon’s platform policies were proud and defiant statements that the primary policy of the network was… Elon’s whim-of-the-day. Truth Social, of course, does something similar with Donald Trump.  And even Mastodon seems to have this type of an approach – with each server having its own rules and ruling elite.  

The result is an internet that increasingly looks like Yarvin’s vision:  a thousand little autocracies.  A marketplace for feudal lords.  A decentralized directory of little dictators.  May the most benevolent digital duchy win.

Liquid Democracy

Ok so anarcho-capitalism isn’t for you.  What if we tried a little shareholder democracy?

The default governance system for most DAOs and protocols today is token-governance.  A project issues governance tokens.  Members can create and vote for proposals.  Their voting power is proportional to their ownership stake.  So far, so familiar. This is, after all, a simple version of how shareholder corporations work.

Liquid democracy differs from the shareholder system because it vests far more power (and higher expectations) in the token holder.  Unlike in the modern company, there is no central management team that shareholders just casually oversee. Token owners are expected – sometimes begged! – to comment on proposals, vote on policies and otherwise be engaged in the business of running the organization.  If they are unable to do so, they are expected to “delegate” their power to representatives that will vote in their interest.

Liquid democracy tries to solve some of the spiritual problems of liberal democracy.  It is not enough – most of the time – to vote and delegate your authority to a political party.  Instead, you are an active citizen and participant in the organization.  You are expected to study the issues, engage with them and vote accordingly.  You are not an investor, you are an owner-operator of the project.  As Seed Club says, DAOs are in the business of “making something that people want to be a part of.”

But, if anything, Liquid Democracy renders the “capital capture” problem of liberal democracy even worse.  When voting power is a financial instrument, vote buyers can “borrow” voting power by taking out token loans.  In fact, if they “short” the project, they temporarily hold significant voting power while actually betting that the protocol will fail.  This unbundling of economic and governance interests is potentially devastating.  A bad actor could short a project, borrow huge amounts of shares, and intentionally sabotage it while profiting handsomely.   To combat this, protocols need to implement protective mechanisms like timelocks or “vetoes” by trusted insiders.

This challenge is not insurmountable.  Vitalik Buterin has suggested some potential fixes.  But it’s also not yet… surmounted.  Until then liquid democracy remains even more vulnerable to the Capital Capture problem than its liberal cousin.

A Nounish Liberalism

NounsDAO (you may have seen them on Twitter using this emoji:⌐◨-◨) has quietly been incubating the most interesting public good funding infrastructure in a generation.

Nouns is an NFT art project.  On August 8, 2021, the project began minting one NFT per day.  The Daily NFT was then auctioned on its nouns.wtf website to the highest bidder.  All of the proceeds from its sale were placed into the group’s collective treasury.  Today, that treasury contains ~28,000 Ethereum (or roughly $40M USD). 

But Nouns didn’t have a clear mission.  There was no clear path for deploying the capital the community had acquired.

So the Nouns team has developed and open-sourced a piece of infrastructure called Prop.House to let the community decide how to allocate its treasure.  Every few weeks, it opens up another “Grant Round” which specifies a reward and a number of recipients – for example, 10 ETH to be split between 10 projects.  Members submit proposals of work that they think would benefit the community.  Then each NFT holder receives 10 votes to allocate their support behind specific proposals.

It is governance stripped to its barebones: taxes in, spending out.

While this governance is limited in scope, that’s actually part of its appeal.  A simple model invites easier participation. 

Representative democracy was developed because leaders believed that citizens could not be trusted to stay informed or engaged with the day-to-day work of governance. Their solution was thus — let people choose representatives to govern them. Nouns take a different approach.  It reduces the cognitive load of governance, but increases the expectation of citizen engagement. 

Each voting round demands voter participation.  Members get meaning from deciding how to spend their money. They feel ownership over the art and technology that the community creates. This differs from representative democracy. When was the last time you felt personally proud to support a US government that invests in art or science?  This provides a solution to the spiritual problem of liberalism.  

And while individuals could purchase voting power by owning more NFTs, the prohibitive price tag of a vote (currently roughly $30,000 to buy an NFT that would offer 10 votes) makes the capital capture problem less dramatic.

Because the whole community votes on each proposal, the model also seems less likely to be weighed down by narrow interest group politics. 

All of this is to say that Nouns might up the ante on Fukuyama. What if we did away with the corrupting layers of representation in democratic governance and increased transparency and voter participation?  What if the answer to liberal democracy’s problems was… just a more liberal, transparent democracy?

The march toward Fukuyama’s End of History continues – one Nouns DAO proposal at a time.

Twitter was supposed to be dead by now.

The servers were going to crash.

The Nazis were going to make the site unusable.

Elon’s “main character energy” was going to alienate the core users.

His selective interpretations of free speech were going to propel anyone with principles out the door.

And yet…

We’re all still there.  Why is that?

The short answer is because Twitter does a very specific job for its users and it does that job better than anyone else.  If you want to really topple Twitter once and for all, you need to understand what that job is. It’s not enough to appeal to ideology or principle. You have to win on the merits.

And so today, we’re going to look at the world’s online townsquare and how we might be use open technology to replace it. DAOs, open protocols and blockchains all have a role to play. But this isn’t a crypto story. It’s a story about the basics of business — bundling and unbundling.

First, though, we have to answer a question:

What business is Twitter actually in? 

Free speech advocates are fond of calling Twitter a global “marketplace of ideas.”  

And, indeed, that is the business Twitter is in.  But what exactly is a marketplace of ideas?

According to the US Supreme Court, it’s part-and-parcel with America’s commitment to the First Amendment.  If we let everyone speak freely, the best ideas will win out.  Hence open debate is like natural selection for memes.  Only the truest survive.

There’s just one problem.  That’s not what a marketplace does.

A marketplace does not decide on the best or “truest” product (whatever that means). 

It decides in favor of products that people want.  It inspires suppliers to make the things that people want.

A seller in the marketplace of content is someone who creates content in exchange for status. A buyer in the marketplace of content is someone who is looking to consume content that meets their momentary needs.  They “pay” the sellers with attention and engagement. 

If people want outrage porn, the market will furnish outrage porn until that need is satiated.  If people want Nazi propaganda, the market provides, as well.  An idea doesn’t need to be true.  It just needs an audience’s demand.

Twitter’s value as a marketplace is that it is really, really good at connecting idea buyers (consumers) and idea sellers (creators).  It connects them through ranking, through trending topics, through hashtags and through search.  Wherever I look, there will be content to consume.  Whatever I create, there will be a way to discover it.

That does not enable some high-minded pursuit of truth. It enables the efficient exchange of content between people who want the status that comes from producing it, and people who want the emotional pay-off that comes from consuming it.

Why is Twitter so good at this?  Because they have built a robust, vertically integrated bundle that connects creators and consumers.

The Twitter Bundle

Jim Barksdale, the former CEO of Netscape, famously said that there are two ways to make money in business.  You can bundle or you can unbundle.  

Twitter is a bundler of four main elements.

It has a set of performant, real-time web technology that lets anyone send or consume updates from anyone, anywhere in the world.  That’s the real time infrastructure component.

It has a distinctive media format that allows individuals to communicate in short text updates of under 280 characters or an image or a video.  That’s the format component. 

It has a network/graph of creators and followers who interact with one another.  That’s the graph component.

And, finally, it has a set of explicit incentives (ranking, feedback, moderation) and implicit incentives (cultural norms, status-seeking-behavior) that cultivate a culture on the platform.  That’s the cultural infrastructure component.  

Put together, these four elements Infrastructure, Format, Network and Culture, make the Twitter bundle.

Most of the folks that want to compete against Twitter are trying to offer an alternative bundle.  They offer a new format (longer posts! Vertical video!).  

They offer a different network (only liberals! Only conservatives! Only Crypto bros!). 

They offer a different culture (say whatever heinous racist shit you want! Say only things that are acceptable in a safe space!).

The problem with these bundles is that they assume that they can hold everything else constant while improving one element. But Twitter’s offerings are tightly coupled.  You can’t actually re-create Twitter modulo one little improvement.  

So you either need to go big – and offer a totally different type of bundle like TikTok – or you need a totally different approach.  

The best way to fight a bundler is not with another bundle.  It’s to unbundle them.

How do we unbundle Twitter?

Remember: Twitter is a bundle of four things – infrastructure, format, network and culture. 

Let’s keep things simple for the moment, and imagine that we want to keep Twitter’s short-text format.  

So now, we have three items to unbundle: infrastructure, network and culture.  We’re not going to build one company that can compete.  We are going to build three new businesses, one for each component of the Twitter Bundle.

The Microblog Infrastructure as a Service

As identified by Farcaster’s Varun Srinivasan, the key features of a common, open social networking infrastructure are the ability to claim a username, to post content and to read content.  

That’s it.  So our goal is to provide the world’s best infrastructure-as-a-service for microblogging.  That means providing for unique usernames and the ability to post/read all the microblogging content that you would want.

Now this is not a new idea.  There are a few major players using different technical approaches. We might use a blockchain for this (like Farcaster and Lens intend to do).  A blockchain provides an open, decentralized datastore.

Or we could say that’s too expensive, and we could use a federated approach instead.  This is what Mastodon does.  It allows anyone to run a server that stores data and specifies ways that these servers need to interoperate.

But the problem with both of these infrastructure approaches is… they want to replace Twitter by themselves.

That’s not our game as an unbundler. We just want to provide one part of the stack perfectly.

Our game is to provide a phenomenal microblogging API service that enables you to post to/read any microblogging content in the world.  Mastodon and Farcaster don’t have all the content that you want.  

Instead they are starting by trying to compete with Twitter.  They build apps that encourage people to switch.  So you end up with a (very good) Twitter clone like Farcaster or a bunch of Mastodon servers.  And those bundles can’t compete with Twitter. 

It’s a little like this XKCD comic: 

And that’s why the key ingredient that’s missing from these approaches is Twitter itself.

As it turns out, Twitter’s API already allows people to read from and write to Twitter without using its blue-bird app. 

So why don’t we bring that in from day 0? 

Anyone who publishes to our database can have their content cross-posted to Twitter.  Anyone who wants to view content on our app can view from Twitter, as well.  Remember – our goal is not to replace Twitter, it’s to unbundle its infrastructure.

Our goal is to build an infrastructure that captures, stores and accesses all of the microblog posts in the world. So we are going to pull in content from Twitter, Farcaster, Mastodon etc. We are going to make that aggregated content open and universally accessible.

This approach is not particularly novel – Plaid does some version of this with its banking plug-ins, Matrix and Texts.com do this with messaging.  It also happens to be how Instagram grew by allowing users to publish into Facebook.

The idea is simple:  create a single, globally available access point for all microblogging content while building your own reservoir of open content.  Make that content available to anyone who wants to access it. Support yourself via some kind of protocol revenue share, API fee, etc.  That’s the service.

Network-as-a-Service

In my early days at Facebook, there was a sign plastered on the wall that read: “People don’t use Facebook because they like Facebook, they use Facebook because they like their friends.”  It’s an elegant reminder that the ultimate value of a social network is the people who use it.  

Facebook once imagined that its social graph would form the backbone of a new internet.  But the shift to the iPhone changed that.  The rolodex in your life stopped being your Facebook friends and started being your phone’s contact book. This is why, today, when you login to a new mobile app it asks you to connect your phone book rather than your Facebook friend list.

For parasocial follower relationships, the calculus has also started to shift.  Substack constantly reminds creators that its value is in “owning your audience.”  When you own their email address, you have an unfiltered channel to access your users.  Twitter and Facebook can’t take your audience away.

Our eventual goal is to build a network-independent graph.  This means that a user can login to any app, find anyone they want to follow, and receive updates from them there – much like you can choose to receive emails via Gmail or Outlook.  It’s hard (and a violation of privacy!) to reach people on a platform they didn’t select.

So what if, instead, we start from the consumer side.  We let a user import their contacts, their email address book, their Twitter following list or Facebook friend list. And we let them manage that directly from their CRM – we let them choose where and how to receive updates from the people in their contacts.  We let them know where else that contact is creating content that they can access.  We let them pull it into their client just like it’s email.

We make it easier for that user to decouple their contacts and their contacts’ content from the specific platform that they are connected to.  

And we tell creators that if they want to assure reach to fans, they should encourage their fans to follow them via our platform.  It will ensure their fans get updates on Twitter, Instagram, YouTube, Email or anywhere else.  

We become the one surefire way to assure reach between different users of many social networks.  That won’t get us all the way there.  But it’s a start to a platform-independent-graph. 

Cultural-Infrastructure-as-a-Service

Today, culture is tightly coupled to platform.  There are posts that make sense on Twitter that would not make sense on Instagram and vice versa.  But this means that folks who want to consume all the content from their creator need to buy into the cultural norms of that platform.  And maybe I really like memes on Twitter, but I don’t want to support Elon Musk’s political agenda.

When I read an email or a text message, I don’t have to worry about what that says about me.  A neutral medium gets out of the way.  A good protocol should do that.  Its job is to carry information between individuals.  But – the thing is – there’s a lot of content out there.

And Twitter’s key value is in connecting the supply of content with the demand of consumers.  Ranking, moderation, UI design, search/sort features – all of these help determine what content gets surfaced and thus influence the culture of a space.  They are the cultural infrastructure of social media.  

Although Twitter is a marketplace for ideas, it is a centrally planned culture.  There is only one feed ranking.  There is only one trending algorithm.  There is only one search algorithm.  There is only one content-moderation policy (though it changes depending on the whims of the CEO).  We can change that with our unbundled approach.

Open data and open graph means that you can choose the cultural infrastructure that you want.  You can choose a content moderation service with specific policies.  You can choose a ranking algorithm (or algorithms!) that meet your needs.  Some days you might want an AI trained to inform you, sometimes you might want one that shows you the cutest puppies.  

Rather than a single marketplace of ideas with a single matching-mechanism, we can let a thousand marketplaces bloom.  And that’s the secret to this whole strategy.

Twitter is a marketplace for content.  It connects people to the text/link content they want efficiently.  To beat it and topple it, you will need more than an ideological appeal.

You need a system with more content, more reach and better matching mechanisms.

The best way to achieve that is not to build a better Twitter.  It’s to build an ecosystem of services that render Twitter as obsolete as the Internet rendered the siloed dial-up services of old.  Then, when you post about how Twitter is dying, you might finally do it on a service other than, y’know, Twitter.

Hey friends. It’s been a few weeks. After Thanksgiving, I went Qatar to watch the USMNT get their asses kicked by the Dutch. But we’re back this week with a big piece about an organization that is doing more to advance the future of internet organizations than any other in the space. Their Demo Day is Friday. I’ll be tuning in, I recommend you do, too :)

Don’t call it a DAO

“I hate the word ‘DAO,’” Jess Sloss, founder of Seed Club, says to me over Zoom.

This is a strange admission. Jess co-founded the most important DAO accelerator.  He is the center of the DAO revolution.  Sitting across from me with a studio microphone and a long beard, he looks every part the Web3 vision-guy.

But Jess is serious.  “It carries a lot of baggage,” he says. He’s not wrong.

Blockchain projects are constantly in search of meme-market fit. They gradually evolve their terms to meet the current moment. This is why Bitcoin is – depending on the day of the week – either a faster, cheaper way to send money, an inflation hedge or a tool to fight authoritarian censorship.

The thing about decentralized products is they have decentralized narratives.  The best (read: least falsifiable, most of-the-moment) story wins.  But the problem with this narrative evolution is that people have long memories.  So when one Bitcoin story is falsified, people don’t always freely flow to the next meme.  They just remember that “Bitcoin” failed to live up to its last story.

DAOs, of course, are no different.  

They have been heralded as the future of work, the future of community, the future of cities and the future of human-computer collaboration.  But each of these stories has gaps. So in the last two years, DAOs have gone from being a utopian-pipe-dream to the-next-big-thing to a symbol of crypto’s penchant for overpromising and under-delivering.  

All of this is to say:  Jess’s point is fair. 

The word “DAO” carries its scars.  And some of those scars even predate Ethereum, the technology that enabled today’s Cambrian explosion of DAOs.

Before he founded Ethereum, Vitalik Buterin was a writer for Bitcoin Magazine.  In 2013, he published a 4-part series called “Bootstrapping a Decentralized Corporation.”  Buterin wrote that corporations were just people and contracts.  He wondered what might happen if we got rid of the people running a company and replaced it with an algorithm.  This algorithm could be a supply/demand balancer as in a market.  It could also be an artificial intelligence designed to optimize for certain goals.

If you have ever seen the Matrix, or thought critically about AI, you might reasonably ask yourself: why would we want this?  

Buterin’s claim is that an organization has built-in failure modes that code can correct.  A leader goes astray (sup, SBF).  A board misinterprets its mission (sup, Facebook).  

By anchoring the mission and the incentives in immutable code, we can guard against these very human failings.  In doing so, we allow “labor” – e.g. everyone other than management – to figure out the best ways to solve problems and then be fairly rewarded for it.  The DAO has a mission, the algorithm sets incremental goals, the people receive compensation for achieving those goals.

In Vitalik’s vision, humans and machines would cooperate to create a truly meritocratic flow of value that could not be corrupted by centralized authority. Today’s DAOs have inherited this idea that clear mission, clear incentives and no centralized control leads to valuable emergent outcomes.

But that’s about all that they share with Buterin’s vision.  Today’s DAOs are not, primarily, an algorithmic economic engine.  They have more in-common with the utopian ideals of artist co-ops and socialist kibbutzim than they do with the libertarian, cyborg organizations of Buterin’s imagination.

The Social Token Renaissance

“When bankers get together for dinner,” Oscar Wilde once said, “they discuss art. When artists get together for dinner, they discuss money.”

The dream of artists achieving compensation commensurate with their contribution to the culture has endured for thousands of years.  Sometimes those artists are painters or musicians.  Sometimes they have a sick jump shot.

In 2019, NBA star Spencer Dinwiddie decided to tokenize his NBA contract, offering investors a tokenized bond against his future earnings.  For Dinwiddie, the idea was that he could de-risk his career and begin to diversify investments.  For his fans, the idea was increased connection and the potential to profit.  The press from Dinwiddie’s initiative launched the 2019 social token era.  Dinwiddie was followed by musician RAC. Then by ASMR influencer Laurel Driskell. 

Soon thousands of influencers with an online audience tried their hands at launching their own branded token.  What were these tokens for? What did they do for buyers or for sellers? That was unclear. 

Some promised shares of future earnings. Others promised to go up in value based on the meme-worthiness of its creator. Still others offered access or consulting with a “thought leader” creator.  Like patronage, the relationship was often ill-defined and unprofitable to either side.  But amidst the craziness, some innovators saw potential.  They saw opportunities to change the economic and the social relationship between influencer and community.

It’s at this emergent intersection of financial and social engineering, that we rejoin Seed Club.

The Boom

In August 2020, Jess Sloss, Nicole d’Avis and a few friends launched a Telegram chat for their friends that they called Seed Club.  But despite comparisons to Y Combinator, the inspiration for Seed Club was a way older and simpler idea than startup accelerator.

In 1937, the author Napoleon Hill coined the term “Mastermind groups” to describe how successful people would often rely on a group of like-minded peers to test their ideas and provide feedback.  Jess had joined a few of these and wanted one for social token creators. So he started to assemble a group of friends that shared his interest and were curious about launching their own social tokens.

They wrote a Medium post soliciting other interested parties to join them.  They positioned themselves as a “social token incubator.”  But, true to the mastermind formula, they were not making investments of capital.  Instead, they were cultivating a community of community builders.  They wanted tinkerers who could share ideas and share inspiration.

 “There were lots of new ways to raise capital,” Jess recalled.  He went on, “That wasn’t the primary need for people experimenting with social tokens.”  Put another way, no one needed a banker.  What they needed was a fellow traveler.

That first “cohort” featured musician RAC, media aggregator Forefront and learning-community Kernel.  Seed Club 1 generated useful insights if no runaway success.  The Club was still in its early stages of learning, exploring and sense-making… It was quietly building momentum, but then came the Boom.

As Bitcoin surged to ~$60,000 ATHs and Ape NFTs sold for hundreds of thousands of dollars, the world grew re-enamored with crypto.  And not just any crypto – but crypto art and crypto community!  

Beeple! And Apes! And Sotheby’s! And the Constitution!  It was a heady time of speculation and infinite possibilities. 

What could a digital community empowered with tokens do? How would it function? Could it outcompete traditional organizations?  Was there any steak underneath all that sizzle?

Seed Club had been on the edges of crypto’s collective consciousness when they started exploring these questions in the DeFi Days of 2020.  

By Fall 2021, they were at the center of the zeitgeist.  

Users flooded into their Discord. Their Twitter followers grew by the thousands.  And their halo-effect started to shine on a new cohort of projects that represented a new type of community.  Gone were the creator-fan token projects.  In their place, was something more democratic and grassroots.  The central question of Seed Club DAOs became: How can an incentivized online community create and share value together?

I’ve written about a handful: gmgn, Cabin, Krause House, Songcamp, Water and Music and Climate DAO. And there are plenty of others making waves – Poolsuite, Boys Club and Twali. 

Even in a bear market, these communities have continued to build momentum.  As “get-rich-quick” Crypto Twitter, craters, their enthusiasm and momentum remains unaffected.  One of the benefits of a decentralized community, it turns out – is resilience. 

But Jess is right – DAO is not a good name for any of these new organizations.  A better one is a literal description of what they are:  Internet Native Organizations. 

The Internet Native Organization Era: From Culture to Capital

Steph Alinsug, Seed Club’s Media Steward, was one of those folks who arrived in the Seed Club Discord during the boom. But she’s no tourist. Steph started to build a reputation in the community as a great storyteller. Today she helps run the DAO.

As the community’s chief storyteller, she’s the exact right person to ask the question I’m putting to her today:  “Is Seed Club covering too much ground?  How can both a labor marketplace and a group trying to buy an NBA team both be Internet Native Organizations?  Are these really the same thing?”

“They are.” She responds without missing a beat. “What unites them all is that they all touch a real-world physical experience.” They’re about bringing people together to do things offline. That’s what unites them.  

It’s a point Jess builds on when we talk the next week:  “They’re also a network of value.  They share this property of creating real value and then reimagining how value flows through the network to the people creating it.” 

If that seems abstract, that’s only because it is. 

 “A flow of value” or a “Real world experience” is not a single tangible “thing”.  It is not a simple use case you can explain to your Mom or to your crypto-skeptic friends. But abstract ideas are powerful precisely because they can be instantiated and adapted in thousands of different ways.  They are the primitives from which great things are built.

Still – after spending time with Jess and Steph, I think I have a more concrete description.  

An internet native organization is a community of people who assemble and collaborate online for the purpose of creating and eventually capturing value in the real world.  They are the economic equivalent of group chats or Reddit Forums. 

And that flexibility is exactly why their economic impact could be as profound as social media’s impact has been on our culture.  

For over a decade now, the internet has been the wellspring of our culture.  Rappers come from Soundcloud.  Celebrities start on TikTok.  Memes start on Twitter.  MAGA started on Reddit. 

But as good as the users of the internet are at creating value, they have been really bad at capturing it.  

Value capture goes to the platforms or the vultures. This is the core insight of the piece “Life After Lifestyle” by Tobi Shorin -a piece that has become influential in Seed Club’s social circles since it was published at FWBFest this past summer.

Tobi’s argument is that the emergence of online subcultures powered the rise of the 2010s DTC brands.  An entrepreneur seeking a market could find a community of likeminded individuals on Instagram or Reddit, then sell their aesthetic and values back to them as a branded product.  As a result, there was tremendous value in trend spotting for the last ten years, but not that much value in incubating communities that can start trends.

 But what if we could change that?  What if we could unify culture and commerce?  What if we could let these online communities create, operate and profit from the goods and services that speak to them?

Imagine you’re a member of a community of surfers.  You go surfing. You watch surfing YouTube videos. You even post in surfer forums.  Today, there are brands that appropriate your style and sell it back to you.  Tomorrow, you could be a member of a community that develops products according to your feedback, sells it to other people, and shares profits with you.  When you get bored of surfing, you might even sell your early membership stake to new surfers. 

Rather than being the inspiration and the customer, you are now an NFT-carrying member of the Surfer Community.  The culture draws you in, the community creates value through your investment of time and capital.  

To put it the way Seed Club does: if Y Combinator is about building something people want, Seed Club is about building something people want to be a part of.

But to build something people want to be a part of, you have to draw them in.  And that takes one damn good Call to Adventure.

The Call to Adventure: Forming a Community

Imagine you want to organize a community to achieve a mission like, say, buying a golf course.  You need to find people who buy into that vision.  But more than that, you need to find folks who are willing to invest in it.  That investment might be capital, time or reputation.  But it's always an investment.  And investments are inherently speculation.  

“Not all speculation is bad,” Steph tells me during our second conversation.  “Speculation is optimism. It’s a bet on the future.” 

The first step in encouraging the right kind of speculation is telling the right kind of story.  Humans are narrative creatures.  We understand the world through the stories we tell one another.  Even in our own lives, we conceive of our trials and tribulations as stories.  And so if you want people to join you on an adventure, you have to convince them that their personal story will be more fulfilling if they interweave it with yours.

You need what Joseph Campbell called The Call to Adventure. 

Campbell described this as the moment a story’s hero becomes aware of a grand adventure awaiting them.  It’s Luke being asked to accompany Obi Wan. It’s Neo taking the red pill.  It’s Moses seeing the burning bush.

 It’s the moment where a community introduces a new recruit to the bigger purpose that they can help achieve.

In DAO culture, these calls to adventure are usually memes.  “We’re going to buy the Constitution.”  “We’re going to disrupt the global financial system.”  “We’re going to create the next great media company.” “We’re going to build a new city.”  

It’s the rallying cry that brings the community together.

But that meme is just a spark.  

It needs to be cultivated if it will grow into an enduring bonfire that continually engages members.  And this is where most DAOs struggle.  It’s why everyone is excited about an NFT mint but then bored by the actual community.

 To build a community with lasting value, you have to nail what Steph calls, “The Trifecta of Culture Building”.  

1. Community Practices or Rituals. - Repeated moments that reinforce membership in the community. This can be a weekly call or an annual retreat.  The more frequent the reinforcement, the better. 

2. The Product Experience. - This is the core of the community. It is how folks interact on a daily basis and what they are building together.  In the case of Arkive’s decentralized museum, it might be the process of selecting works.  It is the tentpole experience that instantiates the meme.

3. Storytelling. - Finally, there’s the mythology of the organization.  Why are we doing this?  Why does it matter?  How do I fit into a bigger vision? The better the story, the more motivated the community.

If you succeed in building this culture, your community transcends financial speculation.  It becomes a bet on the community and the culture.  And that’s how It becomes a part of members’ identity  This is why people list their affiliation with FWB or LinksDAO in their Twitter bios alongside their city, their employer and their alma mater.  It’s why profile picture NFTs are so popular.  

Seed Club has recently been encouraging more communities to use NFTs rather than ERC20s as their membership token.  That’s because NFTs are better at encouraging “the right kind of speculation.”  

In Seed Club’s experience, using NFTs rather than ERC20s encourages a more balanced approach to speculation. It still provides for exit liquidity and a freeflow of members, but it limits speculation because the nonfungibility and lower volume of tokens makes it more challenging to flip assets quickly.  Instead, it attracts people who are betting on the future of the community, but also willing to invest their reputational capital in its success.

After all, even the worst finance bros don’t use stock tickers as their profile pic. 

The Value Must Flow!

In software, people talk about two models of building: a cathedral and a bazaar.

In the Cathedral model, a visionary creates and implements a precise singular product.  Their idea, their team, their execution so they get to capture the value.

Then there’s the Bazaar model.  Just like a marketplace, a bazaar evolves as individuals, each pursuing their own incentives, build a structure that a single planner could never have anticipated. The most unexpected and interesting projects tend to be bazaars.  

Fundamentally, a DAO is a bet on the gradual power of the bazaar model.

Once a community internalizes the constraint of a mission, they can be freed to build on it quickly.  They can push it into new directions.  They can unlock value that a creator might never have imagined themselves.  

This is how a project that put 10,000 ape jpegs into the world last Spring now has worldwide events, music videos made by Eminem and Snoop Dogg, a budding metaverse and multiple independent creative projects under development. 

There’s no doubt that this model can create massive amounts of value.  It already has.  

Take Seed Club itself.  

The DAO has a token but does not require organizations that join its cohort to accept investment.  Instead it often negotiates “token swaps” with organizations that it works with, functionally forming “alliances” or “marriages” with these communities.  But its approach also creates many other avenues for capturing value.

There’s Seed Club Ventures, a separate organization that invests in technology that DAO communities can use.  There’s Seed Club’s own product team which builds technology to power the DAO and could eventually license it out to other organizations.  There’s its nascent media and branding operation that create the preconditions for a number of partnership opportunities.  This “all of the above” approach to investing in future revenue streams is emerging as a standard for the best DAO communities.  Let a thousand flowers bloom, then sell the ones that survive!

But the open question — one that Jess considers the most important confronting today’s community members– is how do you capture value in a way that ensures it flows to the people creating it?  That’s a question as old as economics.  

Adam Smith says value should flow to whoever the invisible hand decides. Karl Marx says it is stolen by capital and should be returned to labor.What do DAOs say?  It’s complicated.

 “The design space of human coordination is limitless,” Steph says.  That’s both the opportunity and the challenge for DAOs at this moment.  And the truth is there is no shortage of experiments in ways to capture or distribute value.  

If DAOs have an advantage over traditional organizations here, it is that transparency, community consensus and decentralized power should provide a check against “early” folks extracting disproportionate rents.

That transparency is already flowing into how work is completed and rewarded.  Bounty systems offer payment in a community’s native token (or in ETH to let you buy that token) for completing specific work.  There’s token grants for larger projects.  There’s PropHouse and Jokerace that both try to gamify selecting which projects get investment.  There’s Coordinape for encouraging the community to assess and reward its own members. 

Much of the excitement over Web3 is that it enables a fairer ownership structure that can more equally split compensation between owners, builders and users.  But for builders, the devil – and the opportunity – is in the details.  The good and the bad news is — there’s plenty of work left to be done here. 

Wen Moon?

Last year, when 17,000 strangers came together online to try (and fail) to purchase a copy of the Constitution, it seemed like DAOs were ready for their breakout moment.  But the momentum receded, and despite some notable projects – many from Seed Club – none have burst into mainstream consciousness just yet.

“I’m glad we haven’t had that moment,” Jess tells me. There are still lots of kinks to work out in community building and incentive design.  Seed Club has a lot more members today than it did in August 2020, but in some ways, they are still that same group of explorers, eyes trained on the horizon, exploring the digital unknown.

Still, Jess is optimistic.  There may not be a single breakout star, but there are now tens - maybe hundreds - of growing, engaged and financially incentivized online communities.  

The next massive internet movement is already here.  Just, please, for the love of God – don’t call it a DAO.

Working in crypto means that you often have to hold two parallel realities in mind.  

There’s the crypto world where “winter” has led to massive building momentum while prices languish.  Then there’s the “real world” where a close friend asked me if NFTs still exist. 

Occasionally, very occasionally, these two worlds collide in spectacular fashion.

Like when one of the crypto world’s largest exchanges helmed by its most public frontman blows up.  For one awesome second, we all exist in the same reality.

Then like light through a prism, reality fragments again. 

In the “real world”, FTX exploding proves that crypto is irredeemably broken.  It should be regulated.  It should be banned altogether.  If you have ever seriously considered its potential then you are bad and you should feel bad.

In Crypto’s parallel reality, just a few clicks away on Twitter, FTX exploding is proof that the crypto vision is necessary, just and inevitable.

Both can’t be right.  So which is it?

….

No, I’m seriously asking you.

Because surely, dear reader, you know the truth.  You are not misled.  Your beliefs are founded on a deep understanding of markets and technology. Your views are not at all distorted by self-interest or schadenfreude.  

Would that I could say the same. 

Telling what is real in moments like these is hard.  It’s a critical point where a few flaps of a butterfly’s wings will make the difference between two wildly divergent outcomes. Everyone will claim the winning perspective was obvious in hindsight. But it wasn’t.

So here’s what I’m going to do.  

I’m going to make the best case for both realities that I can via two particularly obnoxious voices in my head, Anti-Crypto Aaron and Pro-Crypto Peter.  Then we can talk about which “story” is real and which is delusional.  

You will know one of these stories already.  It’s the conventional wisdom that your reality bathes you in, so I’d encourage you to only read the one with which you disagree.  

Let’s see if we can’t shake some priors.

FTX is (more) proof that crypto is a fraud
by Anti-Aaron

How else was this going to end?

Let’s look at some facts. We have a technology that has existed for 14 years. Every use case that has been postulated for it has been demonstrably wrong. Bitcoin is not an inflation hedge. It is not a stable store of value. Its transaction fees are not cheaper than typical bank transfers. It is not empowering the global poor or making global finance more stable.  It has achieved one thing and one thing only.  It has made early buyers more money.

Oh, wait, I forgot money laundering. Yeah it does that, too.

Then you add in Ethereum.  But Ethereum’s primary use-case has been to enable peer-to-peer “contracts” which enable thousands of other tokens and unregulated entities to be speculated on in more complex fashions.  

So now, we have an entire parallel financial system speculating on arbitrarily slow computing power, memory on this slow computer, unregistered equities and various pieces of art.

This financial system is built on zero-actual-assets with zero actual value, zero regulation and zero proof-of-real-identity.  So there’s no floor on the value of assets here.  It’s empty speculation on empty promises.  And everyone is playing “don’t look down” because no one wants to admit that maybe this was a bad idea?

But that’s all prelude, right? Because FTX “isn’t crypto.” That’s what you want me to understand. It’s just a centralized investor speculating on crypto, right?  

Bullshit. 

Your whole system is centralized. .01% of Bitcoin holders control over 55% of the value.  .01% of Ethereum addresses hold 58% of the value and their proof-of-stake system now entrusts that elite to guard your “decentralized system.”  South Africa is the least equal country in the world for wealth distribution.  Yet the top 1% (that’s 100x .01%) of South Africans only own 40% of their country’s wealth.  

Congratulations, decentralization maxis, you’ve invented the world’s most concentrated economy!

Now, let me suggest something controversial.  Maybe, the people who are able to make the most money on an asset without any  real, underlying value are always going to be the smoothest talking con-men?  Maybe, just maybe, it’s inevitable that your shell game attracts the best shell game players.  Maybe people who claim to be “pro-democracy” are able to actually create oligarchies and tyrannical dictatorships.  

Maybe that’s how this goes every single fucking time.

But “it’s early” you say. 

Wait wasn’t the whole idea that once we get enough people involved, enough capital deployed, enough… I don’t know, momentum?... that it would magically become real.  I’ve read Sapiens, too. You people didn’t invent shared myths.

So - crypto has spent ten years saying it’s the “future of finance” and looking for ways to break into the mainstream. And FTX helped you get the poor normal people bought in on your grift! It let everyone do all the fun stuff that you won’t shut up about – betting on all these random investments, letting retail investors pursue complex trading strategies.  

What is FTX but the realization of your crypto dreams/nightmares? 

And, no this isn’t all about fraud.  At least not the kind that you claim is the real culprit.  The bottom fell out of the market because it had no value. The emperor had no clothes. Crypto was seen for what it was – massively overvalued! – and that crushed the “value” of your imaginary digital magic money. FTX fell on the same sword they were selling. 

Their fraud is incidental.  It’s marginal.  The real fraud is that every asset on their “balance sheet” was worthless and inevitably going to go to zero at some point.  The fact that it did so quickly enough that it spurred fraudulent behavior is just the icing on your corrupt cake.

The only way out of this mess is for crypto to add actual value, add regulation and add real identity.  But, you see, that space is already taken by the actual financial sector (TradFi, that’s what you call it, right?) that you all claim to hate so much.

This ending is poetic. It’s just. And with any luck, it will be the end of this entire chapter in our weird internet history.

It ain’t early, bro.  It’s over.

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FTX is proof that crypto is necessary
by Pro Peter

Before we talk about FTX, I want to tell you a story about my friend.  She used this Robinhood-like stock-trading app called TechExchange to invest in tech stocks.  

TechExchange was a platform for investing in major public market tech companies.  But they also had an ill-defined relationship with a separate hedge fund called Piedmont Equities.  

Piedmont and TechExchange, both started by the same guy, right?

And here’s what happened – Piedmont made some really bad bets on Peloton (-94%), Netflix (-55%), Facebook (-67%) and Snapchat (-86%) over the last two years.  Woof.  

So then, the founder of TechExchange/Piedmont sold a bunch of his TechExchange clients’ stock to help Piedmont cover its losses.  He imagined that the market couldn’t stay bad forever, so if Piedmont made some smart bets they would win it all back. Then they could top-up those accounts he “borrowed from” and no one would be the wiser.

Now, to be clear, this was illegal both by law and by the terms that TechExchange offered its users. But hey! It would be totally fine as long as Piedmont didn’t lose the new money, and as long as everyone didn’t try to withdraw their stocks at the same time.  

And honestly, what were the odds of that?

Except that “when it rains it pours.”  The CEO of a rival stock trading app, who happened to also have been an early investor in TechExchange, tweeted that he had lost faith in the company. He said he was selling all his stock. He said he was withdrawing all of his holdings from TechExchange.

Now there’s panic and a bank rush!

So people started asking for their stocks back all at once.  Of course, TechExchange can’t do this because they had broken the law and their Terms of Use.  They have nothing to return to their customers. 

So the firm collapsed. Taking its customers’ net worth with it.

My friend, she’s drawing the right lessons from this. Tech Companies are all scams! Stocks are evil!  We should never invest in any of it ever again.  We should probably forget the whole “tech” bubble ever happened.

…

Ok, I know this is obvious, but that’s the story of FTX.  And that closing point about never investing in tech stocks again, that’s what these weird anti-crypto crusaders want you to believe is the obvious consequence here.

But, here’s the truth:  FTX’s collapse has nothing to do with the blockchain. It has to do with a bad CEO doing sketchy things.  

And you say, “Well, regulation is the answer!”  Except that Enron was regulated. And Lehman Brothers. And AIG.  That system has had hundreds of years to root out bad actors.  Tell me, my self-righteous friend, how is that working out for you?

Look – bad actors are going to do bad shit.  You say we need to trust regulators, I say we should trust no one.  We should prevent anyone from being powerful enough to shake the markets like this. We should have absolute transparency so we can hunt down every bad actor before they can do harm.  You want a regulatory state.  I want a state of transparency.

Imagine instead a system that works like this: 

1. When you invest money, you can see exactly what your trustees are doing with it.

2. You never have to worry about bank solvency because you can withdraw your money at any time. In fact, it’s always under your complete control!

3. To prevent any one actor from becoming a systemic risk, we keep all of our critical infrastructure operating – like email – on a protocol that no one owns.

Is that something you might be interested in?  My guy, that’s what we’re trying to do!

And here’s the crazy thing:  the collapse of FTX only happened because our system works.

The only way we caught FTX was because of transparency.  A journalist reported Alameda’s (the real-world equivalent of “Piedmont Research”) balance sheet looked sketchy.  Then, when their team tried to tell us everything was under control, we could watch as a bank-run started and their wallets stopped processing transactions.

We could catch them (or another party — unclear as of writing) trying to steal from their customers in real-time! All on-chain! 

What traditional banking regulator could ever do that?

Without that open ledger, who knows what happens?  I’ll admit I was taken by Sam and would have bet on him over Binance.  That’s because charlatans win in political systems and facts win in open-systems.

As for systemic risk – okay, that wasn’t great.  We let FTX get too big, too quickly. But the decentralized protocols all stayed up: Uniswap, SushiSwap, dy/dx, the Ethereum chain itself! Nothing fell. Even Solana – which had FTX as a major investor – has rallied and kept all their critical infrastructure working.  

Our system works!  It needs refinement, but the proof is there!

The problem is that we haven’t gone far enough.  

FTX was not a blockchain entity.  They were a bridge between the old world and the new world.  They took people’s money and then used it to speculate in crypto.  They were just an unregulated bank.  They found a regulatory blindspot and worked that loophole for everything it was worth.

In the old world, we have regulation.  In the new world, we have on-chain transparency and decentralization.  FTX found a weakness where those two worlds meet.  You say it means go backward.  You say that crypto has gone too far. I say it means we have to go farther.

And here’s the fun part. That’s happening. Maybe you missed it but Nike announced NFTs on Monday. JPMorgan(!) pointed out that protocols were not to blame. Then the NYFed announced a pilot Central Bank Digital Currency.

My brother, if you’re not ready for the revolution that’s fine, press snooze for another couple years.  We’re going to figure this out. It is still so fucking early.

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Back to Shared Reality

If I can bring us back to some sense of shared ground here, there’s actually a lot the two sides agree on.  FTX was a bad actor. They committed fraud.  I think even our Pro-Crypto Peter would agree that crypto has a way of attracting bad actors. 

The conflict, the core open question of this debate are these three simple questions:

1. Do crypto projects create value other than speculation?

2. Is transparency or decentralization possible in the financial system and if so, can it prevent bad actors?

3. Is decentralization feasible in the current crop of cryptocurrencies?

Point 1 is a big debate, and I’m going to leave it alone.  I have weighed in elsewhere.

Point 2 – well, there’s a Rohrschach blot here.  Crypto tools helped catch the fraud, but regular regulation might have prevented it altogether.  

Point 3 – The trends are favorable. The economy is getting less centralized over time. But the crop of VC projects funded during boom times are not going to help. Nevertheless, the key isn’t equality here, it’s provable neutrality. And Bitcoin’s controlling .01% is still 7000 people. It’s hard to get that many people in on a conspiracy.

The bad news for Pro-Crypto Peter is that the regular people are going to be scared away for a good, long while.  

They see repeated fraud, and they don’t care about all of his nuances or promises of progress.

The good news for Pro-Crypto Peter is, ironically, that the regular people are going to be scared away for a good, long while.

 The tools appealing to them – by offering UX benefits without fulfilling the promise of decentralization and transparency – are going to wither on the vine.  Only the true believers are left.  Only technology that appeals to their values will win.

Crypto’s next few years are make or break. If the community can create real value, if it can prove that transparent markets allow “white blood cells” to catch fraud and prevent it from spreading, then they will have earned the next boom time.

If they can’t – well – from zero your magical internet money came and to zero it will return.

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Richard Feynman once said that if all of scientific knowledge were to be erased, and he could only preserve one sentence, it would be: “that all things are made of atoms — little particles that move around in perpetual motion, attracting each other when they are a little distance apart, but repelling upon being squeezed into one another.”

Feynman’s sentence is predicated on the same idea that animates the XKCD comic above: that science is fundamentally a reductionist project. It’s about taking big things, breaking them down into small things and understanding how those work.  That idea is taken as an article of faith in most of science.  But there’s an alternative view that’s been gaining currency for the last few decades.

In 1972, Nobel Laureate and Physicist PW Anderson published, “More is Different.”  Anderson’s argument was that there are things that happen to big systems which we could not, even in principle, predict just by looking at the properties of their parts.  This idea that the sum is literally greater than its parts is called “emergence.”  To cite a few canonical examples: we can’t predict the wetness of water from hydrogen or oxygen atoms, we can’t predict life from carbon atoms, etc. 

Wait.  Why are we talking about physics?  

Well – because the implication of “more is different” is very relevant to human systems.  We cannot, even in principle, predict what is going to happen when you get millions of people together online and ask them to communicate, trade or govern themselves.  As a system gets progressively more complicated, theory ceases to accurately describe systems.  The only thing to do is, to put it bluntly, fuck around and find out.

And this seems like a good week to talk about this because we are witnessing two attempts to govern complex, emergent systems with their own kind of feedback loops. First, there’s Elon who has been fucking around and finding out on Twitter.  Second, there’s the American midterm elections which offer a report card on the fucking-arounds of Joe Biden and the Democrats’ government. (Ed note: And though we won’t talk about it here, it seems SBF did his own bit of costly fucking around and finding out…)

The problem with both loops – a speed running autocracy and a messy democratic election – is that they’re broken.  Good feedback loops – the kind needed to experiment in and course-correct emergent systems– are pretty easy to describe.  

You need: 

1. The ability to accurately measure an outcome (Did this change result in more revenue?);

2. The ability to isolate the impact of your initiative on that outcome (Was it really our project that made us that revenue?);

3. The ability to do this on the smallest, viable timeframe (How long will it take to learn this?);

4. The ability to iterate if things aren’t working; (Do we have accountability/control to change course?)

They’re just very difficult to implement.  Getting all four criteria for a feedback loop right is subtle, delicate work.  But then: Elon.

Elon and Unaccountable, Unmeasured Speed Running

A few weeks ago, the House GOP Judiciary Committee tweeted this (for reasons surpassing understanding and further proving we live in the strangest timeline):

It’s a weird tweet (for a number of reasons).  But it might also be kind of insightful?

Trump would throw out half-baked thoughts. He would then see how the blowback erupted. It was a destabilizing and exhausting way to run a government. But it was an extremely efficient way to get feedback.  

Elon is playing the same game. Twitter was an infamously slow company. A decision on broadening blue-checkmarks or what to charge for them would have taken months – maybe years to ship.  It might still have missed the mark.  But Musk’s philosophy for learning and guiding emergent behavior is simple: dumb and fast beats smart and slow.

And that’s how we get user research happening in real time with best-selling horror author Stephen King:

This is product management by natural selection.  After all, natural selection is just nature testing random shit and seeing what works.  And that gave us Keanu Reeves.  So it has something to recommend it.  

But lest you think this is just an Elon-fan-post, I don’t for-a-second believe that Musk’s “damn the torpedos” attitude is going to let him solve problems that lots of smart people have tried and failed to address. And that’s for one simple reason: his feedback loop is also busted. 

In natural selection, genes combine and mutate to test our new traits.  New, better combinations win out as nature weans itself through the competition to survive. As a result, nature learns and improves. 

Can Elon? The problem with being a dictator surrounded by loyalist fanboys is that no one tells you you’re wrong. 

Elon is smart. He wants signal. I think that’s why he is so active on Twitter. But he’s also prone to the same mistakes of motivated reasoning and cognitive bias that all of us are.  Without external forces to hold him to account, he’s probably going to fuck things up badly. 

And that’s why - to govern giant complex systems - we have designed other accountability mechanisms – like, say, elections. 

The Worst System Except for All The Others?

By the time this is published on Wednesday, it will either have been a good, bad or inconclusive night for President Joe Biden.  

But what will this election tell us about what the American people want? If Democrats win, is it a referendum on saving democracy? Is it about gas prices falling? Is it about the overturning of Roe v. Wade?

If Republicans win, is it about inflation? Is it a normal structural backlash to the in-power party? Is it a ringing endorsement of Trump and MAGA candidates?

Who knows!  

In 2012, the Republican Party was confident of victory.  When they lost, they commissioned a report to tell them what to do next.  And that report told them that the only path back to power was softening rhetoric on immigration, appealing to women and generally embracing a more diverse, progressive country.

So they ran and won with **checks notes**... Donald Trump.

Countries are definitely prone to emergent, unpredictable behavior. Democracy’s best characteristic is that it has peaceful means of accountability.  When something isn’t working, we can change course.  If it is working, we can double down.  

That works sometimes.  But our system has its own problems with feedback loops: its feedback is non-specific.  In the coming election, people will choose who to support based on a number of issues – inflation, health care policy, abortion, democratic values, crime etc.  A reasonable person might have some heterodox but completely logical views across this matrix of options.  They might think that spending causes inflation, that we need more health care support for needy families, be pro-life, anti-election-denier and pro-police.

How do they signal that the government should correct in this direction?  They can vote Blue which hits about half of their values. They can vote Red which hits the other.  

Neither decision will communicate their actual policy preferences to the government.  That means we don’t have any precision to our feedback loop.  The question that animates me is: could we do better? 

What would a better system look like?

It won’t surprise any of my readers or anyone who has heard me talk in the last year that I think DAOs provide a playground to improve the governance of complex systems.  And my reasoning for that is simple –  DAOs provide an opportunity to build better feedback loops than corporations, with more precise accountability than our electoral system.

In a 2013 blog post, Vitalik Buterin asked if we could build better organizations by eliminating human management altogether: 

But what if, with the power of modern information technology, we can encode the mission statement into code; that is, create an inviolable contract that generates revenue, pays people to perform some function, and finds hardware for itself to run on, all without any need for top-down human direction?

Put another way:  can’t the AI just solve this for us?  

Let me cut to the chase:  No, it can’t.  No GPT3 text prompt is going to tell you how to define an ideal government for a complex collection of people and needs.  But Vitalik’s instincts aren’t totally wrong – we can get a long way by doing a few things:

1. Clarifying the mission of an organization;

2. Empowering specific teams with clear rules on how to achieve those missions;

3. Letting those teams compete for rewards that will be assigned based on a vote by all stakeholders;

4. Measuring their progress against their stated goals and then deciding whether to extend or kill their workstreams.

Now, no DAO is doing this exactly today.  But the individual governance legos are starting to emerge.  You still have to write out your human mission the old-fashioned way, but if you do that, you can learn and iterate quickly and publicly using this set of tools.  And the organizations that adopt them will be able to out-compete the outmoded top-down speed of a corporation or the lossy representativeness of traditional electoral democracy.

1. Small, accountable organizations with Metropolis.  Metropolis is a set of tools that enable an organization to operate as independent pods.  These pods have their own rules, their own mission and their own funding.  They can operate collectively or independently to achieve a group’s mission.  They’re federalism in action.  

2. New mechanisms for incentivizing the right actions with PropHouse and Coordinape.  

   1. Prophouse by Nouns.  The Nouns community invented and has now publicly launched a tool called Prophouse.  It allows any group of people to set a prize pool (say 5 Ethereum), a theme (“What party should we throw?”) and then vote on how to allocate the prize amongst proposals made by members.  It’s a democratic way to choose specific policy ideas from a community.  The discrete ideas, and their proposers, can then be evaluated based on outcomes.  It keeps feedback loops tight and accountable.

   2. Coordinape.  Coordinape enables decentralized “peer bonuses” in a community.  Members decide on how much budget to allocate for the period (say a month).  Then each member gets to award “points” to the members they think did the most valuable work.  At the end of the month, payment is distributed to users proportionally based on the points that they received.  This mechanism encourages everyone to collaborate with everyone.  It’s a p2p way to encourage teamwork.

3. Public and open data to track progress with Dune. One of my favorite things about writing about communities in Web3 is that I can see **all** of their data – even when I’m not a member.  A simple trip to Dune.xyz reveals a world of dashboards measuring every community’s KPIs.  This open data allows anyone to assess what’s working. It is a source of real time truth that allows for quick iterations and improvements.
   

Independently, each of these tools is an interesting organizational innovation.  Taken together, they’re signals of the potential of a new type of organization that helps a community to harness the emergent intelligence of its network.  Allowing insights and leadership to emerge from anywhere enables a network to learn at the speed of its fastest nodes.

It’s governance that can actually keep pace with the governed. Feynman was right that the world is made up of individual pieces, but it's only through bringing those pieces together that we see the really interesting stuff.  More, it turns out, isn’t just different.  When it comes to feedback in complex systems: More is better.

To be human is to be in love with music.

It is both our most personal and our most social art form.  It’s sad songs on a lonely walk home.  It’s the collective roar of a crowd bellowing a refrain back at a lead singer.  

Yet the music business is one giant tragedy of the commons. Music creates massive value in our world. But capturing that value has bedeviled artists and entrepreneurs since the classical era. For hundreds of years, it was only the gifts of the upper class that kept professional music alive.  A single Austrian baron was the patron that allowed Mozart and Beethoven to practice their art. Even today, artists struggle to make ends-meet by mixing streaming, merch sales and performing.  

It’s a rite of passage for every technology to claim it can fix this state of affairs only to ultimately put profits in the hands of a new middle man. And that reality has made the relationship between the music business and technology industry an uneasy one for over a century. 

In 1906, John Phillip Sousa – composer of America’s best-known marching band music and the Jack Antonoff of his day – worried that records were an existential threat to the artists.  In 1942, the American Federation of Musicians announced a general strike against recorded music on the radios.  And of course, the recent trials of musicians in the streaming eras needs little introduction.

But with their signature lack of regard for history, crypto’s innovators have emerged to promise that, “This. Time. Is. Different.”

I’m skeptical.

But after researching the intersection of blockchain and music, I’m confident the era is going to shake things up in both how we listen to and pay for music. What’s less clear is whether it will benefit the next generation of musicians or just the next generation of middlemen.

The 20th Century in Music: The Private, the Public and the Profitable

At the turn of the 20th Century, the consumption and commercialization of music was simple.  You paid to hear an artist perform live.  

Records were often derided as a niche novelty. In 1886, Harper's Magazine wrote that Mr. Edison’s device “failed to make a success, for the reason that the machine was not only a clumsy piece of mechanism, frequently getting out of adjustment.”  Only 4 Million records were sold in 1900.  In contrast, Taylor Swift’s most recent lead single, “Anti Hero” received 60M plays in its first week.   

Because music was largely only consumed live, there were endless jobs for musicians. Every bar that wanted music, every theater that needed an orchestra, every Church that needed an organ player had their own musicians on staff. 

Mass Music

By the 1920s, that was starting to change.  The direct relationship between creator and community was severed by new technology.  Instead, we created an unprecedented concentration in the music market. 

As phonograph and radio sales increased, recorded music overtook live performance as our preferred mode of consumption. We needed less live musicians.  We just needed a few major musicians and a massive distribution network to put their records in audiences’ hands.  

Mass Media culture was born and with it came the record industry.

In this era, distribution was king. A talented artist needed the cooperation of a major label to get their art into record stores or on the radio. A select few artists lived like Kings, but the entire “musical middle class” that had powered bars and theaters during the nineteenth century was eliminated. 

That was a rough state of affairs, but the market adjusted. 

Record labels perfected a business model that involved scouting for talent, producing their projects, promoting them in record stores and radio stations and profiting off of every performance – radio rights, album sales and live concerts.  There were less artists, but more suits that managed the industry.  

But the art was still good! We got the Beatles and the Backstreet Boys. We got NWA and Nirvana.

Streaming Splinters the Industry

The distribution moat that had been dug by the labels was bridged by the nerds that built Napster, iTunes and Spotify.  With no middlemen between the artist and their listener, any listener could find any artist that appealed to them. This powered the rise of small labels and indie artists.  It sought to disrupt the concentrating power of the music industry. In the place of mass culture, we had massively divergent subcultures that could support many more musicians.

That solved everything then, right? We had unlimited access to music and new artists could rise based on merit, right?

Well, no, not quite.

90% of Spotify’s royalties in 2020 went to less than .8% of its artists – and only .2% earned over $50,000.  A survey of working musicians shows that most have to turn to alternative means from streaming to earn money:

The Streaming Era was an incomplete revolution.  It brought thousands of new artists into the public consciousness, but it did not offer a path for these artists to earn a sustainable source of income.  The question confronting the creator class today is whether a smaller, but highly engaged audience is capable of financially supporting the artists they love.

Web3 claims it has the solution. Well many solutions actually.  

Block n Roll

Every technology struggles to find product market fit. That’s not unique to blockchain. But what is unique is that blockchain seems to also be searching for meme-market fit.

In fact, in each of the three Bull Runs of the last twelves years there has been a new narrative about how blockchain will revolutionize music.  None is a panacea.  But each provides an interesting signal on where things may be headed…

The Enterprise Blockchain and The Open Music Database (2014-2018)

In 2013, Bitcoin prices spiked above $1000 for the first time.  The digital currency – long accused of being mostly a tool for nerd sniping or drug dealing – started to attract some real attention.  But this was the era of “Blockchain but not Bitcoin” – the soundbite that made every investor sound smart without really meaning anything.

It also was the beginning of Ethereum and the first programmable blockchains.  People (ok, cryptonerds…) began to understand the idea of a “shared ledger” (an open database not owned by anyone) and “smart contracts” (self-executing agreements). Berklee College of Music’s Rethink Music Initiative imagined an open blockchain that tracked every song ever written and allowed easy licensing/tracking of usage on a collectively owned chain.

That idea captured the imagination of indie fav Imogen Heap of “Hide and Seek”/”Goodnight and Go” fame.  In 2015, she announced Mycelia.  The project was intended to be an open registry of all recorded music rights on the planet. Heap imagined that a global, open, blockchain based registry would allow anyone to directly license or play music and that the funds would flow through smart contracts directly to the artists rather than through the middlemen that populate the industry.  She put her own project where her ideals were – releasing the single Tiny Human on the platform.

She wrote about the decision in the HBR in 2017, 

“I began by posting everything about that track on my website for anyone to experiment with and for fans to enjoy. Phil Barry at the Ujo Music platform joined in, which resulted in Tiny Human being the first song ever to automatically distribute payments via a smart contract to all creatives involved in the making and recording of the song.”  

Heap’s enthusiasm and experimentation were the first instantiation of two big ideas that continue to animate blockchain exploration in music: open data and smart contract based ownership.  But she also encountered the reality that the hype on blockchain far outpaced its real usage. 

”It was very basic — no licensing terms were exhibited — and it raised little money, due in part to the fact that you had to have an Ether wallet with Ether in it (the crypto-currency used on the Ethereum platform) before you could purchase the track, which lost some people along the way.”

Heap encountered a very-real network cold start problem.  To move artists, you needed enough fans using Ethereum.  To move fans, you needed enough artists releasing music exclusively on the platform.  

That’s a problem for blockchain based apps that would linger until the next crypto bull run offered a solution.

The ICO Boom and Artist Owned Platforms (2018-2020)

In 2018, the tech world was captivated by the quick rise and fall of ICOs.  Projects seemed to come out of nowhere, raise millions of dollars through token sales, then collapse into the ether again.  For many, the appeal was getting rich quick.  But for others, the projects were philosophically bound to the idea that ownership should be more fairly distributed.

As a blowback against the major tech platforms started to form during the late-10s, the crypto community began to imagine community-owned alternatives.  

What would it look like if drivers owned Uber or video creators owned YouTube?  

A musician owned Spotify/Soundcloud seemed like a natural fit. Audius, which explicitly positioned itself as a Soundcloud alternative, emerged as the market leader.  Artists earn the platform’s $AUDIO tokens/ownership for publishing music.  Fans use these tokens to unlock experiences or compensate artists.  

The user-owned platform has solid traction – and has even crossed the chasm — by appealing to EDM and hip hop artists, they have 7M monthly listeners.  Most impressively: only 10% of those listeners are active crypto users, otherwise.

Audius is an attractive option for new and emerging artists. It’s important work. But it is a business model innovation rather than a medium-shift.  Records and streaming both changed the way fans listen rather than just the way artists were paid.  The next interesting question for Web3 is whether it can disrupt more than ownership.  

Can it change the way we listen to and create music?

The NFT Boom and the Search for Community “Utility” (2021-2022)

The 2021 Bull Run was the era of the NFT.  If visual artists could make millions on digital monkey JPEGs, surely we should have a musical analog. But owning music NFTs just didn’t seem to capture users’ imagination in the way that profile pictures did.

The Music NFT market is not trivial.  According to research by Music and Water DAO, 1240 artists have sold over $182M in Music NFTs since June 2020.  That’s a lot.  But despite some worthy experiments – Kings of Leon offering lifetime concert access to NFT holders and Royal offering a split on song royalties – none of these projects has broken through into widespread awareness in the way that a Bored Apes or Cryptopunks has. 

I think that’s because musicians needs to look less at the work of visual artists and more to their own history.  Visual art has always associated status with ownership.  Status in music has always worked differently. The streaming revolution showed that people were perfectly happy to “rent” the rights to listen to music.  That’s because status in music does not come from ownership. It comes from being a creator or a curator.

We can earn status by creating music or remixing the music of others. We can also earn it by being a tastemaker that’s the first of a social group to discover a new artist.  So an NFT that actually reflects this status would need to work differently than just “owning” a song.

The core framing of the debate around the music industry has recently been How do artists get a larger share of the pie?  But what if that’s the wrong question. What if the better question is this:  How do we create a system that reflects and compensates the value that each contributor – creator and curator – add to the ecosystem?

That’s a job for the economically incentivized networks called DAOs.

This idea – that music should be a collective creative project that rewards contributors with social and financial capital – animates Songcamp.  

The group convenes a community of musicians, engineers, marketers and other contributors to collectively create and distribute an album.  In one “season” or creative chapter, groups of Songcamp artists worked for two weeks to produce songs, then shuffled themselves and produced again until they had assembled an album.  In another, they produced an interactive game with music at its core.

Members are compensated using a combination of UBI from crowdfunding grants, peer-bonuses and NFT royalty shares. 

Songcamp highlights what Web3 music could look like.  It is a project that breaks down the dichotomy between artist and audience.  Instead, it centers the creative collaboration between members of the musical subculture.  

It invests fans with agency and ownership.  It rewards artists with a built-in community of zealots.  It is a return to our roots – a group of musicians entertaining and collaborating with their community to create value for all involved.

If Web3 can help us to cement this dynamic, while also leveraging the open platforms and data of past bull-runs, the potential value is limitless.  It could actually be a way to make music personal, public and profitable – all at the same time.

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